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In my last post, I started off by providing a rationale for a terminal value and presented alternatives to the perpetual growth model. That said, most DCFs are built with the the perpetual growth equation, setting up for a potential valuation disaster. Mathematically, the denominator is a powder keg waiting to blow, since as you increase g, holding the cash flow and r constant, your value will approach infinity before turning negative, leading to what I call âBuzz Lightyearâ valuations.

The Growth Cap
If you want to draw on the perpetual growth equation, either because you believe your business will last forever or for convenience, the growth rate that you can use in it is constrained to be less than or equal to the growth rate of the economy in which you operate. This is not a debatable assumption, since it is mathematical, not one that owes its presence to economic theory. Within this statement, though, there are estimation choices that you will have to face about how to define the growth cap.

Domestic versus Global: As a cap, you can use the growth in the domestic economy (if your company will remain a purely domestic operator) or growth in the global economy, and the economyâs growth rate has to be computed in the same terms that you are using for the rest of your valuation. That may seem to give you license to use high growth rates for emerging market companies but I would suggest caution, since emerging market economies as they get bigger will tend to see their growth rates move towards a global growth rate. Thus, while it is true that the Indian and Chinese economies have higher real growth rates than the global economy in the near term (5-10 years), they will see their growth rates converge on the global average (closer to 2%) sooner rather than later.
Real versus Nominal: In an earlier post, I argued that one of the hallmarks of a well-done DCF is consistency in how cash flows are defined and discount rates are computed. Specifically, you can choose to estimate your cash flows in real terms or nominal terms, with the former reflecting growth without the helping hand of inflation and the latter inclusive of it. If your valuation is in real terms, the cap on your growth rate will be the real growth rate in the economy, and if in nominal terms, it will be the nominal growth rate.
Currency: If you choose to do your valuation in nominal terms, you have to pick a currency to denominate your cash flows in, and that currency will have an expected inflation component attached to it. The nominal growth rate cap will have to be defined consistently, with the same expected inflation built into it as well. Thus, if you are valuing your company in a high-inflation currency, your nominal growth rate forever can be much higher than if you value it in a low-inflation currency.

What if your company is in a high growth sector or a high growth market? The answer lies in the "forever", since no sector or market, no matter how high its growth is right now, can continue to grow at a rate faster than the overall economy forever. One of the greatest perils in valuation is ignoring the growth cap, either because you forget the mathematical basis for why it exists in the first place or because you have mismatched your cash flows and your discount rate, perhaps estimating the former in a high inflation currency and the latter in a low-inflation one or vice versa.

A Risk Free Rate Proxy?

If you accept the rationale that growth is capped at the growth rate of the economy, you are now confronted with a daunting and perhaps impossible task, i.e., to value an individual company, you will now have to estimate expected growth rate in the economy (domestic or global) and expected inflation in the currency of your choice. I, for one, want no part of this estimation challenge, for two reasons. The first is that I find long term macroeconomic forecasting to be a futile exercise and have absolutely no faith in either myself or the institutional entities that claim to be good at this task. The second is that any time I spend on these macroeconomic forecasts is time that I am not spending on understanding my company and its business, key to valuing that company. Consequently, I use a simpler and more easily observable number as a cap on stable growth: the risk free rate that I have used in the valuation. Not only does this take into account the currency automatically (since higher inflation currencies have higher risk free rates) but it is reasonable to argue that it is a good proxy for the nominal growth rate in the economy. Since it is the component of my valuations that I am taken to task most frequently about, I have three arguments to offer and while none standing alone may be persuasive, you may perhaps accept a combination of them.

1. An Empirical Argument:
To understand the link between the risk free rate (a nominal interest rate) and nominal economic growth rates, consider the following decompositions of both:

Risk free rate = Expected Inflation + Expected real interest rate

Nominal economic growth = Expected Inflation + Expected real growth rate

The table below the risk free rate in US dollars (measured with a ten-year treasury bond rate) and nominal economic growth (the sum of expected inflation and real GDP growth) from 1954 to 2015 in the United States, broken into two sub-periods.

Period	10-Year T.Bond Rate	Inflation Rate	Real GDP Growth	Nominal GDP growth rate	Nominal GDP - T.Bond Rate
1954-2015	5.93%	3.61%	3.06%	6.67%	0.74%
1954-1980	5.83%	4.49%	3.50%	7.98%	2.15%
1981-2008	6.88%	3.26%	3.04%	6.30%	-0.58%

The nominal GDP growth rate was about 0.74% higher than the risk free rate over the entire period (1954-2015), but it has lagged the risk free rate by 0.58% since 1981. I know this table, by itself, proves nothing, but there is reason to heed to the link. In the last few sixty years in the United States, nominal interest rates and nominal growth have been closely tied to each, with an increase in one tied to an increase in the other. It is true that there is evidence in the data, especially in the 1954-1980 time period, that real growth can exceed real interest rates for extended periods, and economic intuition provides a rationale for why. If those who take no risk earn the riskfree rate, the economy, at least on average and over long time periods, has to deliver a little bit more to reward the risk takers. However, not only can that differential not be a large number but it is also worth remembering that the nominal growth rate is the growth rate in the entire economy, composed of both mature and growth companies. If you allow every mature company to grow at the rate at which the economy is growing, what does the growth come to sustain the growth companies in the economies? Put differently, setting the growth rate for mature companies below the growth rate of the economy cannot hurt you but setting it above that of the economy can cause valuations to implode. I'll take my chances on the former!

2. A Consistency Rationale
If you are not convinced by this reasoning, I will offer another reason for tying the two numbers together. When you use a riskfree rate in a valuation, you are implicitly making assumptions about economic growth and inflation in the future and if you want your valuation to be consistent, you should make similar assumptions in estimating your cash flows. Thus, if you believe, the risk free rate today is too low or even negative (because the central banks have kept it so), and you use that risk free rate to come up with your discount rates, you have to keep your growth rate in perpetuity very low or negative to keep your valuation from imploding. That is the point that I was making in my post on negative interest rates. In the last decade, as interest rates have hit historic lows, the danger of this mismatch has become greater. Analysts have been quick to shift to using the lower risk free rates (to 2% or lower) in their discount rate calculations while continuing to use nominal growth in the US economy (5-6%) as the cap on their growth rates. That is a recipe for disaster!

3. A Self-Control Basis
There is a third and final reason and this may reflect my personal weaknesses. When I value companies, I know that I fight my preconceptions and the urges I feel to tweak the numbers to deliver the result that I want to see. There is no number that can have more consequence for value than the growth rate in the terminal value and having a cap on that number removes the most potent vehicle for bias in valuation.

In sum, you may or may not be convinced by my arguments for capping the perpetual growth rate at the risk free rate, but I would strongly recommend that you create your own cap on growth and tie that cap to the risk free rate in your valuation. Thus, you may decide a looser version of my cap, allowing your perpetual growth rate to be as much as (but not more than) one percent higher than the risk free rate.

Conclusion
The perpetual growth model is a powerful device for applying closure in a discounted cash flow valuation but it is a mathematical honey trap, with the growth rate in the denominator acting as the lure for analysts who are inclined by bias or ignorance to play with it. If you are tempted, it is worth also remembering that it is the first place that that people who are well versed in valuation look to check for valuation ineptitude, since there are far more subtle ways to bias your valuations than playing with the growth rate.

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DCF Myth Posts

Introductory Post: DCF Valuations: Academic Exercise, Sales Pitch or Investor Tool

If you have a D(discount rate) and a CF (cash flow), you have a DCF.
A DCF is an exercise in modeling & number crunching.
You cannot do a DCF when there is too much uncertainty.
It's all about D in the DCF (Myths 4.1, 4.2, 4.3, 4.4 & 4.5)
The Terminal Value: Elephant in the Room! (Myths 5.1, 5.2, 5.3, 5.4 & 5.5)
A DCF requires too many assumptions and can be manipulated to yield any value you want.
A DCF cannot value brand name or other intangibles.
A DCF yields a conservative estimate of value.
If your DCF value changes significantly over time, there is something wrong with your valuation.
A DCF is an academic exercise.

The perils of holding all else constant in perpetual growth equations and playing with individual inputs, not only leads to the use of impossibly high growth rates but also inflates the importance of growth in the terminal value estimation. Growth is not free and it has to be paid for with reinvestment and in the terminal value equation, this effectively means that you cannot leave cash flows fixed and change the growth rate. As the growth rate increases, even within reasonable bounds, the company will have to reinvest more to deliver that growth, leading to lower cash flows, thus making the effect on value unpredictable.

Paying for Growth
To make this relationship explicit, let us start by defining the two fundamental drivers of growth, a measure of how much the company reinvests (reinvestment rate) and how well it reinvests (Return on invested capital)

In stable growth, the expected growth rate has to be a product of these two numbers

Growth rate = Reinvestment Rate (RR) * Return on Invested Capital (ROIC)

Over finite time periods, the growth rate for a company can be higher or lower than this "sustainable" growth rate, as profit margins and operating efficiency change, but once you get to the terminal value, where you are looking at forever, there is no evading its reach. Isolating the reinvestment rate in the equation and plugging back into the terminal value equation, here is what we get:

Thus, as g changes, both the numerator and denominator change. For a firm that expects to generate $100 million in after-tax operating income next year, with a cost of capital of 10%, the terminal value can be estimated as a function of the ROIC it earns on its marginal investments in perpetuity. With a growth rate of 3% and a return on capital is 12%, for instance, the terminal value is:

Changing the growth rate will have two effects: it will change the cash flow (by altering reinvestment) and change the denominator, and it is the net effect that determines whether and how much value will change.

The Excess Return Effect
Tying growth to reinvestment leads us to a simple conclusion. It is not the growth rate per se, but the excess returns (the difference between return on invested capital and the cost of capital) that drives value. In the table below, I take much of the hypothetical example from above (a company with expected operating income of $100 million next year and a cost of capital of 10%) and examine the effects of changing growth rate on value, for a range of returns on capital.

Note that as you increase the growth rate in perpetuity from 0% to 3%, the effect on the terminal value is unpredictable, decreasing when the return on invested capital < cost of capital, unchanged when the ROIC = Cost of capital and increasing when the ROIC> Cost of capital. In fact, you an just as easily construct an equity version of the terminal value and show that the growth rate in equity earnings can affect equity value only if the ROE that you assume in perpetuity is different from your cost of equity.

There are a few valuation purists who argue that the only assumption that is consistent with a mature, stable growth company is that it earns zero excess returns, since no company can have competitive advantages that last forever. If you make that assumption, you might as well dispense with estimating a stable growth rate and estimate a terminal value with a zero growth rate. While I see a basis for the argument, it runs into a reality check, i.e., that excess returns seem to last far longer than high growth rates do. Thus, your high growth period has to be extended to cover the entire excess return period, which may be twenty, thirty or forty years long, defeating the point of computing terminal value. It is for this reason that I adopt the practice of assuming that excess returns will move towards zero in stable growth and giving myself discretion on how much, with zero excess return being my choice for firms with few or no sustainable competitive advantages, a positive excess return for firms with strong and sustainable competitive advantages and even negative excess return for badly managed firms with entrenched management.

Two Dangerous Practices
If you follow the practice of tying growth to reinvestment, you will be well-armed against some of the more dangerous practices in terminal value estimation.
1. Grow the nth year's cash flow: If you consider the perpetual growth equation in its simplest form, it looks as follows:

The sheer simplicity of the equation can lull you into a false sense of complacency. After all, if you have projected the free cash flows for the your high growth period of 5 years, i.e, the cash flows after taxes and reinvestment, and you want to estimate your terminal value at the end of year 5, it seems to follow that you can grow your free cash flow in year 5 one more year at the stable growth rate to get your numerator for the terminal value calculation. The danger with doing is that you have effectively locked in whatever your reinvestment rate was in year 5 now into perpetuity and to the extent that this reinvestment rate is no longer compatible with your stable growth rate, you will misvalue your firm. For example, assume that you have a firm with $100 million in after-tax operating earnings that you expect to grow 10% a year for the next five years, with a reinvestment rate of 66.67%% and a return on investment of 15% backing up the growth; after year 5, assume that the expected growth rate will drop to 3%, with a cost of capital of 10%. In the table below, I illustrate the effect on value today of using the "just grow the year 5 free cash flow" and contrast it with the value that you would obtain if you recomputed your terminal year's cash flow, with a reinvestment rate of 80%, compatible with your stable growth rate and return on capital

Note that just growing out the FCFF yields a value today of only $605 million, about half of the (right) value that you get with a recomputed FCFF.

2. Stable Growth firms don't need to reinvest: I am not sure what the roots of this absurd practice are but they are deep. Analysts seems to be willing to assume that when you get to stable growth, you can set capital expenditures = depreciation, ignore working capital changes and effectively make the reinvestment rate zero, while allowing the firm to continue growing at a stable growth rate. That argument fails at two levels. The first is that if you reinvest nothing, your invested capital stays constant during your stable growth period, and as operating income rises, your return on invested capital will approach infinity. The second is that even if you assume a growth rate = inflation rate, you will have to replace your existing productive assets as they age and the same inflation that aids you on your revenues will cause the capital expenditures to exceed depreciation.

Conclusion
It is conventional wisdom that it is the growth rate in the perpetual growth equation that is the most significant driver of the resulting value. That may be true if you hold all else constant and change only the growth rate, but it is not, if you recognize that growth is never free and that changing the growth rate has consequences for your cash flows. Specifically, it is not the growth rate per se that determines value but how efficiently you generate that growth, and that efficiency is captured in the excess returns earned by your firm.

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Attachments

Terminal Value Diagnostic Spreadsheet

DCF Myth Posts

Introductory Post: DCF Valuations: Academic Exercise, Sales Pitch or Investor Tool

If you have a D(discount rate) and a CF (cash flow), you have a DCF.
A DCF is an exercise in modeling & number crunching.
You cannot do a DCF when there is too much uncertainty.
It's all about D in the DCF (Myths 4.1, 4.2, 4.3, 4.4 & 4.5)
The Terminal Value: Elephant in the Room! (Myths 5.1, 5.2, 5.3, 5.4 & 5.5)
A DCF requires too many assumptions and can be manipulated to yield any value you want.
A DCF cannot value brand name or other intangibles.
A DCF yields a conservative estimate of value.
If your DCF value changes significantly over time, there is something wrong with your valuation.
A DCF is an academic exercise.

As you peruse discounted cash flow valuations, it is striking how infrequently you see projections of negative growth into the future, even for companies where the trend lines in revenues and earnings have been anything but positive. Furthermore, you almost never see a terminal value calculation, where the analyst assumes a negative growth rate in perpetuity. In fact, when you bring up the possibility, the first reaction that you get is that it is impossible to estimate terminal value with a negative growth rate. In this post, I will present evidence that negative growth is neither uncommon nor unnatural and that the best course, from a value perspective, for some firms is to shrink rather than grow.

Negative Growth Rates: More common than you think!
The belief that most firms have positive growth over time is perhaps nurtured by the belief that it is unnatural for firms to have negative growth and that while companies may have a year or two of negative growth, they bounce back to positive growth sooner rather than later. To evaluate whether this belief has a basis in fact, I looked at compounded annual growth rate (CAGR) in revenues in the most recent calendar year (2015), the last five calendar years (2011-2015)and the last ten calendar years (2006-2015) for both US and global companies and computed the percent of all companies (my sample size is 46,814 companies) that have had negative growth over each of those time periods:

Region	Number of firms	% with negative revenue growth in 2015	% with negative CAGR in revenues: 2011-2015	% with negative CAGR in revenues: 2006-2015
Australia, NZ and Canada	5014	41.44%	36.73%	28.20%
Developed Europe	7082	33.42%	30.03%	24.25%
Emerging Markets	21196	43.06%	29.35%	21.50%
Japan	3698	33.41%	20.76%	31.80%
United States	9823	39.69%	26.76%	28.10%
Grand Total	46814	39.86%	28.64%	24.69%

Note that almost 40% of all companies, in both the US and globally, saw revenues decline in 2015 and that 25% of all companies (and 27% of US companies) saw revenues decline (on a CAGR basis) between 2006 and 2015. (If you are interested in a break down by country, you can download the spreadsheet by clicking here.) Digging a little deeper, while there are company-specific reasons for revenue declines, there are also clearly sector effects, with companies in some sectors more likely to see revenues shrink than others. In the table below, I list the ten non-financial sectors with the highest percentage of companies (I excluded financial service companies because revenues are difficult to define, not because of any built-in bias):

Industry Grouping	Number of firms	% Negative in 2015	% with Negative CAGR from 2011-2015	% with Negative CAGR from 20106-2015
Publshing & Newspapers	346	53.77%	48.44%	45.69%
Computers/Peripherals	327	43.30%	42.12%	45.65%
Electronics (Consumer & Office)	152	43.70%	47.11%	44.44%
Homebuilding	164	31.51%	22.69%	35.87%
Oil/Gas (Production and Exploration)	959	79.22%	43.75%	35.40%
Food Wholesalers	126	37.00%	30.59%	33.33%
Office Equipment & Services	160	40.58%	32.54%	33.33%
Real Estate (General/Diversified)	418	41.33%	32.72%	32.52%
Telecom. Equipment	473	43.00%	37.36%	32.43%
Steel	757	73.23%	50.65%	32.08%

So what? For some of these sectors (like real estate and homebuilding), the negative revenue growth may just be a reflection of long cycles playing out but for others, it may be an indication that the business is shrinking. If you are valuing a company in one of these sectors, you should be more open to the possibility that growth in the long term could be negative. (If you interested in downloading the full list, click on this link.)

Negative Growth Rates: A Corporate Life Cycle Perspective

One framework that I find useful for understanding both corporate finance and valuation issues is the corporate life cycle, where I trace a companyâs life from birth (as a start-up) to decline and connect it to expectations about revenue growth and profit margins:

If you buy into this notion of a life cycle, you can already see that valuation, at least as taught in classes/books and practiced, is not in keeping with the concept. After all, if you apply a positive growth rate in perpetuity to every firm that you value, the life cycle that is more in keeping with this view of the world is the following:

The problem with this life cycle perspective is that the global market place is not big enough to accommodate these ever-expanding behemoths. It follows, therefore, that there have to be companies (and a significant number at that) where the future holds shrinkage rather than growth. Fitting this perspective back into the corporate life cycle, you should be using a negative growth rate in revenues and perhaps declining margins to go with those shrinking revenues in your valuation, if your company is already in decline. If you are valuing a company that is mature right now (with positive but very low growth) but the overall market is stagnant or starting to decline, you should be open to the possibility that growth could become negative at the end of your forecast horizon.

There is an extension of the corporate life cycle that may also have implications for valuation. In an earlier post, I noted that tech companies age in dog years and often have compressed life cycles, growing faster, reaping benefits for shorter time periods and declining more precipitously than non-tech companies. When valuing tech companies, it may behoove us to reflect these characteristics in shorter (and more exuberant) growth periods, fewer years of stable growth and terminal growth periods with negative growth rates.

Negative Growth Rates: The Mechanics

As I noted in my last post, the growth rate in perpetuity cannot exceed the growth rate of the economy but it can be lower and that lower number can be negative. It is entirely possible that once you get to your terminal year, that your cash flows have peaked and will drop 2% a year in perpetuity thereafter. Mathematically, the perpetual growth model still holds:

If you do assume negative growth, though, you have to examine whether as the firm shrinks, it will be able to divest assets and collect cash. If the answer is no, the effect of negative growth is unambiguously negative and the terminal value will decline as growth gets more negative. If the answer is yes, the effect of negative growth in value will depend upon how much you will get from divesting assets.

To illustrate, consider the example of the firm with $100 million in expected after-tax operating income next year, that is in perpetual growth and letâs assume a perpetual growth rate of -5% a year forever. If you assume that as the firm shrinks, there will be no cash flows from selling or liquidating assets, the terminal value with a 10% cost of capital is:

Terminal value = $100/ (.10-(-.05)) = $666.67

If you assume that there are assets that are being liquidated as the firm shrinks, you have to estimate the return on capital on these assets and compute a reinvestment rate. If the assets that you are liquidating, for instance, have a 7.5% return on invested capital, the reinvestment rate will be -66.67%.

Reinvestment rate = -5%/7.5% = 66.67%

If you are puzzled by a negative reinvestment rate, it as the cash inflow that you are generating from asset sales, and your terminal value will then be:

Terminal value = $100 (1-(-0.6667))/ (.10 â (-.05)) = $1,111.33

Put simply, the same rule that governs whether the terminal value will increase if you increase the growth rate, i.e., whether the return on capital is greater than the cost of capital, works in reverse when you have negative growth. As long as you can get more for divesting assets than as continuing investments (present value of cash flows), liquidating them will increase your terminal value.

Negative Growth: Managerial Implications

Our unwillingness to consider using negative growth in valuation has turned the game over to growth advocates. Not surprisingly, there are many in academia and practice who argue that the essence of good management is to grow businesses and that the end game for companies is corporate sustainability. That's nonsense! If you are a firm in a declining business where new investments consistently generate less than the cost of capital, your attempts to sustain and grow yourself can only destroy value rather than increase it. It is with this, in mind, that I argued in an earlier post that the qualities that we look for in a CEO or top manager will be different for companies at different stages of the life cycle:

A visionary at the helm is a huge plus early in corporate life, but it is skill as a business builder that allows young companies to scale up and become successful growth companies. As growth companies get larger, the skill set shifts again towards opportunism, the capacity to find growth in new places, and then again at mature companies, where it managementâs ability to defend moats and competitive advantages that allow companies to harvest cash flows for longer periods. In decline, it is not vision that you value but pragmatism and mercantilism, one reason that I chose Larry the Liquidator as the role model. It is worth noting, though, that the way we honor and reward managers follows the growth advocate rule book, with those CEOs who grow their companies being put on a much higher pedestal (with books written by and about them and movies on their lives) than those less ambitious souls who presided over the gradual liquidation of the companies under their command.

Conclusion
I believe that the primary reason that we continue to stay with positive growth rates in valuation is behavioral. It seems unnatural and even unfair to assume that the firm that you are valuing will see shrinking revenues and declining margins, even if that is the truth. There are two things worth remembering here. The first is that your valuation should be your attempt to try to reflect reality and refusing to deal with that reality (if it is pessimistic) will bias your valuation. The second is that assuming a company will shrink may be good for that company's value, if the business it is in has deteriorated. I must confess that I don't use negative growth rates often enough in my own valuations and I should draw on them more often not only when I value companies like brick and mortar retail companies, facing daunting competition, but also when I value technology companies like GoPro, where the product life cycle is short and it is difficult to keep revitalizing your business model.

YouTube Video

Attachments

DCF Myth Posts

Introductory Post: DCF Valuations: Academic Exercise, Sales Pitch or Investor Tool

If you have a D(discount rate) and a CF (cash flow), you have a DCF.
A DCF is an exercise in modeling & number crunching.
You cannot do a DCF when there is too much uncertainty.
It's all about D in the DCF (Myths 4.1, 4.2, 4.3, 4.4 & 4.5)
The Terminal Value: Elephant in the Room! (Myths 5.1, 5.2, 5.3, 5.4 & 5.5)
A DCF requires too many assumptions and can be manipulated to yield any value you want.
A DCF cannot value brand name or other intangibles.
A DCF yields a conservative estimate of value.
If your DCF value changes significantly over time, there is something wrong with your valuation.
A DCF is an academic exercise.

When you complete a discounted cash flow valuation of a company with a growth window and a terminal value at the end, it is natural to consider how much of your value today comes from your terminal value but it is easy to interpret this number incorrectly. First, there is a perception that if the terminal value is a high proportion of your value today, the DCF is inherently unreliable, perhaps a reflection of old value investing roots. Second, following up on the realization that a high percentage of your current value comes from your terminal value, you may start believing that the assumptions that you make about high growth therefore don't matter as much as the assumptions you make in your terminal valuation. Neither presumption is correct but they are deeply held!

If the terminal value is a high percent of value, your DCF is flawed!
To understand why the terminal value is such a high proportion of the current value, it is perhaps best to deconstruct a discounted cash flow valuation in the form of the return that you make from investing in the equity of a business. For simplicity, letâs assume that you are discounting cash flows to equity (dividends of free cash flow to equity) to arrive at a value of equity today:

Note that if you were to invest at the current value and hold through the end of your growth period, your returns will take the form of annual cash flows (yield) for the first five years and an expected price appreciation, captured as the difference between the terminal value and the value today. So what? Consider how investors have historically made money on stocks, decomposing US stock returns from 1928 through 2015 in the graph below:

	1-Year Horizon	5-Year Horizon	10-year Horizon
1928-2015	67.09%	67.57%	70.09%
1966-2015	72.43%	73.42%	75.10%
1996-2015	81.51%	84.11%	85.28%

Note that no matter what time period you use in your assessment, the bulk of your return has taken the form of price appreciation and not dividends. Consequently, you should not be surprised to see the bulk of your value in a DCF come from your terminal value. In fact, it is when it does not account for the bulk of the value that you should be wary of a DCF!

Determinants of Terminal Value Proportion
While the terminal value will be a high proportion of the current value for all companies, the proportion of value that is explained by the terminal value will vary across companies. When you buy a mature company, you will get larger and more positive cash flows up front, and not surprisingly, if you put a 5-year or a 10-year growth window, you will get a smaller percentage of your value today from the terminal value than for a growth company, which is likely to have low (or even negative0 cash flows in the early years (because of reinvestment needs) before you can collect your terminal value. This can be seen numerically in the table below, where I estimate the percentage of current equity value that is explained by the terminal equity value for a firm with a high growth period of 5 years, varying the expected growth over the next 5 years and the efficiency with which that growth is delivered (through the return on equity):

Excess Growth Rate (next 5 years)	ROE = COE -2%	ROE = COE	ROE = COE +2%
0%	75.14%	75.14%	75.14%
2%	86.30%	82.53%	80.86%
4%	100.00%	90.76%	86.75%
6%	117.24%	100.00%	93.15%
8%	139.59%	110.44%	100.00%
10%	169.71%	122.33%	107.35%

In fact, if the reinvestment needs are large enough or the company is not quite ready to make profits, you can get more than 100% of your value today from the terminal value. While that sounds patently absurd, it reflects the reality that when your cash flows are negative in the early years (as a result of high growth and reinvestment), your equity holding may get diluted in those years as the company raises new equity (by issuing shares). Note that to the extent that the cash flows come in as anticipated, with high growth and low/negative cash flows, you will not have to wait until the terminal year to cash out, since the price adjustment will lead the cash flows turning positive. (You can download the spreadsheet and try your own numbers)

If your terminal value accounts for most of your value, your growth assumptions donât matter
If you accept the premise that the terminal value, in any well-done DCF, will account for a big proportion of the current value of the firm and that proportion will get higher, as growth increases, it seems logical to conclude that you should spend most of your time in a DCF finessing your assumptions about terminal value and very little on the assumptions that you make during the high growth period. Not only is this a dangerous leap of logic, but it is also not true. To see why, let me take the simple example of a firm with after-tax operating income of $100 million in the most recent year, a five-year high growth period , after which earnings will grow at 2% a year forever, with a 8% cost of equity. Holding the terminal growth rate fixed, I varied the growth rate in the high growth period and the return on equity. The resulting terminal values are reported in the table below:

Excess Growth Rate (next 5 years)	ROE = COE -2%	ROE = COE	ROE = COE +2%
0%	$1,227.00	$1,380.00	$1,472.00
2%	$1,326.00	$1,491.00	$1,591.00
4%	$1,431.00	$1,610.00	$1,717.00
6%	$1,542.00	$1,734.00	$1,850.00
8%	$1,659.00	$1,864.00	$1,991.00
10%	$1,783.00	$2,006.00	$2,140.00

Note that assuming a much higher growth rate and return on equity in the first five years has a large impact on my terminal value, even though the terminal growth rate remains unchanged. This effect will get larger for high growth firms and for longer growth periods. The conclusion that I would draw is ironic: as the terminal value accounts for a larger and larger percent of my current value, I should be paying more attention to the assumptions I make about my high growth period, not less!

Conclusion
If you are valuing equity in a going concern with a long life, you should not be surprised to see the terminal value in your DCF account for a high percentage of value. Contrary to what some may tell you, this is not a flaw in your valuation but a reflection of how investors make money from equity investments, i.e., predominantly from capital gains or price appreciation. You should also be aware of the fact that even though the terminal value will be a high proportion of current value, you should still pay attention to your assumptions about cash flows and growth during your high growth period, since your terminal value will be determined largely by these assumptions.

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Attachments

DCF Myth Posts

Introductory Post: DCF Valuations: Academic Exercise, Sales Pitch or Investor Tool

If you have a D(discount rate) and a CF (cash flow), you have a DCF.
A DCF is an exercise in modeling & number crunching.
You cannot do a DCF when there is too much uncertainty.
It's all about D in the DCF (Myths 4.1, 4.2, 4.3, 4.4 & 4.5)
The Terminal Value: Elephant in the Room! (Myths 5.1, 5.2, 5.3, 5.4 & 5.5)
A DCF requires too many assumptions and can be manipulated to yield any value you want.
A DCF cannot value brand name or other intangibles.
A DCF yields a conservative estimate of value.
If your DCF value changes significantly over time, there is something wrong with your valuation.
A DCF is an academic exercise.

I was a doctoral student at UCLA, in 1983 and 1984, when I was assigned to be research assistant to Professor Eugene Fama, who wisely abandoned the University of Chicago during the cold winters for the beaches and tennis courts of Southern California. Professor Fama won the Nobel Prize for Economics in 2013, primarily for laying the foundations for efficient markets in this paper and refining them in his work in the decades after. The debate between passive and active investing that he and others at the University of Chicago initiated has been part of the landscape for more than four decades, with passionate advocates on both sides, but even the most ardent promoters of active investing have to admit that passive investing is winning the battle. In fact, the mutual fund industry seems to have realized that they face an existential threat not just to their growth but to their very existence and many of them are responding by cutting fees and offering passive investment choices.

Passive Investing is winning!
When Jack Bogle started the Vanguard 500 Index fund in 1975, I am sure that even he could not have foreseen how successful it would become in changing the way we invest. Not only have index funds become an increasing part of the landscape, but exchange traded funds have also added to the passive investing mix and index-based investing has expanded well beyond the S&P 500 to cover almost every traded asset market in the world. Today, you can put together a portfolio composed of index funds and ETFs to create any market exposure that you want in stocks, bonds or commodities. The growth of passive investing can be seen in the graph below, where I plot the proportion of the US equity market held by passive investors (in the form of ETFs and index funds) and active investors from 2005 to 2016:

Source: Morningstar

In 2016, passive investing accounted for approximately 40% of all institutional money in the equity market, more than doubling its share since 2005. Since 2008, the flight away from active investing has accelerated and the fund flows to active and passive investing during the last decade tell the story.

The question is no longer whether passive investing is growing but how quickly and at what expense to active investing. The answer will have profound consequences not only for our investment choices going forward, but also for the many employed, from portfolio managers to sales people to financial advisors, in the active investing business.

Aided and Abetted by Active Investing
To understand the shift to passive investing and why it has accelerated in recent years, we have to look no further than the investment reports that millions of investors get each year from their brokerage houses or financial advisors, chronicling the damage done to their portfolios during the course of the year by frenetic activity. Put bluntly, investors are more aware than ever before that they are often paying active money managers to lose money for them and that they now have the option to do something about this disservice.

1. Collectively, active investing cannot beat passive investing (ever)!
Before you attack me for being a dyed-in-the-wool efficient marketer, there is a simple mathematical reason why this statement has to be true. During 2015, for instance, about 40% of institutional money in equities was invested in index funds and ETFs and about 60% in active investing of all types. The money invested in index funds and ETFs will track the index, with a very small percentage (about 0.11%) going to cover the minimal transactions costs. Thus, active money managers have to start off with the recognition that they collectively cannot beat the index and that their costs (transactions and management fees) will have to come out of the index returns. Not surprisingly, therefore, active investors will collectively generate less than the index during every period and more than half of them will usually underperform the index. To back up the first statement, here are the median returns for all actively managed funds, relative to passive index funds for various time periods ending in 2015:

Source: S&P (SPIVA)

The median active equity fund manager underperformed the index by about 1.21% a year between 2006 and 2015 and by far larger amounts over one-year (-2.92%), three year (-2.78%) and five year (-2.90%). Thus, it should come as no surprise that well over half of all active fund managers have been outperformed by the index over different time periods:

Note that in this graph, active fund managers in equity, bond and real estate all under perform their passive counterparts, suggesting that poor performance is not restricted just to equity markets.

If active money managers cannot beat the market, by construct, how do you explain the few studies that claims to find that they do? There are three possibilities. The first is that they look at subsets of active investors (perhaps hedge funds or professional money managers) rather than all active investors and find that these subsets win, at the expense of other subsets of active investors. The second is that they compare the returns generated by mutual funds to the return on a stock index during the period, a comparison that will yield the not-surprising result that active money managers, who tend to hold some of their portfolios in cash, earn higher returns than the index in down markets, entirely because of their cash holdings. You can perhaps use this as evidence that mutual fund managers are good at market timing, but only if they can generate excess returns over long periods. The third is that these studies are comparing returns earned by active investors to a market index that might not reflect the investment choices made by the investors. Thus, comparing small cap active investors to the S&P 500 or global investors to the MSCI may reveal more about the limitations of the index than it does about active investing.

2. No sub-group of active investors seems to be able to beat the market
The standard defense that most active investors would offer to the critique that they collectively underperform the market is that the collective includes a lot of sub-standard active investors. I have spent a lifetime talking to active investors who contend that the group (hedge funds, value investors, Buffett followers) that they belong to is not part of the collective and that it is the other, less enlightened groups that are responsible for the sorry state of active investing. In fact, they are quick to point to evidence often unearthed by academics looking at past data that stocks with specific characteristics (low PE, low Price to book, high dividend yield or price/earnings momentum) have beaten the market (by generating returns higher than what you would expect on a risk-adjusted basis). Even if you conclude that these findings are right, and they are debatable, you cannot use them to defend active investing, since you can create passive investing vehicles (index funds of just low PE stocks or PBV stocks) that will deliver those excess returns at minimal costs. The question then becomes whether active investing with any investment style beats a passive counterpart with the same style. SPIVA, S&Pâs excellent data service for chronicling the successes and failures of active investing, looks at the excess returns and the percent of active investors who beat the index, broken down by style sub-group.

Source: S&P (SPIVA)

Note that not only is there not a single sub-group that has been able to beat the index for that group but also that the magnitude of under performance is staggering. It is true that these are the results for US equity fund managers, but just in case you are holding out hope that active money management is better at delivering results in other markets, the following table that looks at the percent of active managers who beat indices in their markets should cast doubt on that claim:

Source: S&P (SPIVA)

There are glimmers of hope in the one-year returns in Europe and Japan and in the emerging markets, but there is not a single geography where active money managers have beaten the index over the last five years.

3. Consistent winners are rare
The third and final line of defense for active investors is that while they collectively underperform and that underperformance stretches across sub-groups, there is a subset of consistent winners who have found the magic ingredient for investment success. That last hope is dashed, though, when you look at the numbers. If there is consistent performance, you should see continuity in performance, with highly ranked funds staying highly ranked and poor performers staying poor. To see if that is the case, I looked at how portfolio managers ranked by quartile in one period did in the following three years:

Note that the numbers in the table, when you look at all US equity funds, suggest very little continuity in the process. In fact, the only number that is different from 25% (albeit only marginally significant on a statistical basis) is that transition from the first to the fourth quartile, with a higher incidence of movement across these two quartiles than any other two. That should not be surprising since managers who adopt the riskiest strategies will spend their time bouncing between the top and the bottom quartiles.

As your final defense of active investing, you may roll out a few legendary names, with Warren Buffett, Peter Lynch and the latest superstar manager in the news leading the list, but recognize that this is more an admission of the weakness of your argument than of its strength. In fact, successful though these investors have been, it becomes impossible to separate how much of their success has come from their investment philosophies, the periods of time when they operated and perhaps even luck. Again, drawing on the data, here is what Morningstar reports on the returns generated by their top mutual fund performer each year in the subsequent two years:

While the numbers in 2000 and 2001 look good, the years since have not been kind to super performers who return to earth quickly in the subsequent years. We could try to explain the failure of active investing to deliver consistent returns over time with lots of reasons, starting with the investment world getting flatter, as more investors have access to data and models but I will leave that for another post. Suffice to say, no matter what the reasons, active investing, as structured today, is an awful business, with little to show for all the resources that are poured into it. In fact, given how much value is destroyed in this business, the surprise is not that passive investing has encroached on its territory but that active investing stays standing as a viable business.

The What next?
Since it is no longer debatable that passive investing is winning the battle for investor money, and for good reasons, the question then becomes what the consequences will be. The immediate effects are predictable and painful for active money managers.

The active investing business will shrink: The fees charged for active money management will continue to decline, as they try to hold on to their remaining customers, generally older and more set in their ways. Notwithstanding these fee cuts, active money managers will continue to lose market share to ETFs and index funds as it becomes easier and easier to trade these options. The business will collectively be less profitable and hire fewer people as analysts, portfolio managers and support staff. If the last few decades are any indication, there will be periods where active money management will look like it is mounting a comeback but those will be intermittent.
More disruption is coming: In a post on disruption, I noted that the businesses that are most ripe for disruption are ones where the business is big (in terms of dollars spent), the value added is small relative to the costs of running the business and where everyone involved (businesses and customers) is unhappy with the status quo. That description fits the active money management like a glove and it should come as no surprise that the next wave of disruption is coming from fintech companies that see opportunity in almost every facet of active money management, from financial advisory services to trading to portfolio management.

While active investing has contributed to its own downfall, there is a dark side to the growth of passive investing and many in the active money management community have been quick to point to some of these.

Corporate Governance: As ETFs and index funds increasing dominate the investment landscape, the question of who will bear the burden of corporate governance at companies has risen to the surface. After all, passive investors have no incentive to challenge incumbent management at individual companies nor the capacity to do so, given their vast number of holdings. As evidence, the critics of passive investors point to the fact that Vanguard and Blackrock vote with management more than 90% of the time. I would be more sympathetic to this argument if the big active mutual fund families had been shareholder advocates in the first place, but their track record of voting with management has historically been just as bad as that of the passive investors.
Information Efficiency: To the extent that active investors collect and process information, trying to find market mistakes, they play a role in keeping prices informative. This is the point that was being made, perhaps not artfully, by the Bernstein piece on how passive investing is worse than Marxism and will lead us to serfdom. I wish that they had fully digested the Grossman and Stiglitz paper that they quote, because the paper plays out this process to its logical limit. In summary, it concludes that if everyone believes that markets are efficient and invests accordingly (in index funds), markets would cease to be efficient because no one would be collecting information. Depressing, right? But Grossman and Stiglitz also used the key word (Impossibility) in the title, since as they noted, the process is self-correcting. If passive investing does grow to the point where prices are not informationally efficient, the payoff to active investing will rise to attract more of it. Rather than the Bataan death march to an arid information-free market monopolized by passive investing, what I see is a market where active investing will ebb and flow over time.
Product Markets: There are some who argue that the growth of passive investing is reducing product market competition, increasing prices for customers, and they give two reasons. The first is that passive investors steer their money to the largest market cap companies and as a consequence, these companies can only get bigger. The second is that when two or more large companies in a sector are owned mostly by the same passive investors (say Blackrock and Vanguard), it is suggested that they are more likely to collude to maximize the collective profits to the owners. As evidence, they point to studies of the banking and airline businesses, which seem to find a correlation between passive investing and higher prices for consumers. I am not persuaded or even convinced about either of these effects, since having a lot of passive investors does not seem to provide protection against the rapid meltdown of value that you still sometimes observe at large market cap companies and most management teams that I interact with are blissfully unaware of which institutional investors hold their shares.

The rise of passive investing is an existential threat to active investing but it is also an opportunity for the profession to look inward and think about the practices that have brought it into crisis. I think that a long over-due shakeup is coming to the active investing business but that there will be a subset of active investors who will come out of this shakeup as winners. As to what will make them winners, I have to hold off until another post.

Making it personal
Should you be an active investor or are you better off putting your money in index funds? The answer will depend on not only what you bring to the investment table in the resources but also on your personal make-up. I have long argued that there is no one investment philosophy that works for all investors but there is one that is just right for you, as an investor. In keeping with this philosophy of personalized investing, I think it behooves each of us, no matter how limited our investment experience, to try to address this question. To start this process, I will make the case for why I am an active investor, though I donât think any you will or should care. I will begin by listing all the reasons that I will not give for investing actively. Since I use public information in financial statements and databases, my information is no better than anyone elseâs. While my ego would like to push me towards believing that I can value companies better than others, that is a delusion that I gave up on a long time ago and it is one reason that I have always shared my valuation models with anyone who wants to use them. There is no secret ingredient or special sauce in them and anyone with a minimal modeling capacity, basic valuation knowledge and common sense can build similar models.

So, why do I invest actively? First, I am lucky enough to be investing my own money, giving me a client who I understand and know. It is one of the strongest advantages that I have over a portfolio manager who manages other peopleâs money. Second, I have often described investing as an act of faith, faith in my capacity to value companies and faith that market prices will adjust to that value. I would like to believe that I have that faith, though it is constantly tested by adverse market movements. That said, I am not righteous, expecting to be rewarded for doing my homework or trusting in value. In fact, I have made peace with the possibility that at the end of my investing life, I could look back at the returns that I have made over my active investing lifetime and conclude that I could have done as well or better, investing in index funds. If that happens, I will not view the time that I spend analyzing and picking stocks as wasted since I have gained so much joy from the process. In short, if you donât like markets and donât enjoy the process of investing, my advice is that you put your money in index funds and spend your time on things that you truly enjoy doing!

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In my last post, I pointed to the shift towards passive investing that has accelerated over the last decade and argued that much of that shift can be explained by the sub-par performance of active investors. I ended the post on a contradictory note by explaining why I remained an active investor, though the reasons I gave were more personal than professional. I was taken to task on two fronts. The first was that I should have spent less time describing the problem (poor performance of active investors) and more time diagnosing the problem (the reasons for that poor performance). The second was that my rationale for being an active investor, i.e., that I enjoyed investing enough that I would be okay not earning excess returns, could never be used if I sought to manage other people's money and that a defense of active investing would have to be based on something more substantial. Both are fair critiques and I hope to address them in this post.

The Roots of the Active Investing Malaise

There is no denying the facts. Active investing has a problem not only because it collectively under performs passive investing (which is a mathematical given) but also because the drag on returns (from transactions costs costs and management fees) seems to be getting worse over time. Even those few strands of active investing that historically have outperformed the market have come under siege in the last decade. While there are many reasons that you can point to for this phenomenon, here are some that I would highlight:

A "Flatter" Investment Word: The investment world is getting flatter, as the differences across active investors rapidly dissipate. From information to processing models to trading platforms, professionals at the active investing game (including mutual funds and hedge funds) and individual investors are on a much more even playing field than ever before. As an individual investor, I have access to much of the information that an analyst working at Merrill Lynch or Fidelity has, whether it be financial statements or market rumors. I am not naive enough to believe that, SEC rules against selective information disclosure notwithstanding, there are no channels for analysts to get "inside" information but much of that information is either too biased or too noisy to be useful. I have almost as much processing power on my personal computer as these analysts do on theirs and can perhaps even put it to better use. In fact, the only area where institutions (or at least some of them) may have an advantage over me is in being able to access information on trading data in real time and investing instantaneously and in large quantities on that information, leading to breast beating about the unfairness of it all. If history is any guide, the returns to these strategies fade quickly, as other large players with just as much trading power are drawn into the game. In fact, while much ink was spilt on flash trading and how it has put those who cannot partake at a disadvantage, it is worth noting that the returns to flash trading, while lucrative at first, have faded, while attracting smaller players into the game. In summary, if the edge that institutional active investors have had over individual active investors was rooted in information and processing power, it has almost disappeared in the United States and has eroded in much of the rest of the world.
No Core Philosophy: There is an old saying that if you don't stand for something, you will fall for anything, and it applies to much of active investing. Successful investing starts with an investment philosophy, a set of core beliefs about market behavior that give birth to investment strategies. Too many active investors, when asked to characterize their investment philosophies, will describe themselves as "value investors" (the most mushy of all investment descriptions, since it can mean almost anything you want it to mean), "just like Warren Buffett" (a give away of lack of authenticity) or "investors in low PE stocks" (confusing an investment strategy with a philosophy). The absence of a core philosophy has two predictable consequences: (a) a lack of consistency, where active investors veer from one strategy to another, often drawn to whatever strategy worked best during the last time period and (b) me-tooism, as they chase momentum stocks to keep up with the rest. The evidence for both can be seen in the graph below, which looks at the percentages of funds in each style group who remain in that group three and five years later and finds that about half of all US funds change styles within the next five years.
Source: SPIVA
Bloated Cost Structures: If there is a core lesson that comes from looking at the performance of active investors, it is that the larger the drag on returns from the costs of being active, the more difficult it is to beat passive counterparts. One component of these costs is trading costs, and the absence of a core investment philosophy, referenced above, leads to more trading/turnover, as fund managers undo entire portfolios and redo them to match their latest active investing avatars. Another is the overhead cost of maintaining an active investing infrastructure that was built for a different market in a different era. The third cost is that of active management fees, set at levels that are not justified by either the services provided or by the returns delivered by that management team. Active money managers are feeling the pressure to cut costs, as can be seen in expense ratios declining over time, and the fund flows away from active money managers has been greatest at highest cost funds. I can only speak for myself but there is not one active investor (nope, not even him, and not even if he was forty years younger) in the world that I have enough reverence for that I would pay 2% (or even .5%) of my portfolio and 20% (or 5%) of my excess returns every year, no matter what his or her track record may be. To those who would counter that this is the price you have to pay for smart money, my response is that the smart money does not stay smart for very long, as evidenced by how quickly hedge fund returns have come back to earth.
Career Protection: Active money managers are human and it should come as no surprise that they act in ways that increase their compensation and reduce their chances of losing their jobs. First, to the extent that their income is a function of assets under management (AUM), it is very difficult, if not impossible, to fight the urge to scale up a strategy to accommodate new inflows, even if it is not scaleable. Second, if you are a money manager running an established fund, it is far less risky (from a career perspective) to adopt a strategy of sustained, low-level mediocrity than one that tries to beat the market by substantial amounts, with the always present chance that you could end up failing badly. In institutional investing, this has led some of the largest funds to quasi-index, where their holdings deviate only mildly from the index, with predictable results: these funds deliver returns that match the index, prior to transactions costs, and systematically under perform true index funds, after transactions costs, but not by enough for managers to be fired. Third, at the other end of the spectrum, if you are a small, active money manager trying to make a name for yourself, you will naturally be drawn to high-risk, high-payoff strategies, even if they are bad bets on an expected value basis. In effect, you are treating investing as a lottery, where if you win, more money will flow into your funds and if you do not, it is other people's money anyway.

There are macroeconomic factors that may also explain why active investing has had more trouble in the last decade, but it is not low interest rates or central banks that are the culprits. It is that the global economy is going through a structural shift, where the old order (with a clear line of demarcation between developed & emerging markets) is being replaced with a new one (with new power centers and shifting risks), upending historical relationships and patterns. Given how much of active money management is built on mean reversion and lessons learned by poring over US market data from the last century, it should come as no surprise that the payoff to screening stocks (for low PE ratios or high dividend yield) or following rigid investing rules (whether they be centered on CAPE or interest rates) has declined. In all of this discussion, I have focused on the faults of active institutional investors, be they hedge funds or mutual funds, but I believe that their clients bear just as much responsibility for the state of affairs. They (clients) let greed override good sense (knowing that those past returns are too good to be true, but not asking questions), claim to be long term (while demanding to see positive performance every three months), complain about quasi indexing (while using tracking error to make sure that deviations from the index get punished) and refuse to take responsibility for their own financial affairs (blaming their financial advisors for all that goes bad). In effect, clients get the active money managers they deserve.

A Pathway to Active Investing Success

If you accept even some of my explanation of why active investing is failing, at least collectively, there is a kernel of good news in that description. Specifically, the pathway to being a successful active investor lies in exploiting the weakness of the active investment community, especially large institutional investors. Here are my ingredients for active investing success, though I will add the necessary caveat that having all these ingredients will not guarantee an investment payoff.

Have a core investment philosophy: In my book on investment philosophies, I argued that there is no best investment philosophy that fits all investors. The best investment philosophy for you is the one that best fits you as an investor, in sync not only with your views about markets but with your personal makeup (in terms of patience, liquidity needs and skill sets). Thus, if you have a long time horizon, believe that value is grounded in fundamentals and that markets under estimate the value of assets in place, old-time value investing may very well be your best choice. In contrast, if your time horizon is short, believe that momentum, not value, drives stock prices, your investment philosophy may be built around technical analysis, centered on gauging price momentum and shifts in it.
Balance faith with feedback: In a post on Valeant, I argued that investing requires balancing faith with feedback, faith in your core market beliefs with enough of an acceptance that you can be wrong on the details, to allow for feedback that can modify your investing decisions. In practice, walking this tightrope is exceedingly difficult to do, as many inveAt one extreme, you have investors whose faith is so absolute that there is no room for feedback and positions once taken can never be reversed. At the other extreme, you have investors who have no faith and whose decisions change constantly, as they observe market prices.
Find your investing edge: It has always been my contention that you have to bring something uncommon to the investment table to be able to take something away. Drawing on the language of competitive advantages and moats, what sets you apart does not have to be unique but it does have to be scarce and not easily replicable. That is why I am unmoved by talk of big data in investing and the coming onslaught of successful quant strategies, unless that big data comes with exclusivity (you and only you can exploit it). Here are four potential edges (and I am sure that there others that I might be missing): (a) In sync with client(s): I was not being facetious when I argued that one of my big advantages as an investor is that I invest my own money and hence have a freedom that most active institutional investors cannot have. If you are managing other peoples money, this suggests that your most consequential decision will be the screening your clients, turning money away from those who are not suited to your investment philosophy (b) Sell Liquidity: To be able to sell liquidity to investors seeking it, especially in the midst of a crisis, is perhaps one of investing's few remaining solid bets. That is possible, though, only if you, as an investor, value liquidity less than the rest of the market, a function of both your financial security. (c) Tax Play: Investor price assets to generate after-tax returns and that effectively implies that assets that generate high-tax income (dividends, for instance) will be priced lower than assets that generate low-tax or no-tax income. If you are an investor with a different tax profile, paying either no or low taxes, you will be able to capture some of the return differential. Before you dismiss this as impossible or illegal, recognize that there is a portion of each of our portfolios, perhaps in IRAs or pension funds, where we are taxed differently and may be able to use it to our advantage. (d) Big Picture Perspective: As we become a world of specialists, each engrossed in his or her corner of the investment universe, there is an opening for "big picture" investors, those who can see the forest for the trees and retain perspective by looking across markets and across time.

If you are considering actively investing your money, you should be clear about what your own investment philosophy is, and why you hold on to it, and identify the scarce resource that you are bringing to the investment table. If you are considering paying someone else to actively manage your money, my suggestion is that while you should consider that person's track record, it is even more critical that you examine whether that track record is grounded in a consistent investment philosophy and backed up by a sustainable edge.

Conclusion

There is much that I still do not know about investing but here are the lessons that I learn, unlearn and relearn every day. First, an investment cannot be a sure-bet and risky at the same time, and you can count me among the skeptical when presented with the next easy way of beating the market. Second, when I believe that I own the high ground in any investment debate, it is a sure sign that I have let hubris get the better of me and that my arguments are far weaker than I think they are. Third, much as I hate to be wrong on my investment choices, I learn more when I concede that "I am wrong" than when I contend that "I am right". For now, I will continue to invest actively, holding true to my investment philosophy centered on intrinsic value, while nurturing the small edges that I have over institutional investors.

Each year, for the last 25 years, I have spent the first week playing Moneyball, with financial data. I gather accounting and market data on all publicly traded companies, listed globally, and then try to extract whatever lessons that I can from the data, to use in investing, corporate finance and valuation for the rest of the year. I report the data, classified by industry group and by country, on my website, in the hope that others might find it useful. While, like last year, I will be summarizing what I see in the data in a series of posts over the rest of January, I decided to use this one to both provide some perspective and cautionary notes not only on my data but on numbers, in general.

The Number Cruncher's Delusions
In an earlier post on narrative and numbers, I confessed that I am more naturally a number cruncher than a story teller and that I have learned through experience that focusing entirely on the numbers can lead you astray in valuation and investing. In fact, as you read my posts on what the numbers look like at the start of 2017, it is also worth noting that I am, like all number crunchers, susceptible to three delusions about data:

Numbers are precise: I say, only half jokingly, that when a number cruncher is in doubt, his or her reaction is to add more decimals, in the hope that making a number look more precise will make it so. The truth is that numbers are only as precise as the process that delivers them and in business, that makes them imprecise. Thus, when you peruse the returns on capital or costs of capital that I will be estimating and reporting for both companies and industry groups, please do recognize that the former is an accounting number, where discretionary choices on expensing and depreciation can translate into big changes in returns on capital, and the latter is market number, making it not only a moving target (as interest rates and risk premiums change) but also a function of my estimation choices as well as estimation error in estimating risk premiums and risk parameters.
Numbers are objective: One of the resentments that number crunchers have about story tellers is that the latter indulge in flights of fancy and are unashamed about bringing their biases into their stories and through them into pricing and investing. The problem, though, is that numbers can be just as biased as stories, with the caveat that it is easier to hide biases with numbers. To give one example, one of the datasets that I will be updating has tax rates paid by US companies in 2016 and I provide three measures of effective tax rates, ranging from a simple average of effective tax rates across all companies in a sector, yielding the lowest values, to a weighted average effective tax rate that is computed only across money-making firms, which yields much higher values. If you are dead-set on making a case that US companies don't pay their fair share in taxes, you will report only the first number and not mention the rest, whereas if you want to show that US companies pay their fair share and more in taxes, you will go with the latter. It is for this reason that I will not claim to be unbiased (since no one is) but I will try to provide multiple measures of widely used variables and leave it to you to decide which one best fits your preconceptions.
Numbers put you in control: It is human nature to try to be in control and numbers serve us well, in that pursuit. As in other aspects of life, we seem to think that attaching a number to a volatile or uncontrollable variable brings it under control. So, at the risk of stating the obvious, let me say that measuring your return on invested capital is not going to turn bad projects into good ones, just as estimating your interest coverage ratio is not going to make it easier for you to make your interest payments.

Don't get me wrong! I remain, at heart, a number cruncher but I have a more complicated, and healthier, relationship with data than I used to have. My faith in data has been tempered by my experiences with data, and especially so with the ease with which I have seen it bent to reflect the agenda of the user. I trust numbers, but only after I verify them, and I hope that you will do the same with the data that you find on my site.

A Big Data Skeptic

It is my experience with data that make me skeptical about two of the hottest concepts in business, big data and data analytics, at least as a basis for making money. It is true that companies are collecting more data than ever before on almost every aspect of our lives, with the intent of using that data to make more money of us. In a capitalist society, I remain doubtful that big data will be monetized, for three reasons.

Data is not information: Not all data is created equal. Data that is based on what you do is worth a lot more than what you say will do; a tweet that you are bullish on Apple, Twitter or the entire market is less useful data than a record of you buying Apple, Twitter or the entire market. This is a point worth remembering as the rush is on to incorporate social media data (from Twitter and Facebook) with financial data to create super data bases. In addition, as we collect and store more data, it is worth noting that data is not information. In fact, if data analytics does its job, converting data to information will remain its focus, rather than generating neat look graphs and obscure statistics.
If everyone has it (data), no one has it: For data to have value, you have to some degree of exclusivity in access to that data a proprietary edge on processing that data. It is one of the reasons that investors have been unable, for the most part, to convert increased access to financial data into investing profits.
Not all data is actionable: , To convert that data to profits, you need to be able to find a way to monetize whatever data edge you have acquired. For companies that offer products and services, this will take the form of modifying existing products/services or coming up with new products/services to what you have learned from the data.

As you look at these three factors, it is easy to see why Netflix and Amazon have become illustrative examples for the benefits of big data. They get to observe us (as consumers) in action, Amazon watching what we buy and Netflix observing what we watch on our devices, and that information is not only proprietary but can be used to not only modify product offerings but to also nudge us to act in ways that will be beneficial to the companies. By the same token, you can also see why using big data as an investing advantage will, at best, provide a transitory advantage, and why I feel no qualms about sharing my data.

Data Details

If you choose to use any of my data, it behooves me to take you through the process by which I collect and analyze the data and offer some cautionary notes along the way.

Raw Data: The first step in the process is collecting the raw data and I am deeply thankful to the data services that allow me to do this. I use S&P Capital IQ, Bloomberg and a host of specialized services (Moody's, PRS etc.). For company-specific data, the only criteria that I use for including a company is that it has to have a non-zero market capitalization, yielding a total of 42678 firms on January 1, 2017. The data collected is as of January 1, 2017, with market data (stock prices, market capitalization and interest rates) being as of that data but accounting data reflects the most recent twelve months (which would be through September 30, 2016 for calendar year companies).
Classification: I classify these companies first by geographic group into five groups - the United States, Japan, Developed Europe (including the EU and Switzerland), Emerging Markets (including Eastern Europe, Asia, Africa and Latin America) and Australia/New Zealand/Canada, a somewhat arbitrary grouping that I am stuck with because of history.
I also classify firms into 96 industry groups, built loosely on raw service industrial grouping and SIC codes. The number of firms in each industry group, broken down further by geographic grouping, can be found at this link and you can find the companies in each industry grouping at this link.
Key numbers: I generally don't report much macroeconomic data (interest rates, inflation, GDP growth etc.), since there are much better sources for the data, with my favorite remaining FRED (the Federal Reserve data site in St. Louis). I update equity risk premiums not only for the US but for much of the world at the start of every year and will update them again in July 2016. Using the company data, I report on dozens of metrics at the industry group and geographic levels on profitability, cost of capital, relative risk and valuation ratios and you can find the entire listing here.
Computational details: One of the lessons that I have learned from wrestling with the data is that computing even simple statistics requires making choices, which, in turn, can be affected by your biases. Just to provide an example, to compute the PE ratio for US steel companies, I can take a simple average of the PE ratios of companies but that will not only weight tiny companies and very large companies equally but will also eliminate any companies that have negative earnings from my sample (causing bias in my estimates). To eliminate this problem, for most of the industry average statistics, I aggregate values across companies and then compute ratios. With the PE ratio for US steel companies, for instance, I aggregate the net income of all steel companies (including money-losing companies) and the market capitalizations for the same companies and then divide the former by the latter to get the PE ratio. Think of these averages then as weighted averages of all companies in each industry group, perhaps explaining why my numbers may be different from those reported by other services.
Reporting: I have wrestled with how best to report this data, so that you can find what you are looking for easily. I have not found the perfect template, but here is how you will find the data. For the current data (from January 2017), go to this link. You will see the data classified into risk, profitability, capital structure and dividend policy measures, reflecting my corporate finance focus, and then into pricing groups (earnings multiples, book value multiples and revenue multiples). I also keep archived data from prior years (going back to 1999) at this link. Unfortunately, since I have had to switch raw data providers multiple times in the last 20 years, the data is not perfectly comparable over time, as both industry groupings and data measures change over time.
Usage: There are two ways you can get the data. For the US data, I have html versions that you can see on your browser. For all of the data, I have excel spreadsheets that you can download for the data. I would strongly encourage you to use the latter rather than the former, since you can then manipulate and work with the data. If you have questions about any of the variables and how exactly I define them, try this link, where I summarize my computational details.

In Closing

I am a one-man operation and I am sure that there are datasets that I have not updated or where you find missing pieces. If you find any of these, please let me know, and I will try to fix them. I also don't see myself as a raw data provider, especially on a real-time basis and on individual companies. So, I don't plan to update this data over the course of the year, partly because industry averages should not have dramatic changes over a few months and partly because I have other stuff that I would rather do.

YouTube Video

Data Links

Data 2017 Posts

Data Update 1: The Promise and Perils of Big Data
Data Update 2: US Stocks at the start of 2017
Data Update 3: Of Interest Rates and Currencies - January 2017
Data Update 4: Country Risk and Pricing, January 2017
Data Update 5: Death and Taxes in January 2017- Changes Coming?
Data Update 6: The Cost of Capital in January 2017
Data Update 7: Profitability, Excess Returns and Corporate Governance- January 2017
Data Update 8: The Debt Trade off in January 2017
Data Update 9: Dividends and Buybacks in 2017
Data Update 10: A Pricing Update in January 2017

When I taught my first valuation class in 1986 at New York University, I taught it with numbers, with barely a mention of stories. It was only with the passage of time that I realized that my valuations were becoming number-crunching exercises, with little holding them together other than historical data and equations. Worse, I had no faith in my own valuations, recognizing how easily I could move my final value by changing a number here and a number there. It was then that I realized that I needed a story to connect the numbers and that I was not comfortable with story telling, and that realization led me to start working on my narrative skills. While I am still a novice at it, I think that I have become a little better at story telling than I used to be and it is this journey that is at the core of my newest book, Narrative and Numbers: The Value of Stories in Business.

Story versus Numbers

What comes more naturally to you, story telling or number crunching? That is the question that I start every valuation class that I teach and my reasons are simple. In a world where we are encouraged to make choices early and specialize, we unsurprisingly play to our strengths and ignore our weaknesses. I see a world increasingly divided between number crunchers, who have abandoned common sense and intuition in pursuit of data analytics and complex models and story tellers, whose soaring narratives are unbounded by reality. Each side is suspicious of the other, the story tellers convinced that numbers are being used to intimidate them and the number crunchers secure in their belief that they are being told fairy tales. It is a pity, since there is not only much that each can learn from the other, but you need skills in investing and valuation. I think of valuation as a bridge between stories and numbers, where every story becomes a number in the valuation and every number in a valuation has a story behind it.

When I introduce this picture in my first class, my students are skeptical, as they should be, viewing it as an abstraction, but I try to make it real, the only way I can, which is by applying it on real companies. I start every valuation that I do in class with a story and try to connect my numbers to that story and I try to be open about how much I struggle to come up with stories for some companies and have much my story has to change to reflect new facts or data with others. I push my students to work on their weaker sides when they do valuations, trying asking story tellers to pay more heed to the numbers and beseeching number crunchers to work on their stories. Seeking a larger audience, I have not only posted many times on the process but almost every valuation that I have posted on this blog has been as much about the story that I am telling about the company as it is about the numbers. In fact, having written and talked often about the topic, I thought it made sense to bring it all together in a book, Narrative and Numbers, published by Columbia University Press, and available at bookstores near you now (and on Amazon in both physical and Kindle versions).

From Story to Value: The Sequence

So, how does a story become a valuation? This book is built around a sequence that has worked for me, in five steps, starting with a story, putting the story through a reality check, converting the story into a valuation and then leaving the feedback loop open (where you listen to those who disagree with you the most and try to improve your story).

There is no rocket science in any of these steps and I am sure that this is not the only pathway to converting narrative to value. These steps have worked for me and I use four companies as my lead players to illustrate the process.

Uber, the ride-sharing phenomenon: I start with the story that I told about Uber in June 2014, and the resulting value, and how that story evolved over the next 15 months as I learned more about the company and its market/competition changed.
Amazon, the Field of Dreams Company: Amazon is a story stock that seems to defy the numbers laws and I use it to illustrate how the value for Amazon can vary as a function of the story you tell about it.
Alibaba, the China story: The China big market story has been used to justify the valuations of many companies, but Alibaba is one case where the use of that story is actually merited. In my story, Alibaba continues to dominate the growing Chinese online retail market and my value reflects that, but I also look at how that value will change if Alibaba can replicate its success globally (Alibaba, the Global Story).
Ferrari, the Exclusive Club: I value Ferrari as an exclusive club, leading into its IPO, and explore how that value will change if you assume that it will follow a different business model.

In the later chapters, I bring in other familiar names (at least to those who read my blog), Vale to illustrate how macroeconomic factors affect stories and Yahoo! to examine the effect of the corporate life cycle. In the final part of the book, I turn the focus on management and look at how the story telling skills of top managers can make a significant difference in how a young company is perceived and valued by the market and how that skill set has to shift as the company ages.

Personal, Applied and Live!

This is my tenth book and I have never had more fun writing a book. There are three aspects to this book that I hope come through:

It is a personal book: If you read the book, you will notice that rather than use the formal "we" or "you" through much of the book, I talk about "I" and "my". Before you decide that this is a sign of an ego run wild, I did this because this book is about my journey from an unquestioning trust in numbers to an increasing focus on stories in valuation and my stories about the companies that I value in this book. I don't expect you to buy into my stories. In fact, I hope that you disagree with me and tell your own stories and that this book will help you convert those stories into valuations.
It is applied: One common theme across all my books is that I believe that financial tools are best illustrated with real companies in real time. That is the reason that I not only chose real companies as my illustrative examples, but companies that many of you will have strong views (positive or negative) about.
It is live: The most exciting part of this book, for me, is that is is never going to be complete. The companies that I use in the book are dynamic entities and I am sure that the stories that I have told about them will change, shift and perhaps even break over time. Rather than dread these upcoming changes, I view them as opportunities for me to revisit my stories and valuations and to update them. You will see these updates on this blog but you will also be able to find them at the website for the book, where I also have pulled together YouTube videos and other material relevant to the book.

Closing

I am usually too embarrassed to ask people to buy my books, since many of them are obscenely over priced, one reason that I don't require them even for students in my classes. I feel no such qualms about this book, since it is (I think) priced reasonably and I hope it offers good value for the money. I hope that you will read the book and that that you enjoy it, and if you can learn something that helps you improve your valuation skills, I will view that as icing on the cake. Drawing on one of the themes in the book, where I argue that the key to keep the feedback loop open, I would also like to hear from those of you who don't like the book and what I can do better! I'll try!

YouTube Video

Book Links

If you have been reading my blog for awhile, you should be familiar with the routine at the start of every semester. If I am teaching that semester, I list the classes that I will be teaching, describe them briefly and offer ways in which you can follow the classes online, if you are so inclined. This semester is shaping up to be a busy one, with an MBA Corporate Finance class leading the list, followed by an undergraduate Valuation class and closing with a new online valuation certificate class that will be offered by the Stern School of Business.

Corporate Finance

The most important class that I teach is corporate finance, not valuation. Put simply, this class (or at least the version that I subscribe to) is about the first financial principles that govern how to run a business, small or large, private or public and in any market. That sounds like an ambitious agenda but it makes for a fascinating class, where we break down everything that a business does into three categories: investing, financing and dividend decisions. At the risk of summarizing the entire class into a single picture, these are the questions that corporate finance tries to answer:

For a business to be successful, it has to find a singular objective and then make investment, financing and dividend decisions that advance that objective. We start the class by debating what that objective should be and then move into the investment principle, first looking at how best to estimate the hurdle rates (the threshold for a good investment) in a business and then then at measuring the returns on prospective or actual investments. We follow up by discussing whether there is a right mix of debt and equity to use in funding a business as well as the right type of financing (long term or short term, floating or fixed, straight or convertible, currency) for that business. We finish with a discussion of how much cash should be returned to investors in a business in the form of dividends or buybacks, why a business may prefer one form of cash return over another and how much cash (balance) is too much cash. We end the class by bringing all of these principles together in the value of a business, setting up for my next class (Valuation).

The first session will be on January 30, 2017, and we will meet every Monday and Wednesday from 10.30-12 until May 8. While you have to be enrolled in the class as a Stern MBA to attend the class physically, you are welcome to follow the class online in one of three forums. In each of these forums, I will post recorded webcasts of the lectures late on Mondays and Wednesdays, with links lecture notes and other material. I will also post the quizzes and exams that I will be giving in class online, with grading templates that you can use to grade yourself.

My website: The primary platform for my class is on the webpage for the class on my website. A one-page listing of the webcasts and other materials can be found at this link. You can watch the streaming videos or download them and also the slides and other links for each class. You can indulge your voyeuristic instincts by reading the emails I send to the class at this link.
Apple iTunes U: If you prefer a more polished and device-friendly platform and you own an Apple device (iPhone or iPad), you should download the iTunes U app from the store and once you have it installed, try entering the code " EXC-JJS-XEA", and the class should show up on your shelf. (If it does not, try this link instead.) As I post the lectures and other material on the site, you should get a notification (if you want) about the posting. If you have an Android device, you have to download the Tunesviewer app to be able to access iTunes U classes.
YouTube: If you want a more minimalist set up, with limited demands on broadband, you can use YouTube and check out the playlist for the class. Again, as classes get posted, you should see them show on the playlist.

Valuation

This is a class that I teach almost every semester to the MBAs and this semester, I will be teaching it to undergraduates. That said, I teach exactly the same class to both and this class follows the same structure as my MBA classes. It is a class about attaching a number to an asset or business and we will look at both intrinsic valuation and pricing of both public and private firms.

Since I provided a much longer introduction when I wrote about my Fall 2016 class, you can read it full at this link. The first session for this class will be January 23, and as with the corporate finance class, you can follow the class online, in one of three ways:

My website: The primary platform for my class is on the webpage for the class on my website. A one-page listing of the webcasts and other materials can be found at this link.
Apple iTunes U: If you download the iTunes U app from the store to your Apple device, you can enter the code "FHS-KWW-FPK" for the class. If you prefer a direct link, try this one.
YouTube: You can use YouTube and check out the playlist for the class. As classes get posted, you should see them show on the playlist.

Valuation Certificate

These postings, listing upcoming classes and offering them online, have been a ritual of mine for more than 20 years and one common query I get is whether I can offer certification. My answer, hitherto, has been no, not only because I have no way of testing or grading what you do or providing feedback. This semester, the Stern School of Business has decided to offer an online version of my class as Valuation certification class, with the following features:

Lectures: The class is built around twenty eight lecture sessions, each of which is about 12-20 minutes long. These sessions were recorded in a studio and should much more professional than the online videos that I make and more watchable than my full-length classes.
Timing: The class is scheduled to begin on January 30 and go through mid-May, requiring that you watch about two sessions a week. Each session will come with self-test assessment, practice problems, additional readings and other material to supplement learnings.
Synchronous sessions: Every two weeks, I will use WebEx for a live Q&A session, where you can ask questions about the four sessions from the prior two weeks.
Discussion Boards: If you are enrolled in the class, you will be able to participate in discussion boards organized by valuation topics, posting comments, questions or other links. A teaching assistant will monitor the boards and add to the discussion, if needed.
Quizzes and Exams: Just as in my regular classes, there will quizzes and exams. You will be able to take these exams online and I will grade them.
Valuation Project: As in my regular class, each person in the certificate program will be both valuing and pricing a company and I will provide mid-semester feedback on the valuation and a final grade assessment at the end of the semester.

There is bad news and good news with this new offering. The first piece of bad news is that it is not free and you have to decide, for yourself, whether the price charged ($425) is worth the experience (and the certificate). The second is that this is Stern's first try at this type of offering; it will have a few hiccups and the number of students will be capped at fifty. If you are interested, you can find out more about the certificate program at this link and even if you are unable to participate or get into the class this semester, it will be offered again to a larger audience, later in the year. The good news, if you decide to be part of the program is that I will treat you like I treat my regular in-class students. I am not sure that even this is good news, since you will hear from me about once every day and you will be sick and tired of me by May 12.

YouTube Video: Valuation Certificate Class Preview

Links

Corporate Finance (MBA): (a) My website (b) Apple iTunes U (c) YouTube Playlist
Valuation (Undergraduate): (a) My website (b) Apple iTunes U (c) YouTube Playlist
Stern Valuation Certificate: Stern entry webpage

If asked to list the biggest threats to US equities at the start of 2016, most people would have pointed to the Federal Reserveâs imminent retreat from quantitative easing and the possibility of a slowdown in China spilling into lower global growth. Those fears contributed to a very bad start to 2016 for US stock markets, and as stocks dropped by about 5% in January, those who have warned us about a bubble looked prescient. But the stock market, as is its wont, surprised us again. Not only did US equities come back from those setbacks but it weathered other crises during the year, including the decision by UK voters to exit the EU in June and by US voters to elect Donald Trump as president in November to end the year with healthy gains. As we enter a year with potentially big changes to the US tax code and trade policy looming, it is time to take stock of where we are and where we might be going in the next year.

Stocks and Bonds: Looking Back
The best place to see how the year unfolded for stocks is to trace out how the S&P 500 (large cap stocks), the S&P 600 (for small cap stocks) and US ten-year treasury bond rate did on a month by month basis through 2016.

Monthly returns, using month-end values

To convert the index values into returns each month, I first computed price changes for the indices each month (and cumulatively over the year) and added the dividends for the year to estimate annual returns of 11.74% for the S&P 500 and 26.46% for the S&P 600; it was a very good year for small cap stocks and a good one for large cap stocks. I converted the treasury bond rates into bond price changes each month and cumulatively (for a 10-year constant maturity bond) over the year and added the coupon at the start of the year to get a return of 0.58% for the year; the rise in interest rates cause bond prices to drop by 1.68% during the year.

To put these returns in perspective, I added the S&P 500 and treasury bond return for 2016 to my historical data series which goes back to 1928 and computed both simple and compounded (geometric) annual averages in both for the entire period and compared them to a annualized 3-month treasury bill return (which you can think of as the return for holding cash).

Download spreadsheet with historical data

This table (or some variant of it) is used by practitioners to get the equity risk premium for US markets, by subtracting the average return on treasuries (bills or bonds) from the average return on stocks over a historical time period. Using my estimates, I get the following values for the historical equity risk premium for the US market.

Download spreadsheet with historical data

Note that the equity risk premium varies widely, from 2.3% to 7.96%, depending on how long a time period you use, how you compute averages (simple or compounded) and whether you use treasury bills or bonds as your measure of a risk free investment. Adding a statistical note of caution, each of these estimated premiums comes with a standard error, reported in red numbers below the estimated number. Thus, if you decide to use 6.24%, the difference between the arithmetic average returns on stocks and bonds from 1928-2016, as your historical risk premium, that number comes with a standard error of 2.26%. That would mean that your true equity risk premium, with 95% confidence, could be anywhere from 1.72% to 10.76% (plus and minus two standard errors).

Stocks: Looking forward
Looking at the past may give us comfort but investing is always about the future. I have been a long-time skeptic of historical risk premiums for two reasons. First, as noted in the table above, they are noisy (have high standard errors). Second, they assume mean reversion, i.e., that US equity markets will revert back to what they have historically delivered as returns and that is an increasingly tenuous assumption. It is for this reason that I compute a forward-looking estimate of the equity risk premium for the US, using the S&P 500 Index as my measure of US stocks. Specifically, I estimate expected cash flows from dividends and buybacks from holding the S&P 500 for the next five years, using the trailing 12-month cash flow as my starting point and an expected growth rate in earnings as my proxy for cash flow growth and use these estimates, in conjunction with the index level on January 1, 2017, to compute an internal rate of return (a discount rate that will make the present value of the expected cash flows on the index equal to the traded level of the index).

Download spreadsheet to compute implied ERP

Given the level of the index (2038.83 on January 1, 2017) and expected cash flows, I estimate an expected return on 8.14% for stocks and netting out the T.Bond rate of 2.45% on January 1, 2017, yields an implied ERP for the index of 5.69%. That number is down from the 6.12% that I estimated at the start of 2016 but is still well above the historical average (from 1960-2016) for this implied ERP of about 4.11%.

There is one troubling feature to the trailing 12 month cash flows on the S&P 500 that gives me pause. As was the case last year, the cash flows returned by S&P 500 companies represented more than 100% of earnings during the trailing 12 months, an unsustainable pace even in a mature market. I recomputed the ERP on the assumption that the cash payout ratio will decrease over time to sustainable levels, i.e., levels that would allow for enough reinvestment given the growth rate. The results are shown below:

Download spreadsheet to compute implied ERP

The implied ERP for the index, with payout adjusting to about 82.3% of earnings in year 5, is 4.50%, still higher than historic norms but with a much slimmer buffer for safety. Looking at the next year, though, the potential for tax law changes will roil estimates. Not only are many analysts expecting significant increases in earnings next year of 12-15%, as they expect corporate tax rates to get lowered (at least in the aggregate) but there may also be a return of some of the trapped cash ($2 trillion or higher) back to the US, if that portion of the law is modified. Either change will relieve the pressure on cash flows and make it less likely that you will see dramatic cuts in stock buybacks or dividends.

Interest Rates: What lies ahead?
With bonds, I will take a different tack. I believe that, rather than waiting on the Fed, the path for interest rates this year will be determined by the path of the economy, with higher real growth and/or higher inflation pushing up rates. Updating a figure that I have used before, where I compare the T.Bond rate to an intrinsic interest rate (computed by adding expected inflation to expected real growth), you do see the beginning of a gap between the two at the end of 2016:

Download spreadsheet with historical rates

Entering 2017, the ten-year treasury bond at 2.45% is well below the intrinsic risk free of 3.60%, obtained by adding the inflation rate to real GDP growth through much of 2016. It is entirely possible that the economy will revert back to its post-2008 sluggishness or that there will be other shocks to the global economic system that will cause inflation and real growth to recede and interest rates to stay low, but for the moment at least, it looks like interest rates are their journey back to a new normal. If I were advising the Fed, my suggestion is to them is to act quickly on rates (perhaps as early as the next meeting) in order to preserve the fiction that it is they are setting rates, rather than following them.

PE, CAPE and Bond PE Ratios

I am not a fan of PE crystal ball gazing but I know that there are many who make their market judgments based on PE ratios. Updating a graph that I last used when I posted on CAPE last year to reflect the numbers at the start of the 2017, here is what the updated PE ratios look like for the S&P 500:

Spreadsheet with data

While current PE ratios, in all their variants, are not at 1999 levels, they have clearly climbed back to 2007 levels and are well above historical averages. Scary, right? This will inevitably lead to the warnings about markets overheating and a coming crash, just as it has for much of the last five years. While one of these years, that predicted crash will come, you may want to look at stock PE ratios relative to the PE ratio on a treasury bond today, another comparison that I made in my CAPE post;

Spreadsheet with data

It is true that stocks look expensive today (at 27 times earnings) but they start to look much better when you compare them to bonds (at 40 times earnings). If you are concerned that bond rates will climb this year to reflect higher inflation/real growth, you may be forced to take another look at how you are pricing stocks at that time. There is one final divergence that needs explaining. In the last section, I noted that implied equity risk premiums on the US market look reasonable or even high relative to historical norms (a sign that the market is not over valued) but in this section, I have pointed to PE ratios being higher than historical norms (a sign of stock prices overheating). How do you reconcile the two findings? The answer lies in this final graph:

Spreadsheet with data

While PE ratios have risen over the last five or six years by almost 35-40%, the ratio of price to cash returned to stockholders (in the form of dividends and buybacks) has barely budged for the last five years. Here again, you should heed the warnings in the last section, where I noted that US companies are returning almost 107% of their earnings as cash to stockholders, unsustainable in the long term. If companies abruptly pull back on stock buybacks, the delicate balance that has allowed for the long bull market will be threatened.

The Closing
In summary, the primary threats to stocks at the start of 2017, whether you look at implied equity risk premiums or PE ratios, come from two sources. The first is that interest rates will rise quickly, without a concurrent increase in earnings, and the second is that companies will scale back the cash they return to stockholders to get back to a sustainable payout. Is there a reasonable probability that these events could occur? Of course, and if they both do, it will be a bad year for stocks. However, there is almost equal likelihood that as interest rates rise, earnings will rise even more (partly because of higher inflation/growth and partly because of cuts in corporate taxes) and that companies are able to sustain or even augment cash returned to stockholders. If this scenario unfolds, it will be a very good year for stocks. I will predict that you will be hearing from absolutists on both sides of this argument, one side preaching bloom and doom and the other predicting a market surge. I am in awe of the conviction that each side has in its market-timing judgment, but I am afraid that my market crystal ball is much too cloudy for me to make strong market predictions. So, I will do what I have always done, invest in individual stocks that I find to be priced right and accept that I have little or no control over the market.

YouTube Video

Datasets

There was a time in the not so distant past, where analysts could do their analysis in their local currencies and care little or not at all about foreign currencies, how they moved and why. This was particularly true for US analysts in the last half of the last century, where the US dollar was the unchallenged global currency and the US economy bestrode the world. Those days are behind us and it is almost impossible to do valuations or corporate financial analysis without understanding how to deal with currencies correctly. Since the perils of misplaying currencies can be catastrophic, I decided to spend this post getting up to speed on the basics of how currency choices play out in valuation and where the numbers stand at the start of 2017.

A Currency Primer in Valuation

In intrinsic valuation, the value of an asset is the expected cash flows on that asset, discounted back at a risk adjusted discount rate.

Note that there is no currency specification in the DCF equation and that analysts are given a choice of currencies. So, what currency should you use in valuing a company? While some analysts view this choice rigidly as being determined by the country in which the company operates in or the currency that it reports its financial statements in, there are two basic propositions that govern this choice.

The first is that currency is a measurement mechanism and that you should be able to value any company in any currency, since all it will require is restating cash flows, growth rates and discount rates in that currency.
The second is that in a robust DCF valuation, your value should be currency invariant. Put differently, the value of Petrobras should be unchanged, whether you value the company in nominal Brazilian Reais ($R), US dollars or Euros.

The second proposition may strike some as impractical, since risk free rates vary across currencies and some currencies, like the $R, have higher risk free rates than others, like the US dollar. But the key to understanding currency invariance is recognizing that currency choices affect both your cash flows and your discount rate and if you are being consistent about your currency estimates, those effects should cancel out.

Intuitively, picking a high inflation currency will lead to higher discount rates but also to higher cash flows and growth rates. In fact, if the currency effect is a pure inflation effect, you can see very quickly that you could make your valuation currency-free by doing your entire analysis in real terms, where you cash flows reflect only real growth (without the boost offered by inflation) and your discount rate is built on top of a real risk free rate. Your value should be again equivalent to the value you would have obtained by using the currency of your choice in your valuation.

To make these estimation choices real, consider valuing a company that derives half its cash flows in the United States (in US dollars) and half in Brazil (in nominal $R). You can value the company in US dollars, and to do so, you would have to estimate its cost of capital in US $ and convert the portion of its cash flows that are in $R to US$ in future years; that would require forecasting exchange rates. Alternatively, you can value the company in $R, converting the portion of cash flows in US$ to $R and then estimating a cost of capital in $R. This may sound simple, even trivial, but a whole host of estimation challenges lie in wait.

Expected Exchange Rates

If you want to make your valuations currency invariant, and inflation is what sets currencies apart, the way to estimate expected future exchange rates is to assume purchasing power parity, where exchange rates move to capture differential inflation. Specifically, you can get from the current exchange rate of local currency (LC) for the foreign currency (FC) to an expected exchange rate in a future year (t) using the expected inflation rates in the two currencies:

Simply put, if the inflation in the local currency is 5% higher than the inflation in the US$, you are assuming that the local currency will depreciate about 5% a year. I know that exchange rate movements deviate from purchasing power parity significantly over short and perhaps even extended periods and that expected inflation can be difficult to estimate in many currencies, but there is a simple reason why you should stick with this simplistic way of forecasting exchange rates, at least when it comes to valuation. First, it is far easier (and less expensive) that creating a full-fledged exchange rate forecasting model or paying a forecaster, especially because you have to forecast exchange rate changes over very long time periods. Second, it forces you to be explicit about your inflation expectations and by extension, at least be aware of inconsistencies, where you assume one measure of inflation for exchange rates (and cash flows) and another for discount rates. (You can use forward exchange rates for the near years, as long as you are willing to then use interest rate differentials as proxies for inflation differentials.)

But what if you have strong views on the future direction of exchange rates that deviate from inflation expectations? I would argue that you should not bring them into your company valuations for a simple reason. If you incorporate your idiosyncratic exchange rate forecasts into cash flows and value, your final valuation of a company will be a joint consequence of your views on the company and of your views on exchange rates, with no easy way to separate the two. Thus, if you expect the Indian rupee to appreciate over the next five years, rather than depreciate (given your expectations of inflation in the rupee), you will find most Indian companies that you value to be cheap. If that conclusion is being driven by your exchange rate views, why invest in Indian companies when there are far easier and more profitable ways of playing the exchange rate game?

Currency Costs of Capital

Let's start with the challenge of estimating costs of capital in different currencies. There are two general approaches that you can use to get there. One is to compute the cost of capital in a currency from the ground up, starting with a risk free rate and then estimating and adding on risk premiums to arrives at costs of equity, debt and capital. The other is to compute the cost of capital in a base currency (say the US dollars) and then converting that cost of capital to the local currency.

Currency Risk Free Rates

Every economics student, at some point early in his or her education, has seen the Fisher equation, where the nominal interest rate is broken down into an expected inflation component and an expected real interest rate:

Nominal Interest Rate = Expected Inflation + Expected Real Interest Rate

Note that this is neither a theory nor a hypothesis, but a truism, if you add no constraints on either the expected inflation and real interest rate. It is also a powerful starting point for thinking about what goes into a risk free rate and why it changes over time. It is as you add constraints on the components of interest rates that you start making assumptions which may or may not be true, and require testing. You could assume, for instance, that actual inflation in the most recent periods is a reasonable proxy for expected inflation in the future and that the real interest rate can be approximated to by the real growth rate in the economy in the most recent period (not an unreasonable assumption in mature economies). In fact, it is this proposition that I used in my last post on US markets to estimate intrinsic T.Bond rates that I compared to actual rates. I will use this framework as my back up as I look at four different ways of estimating risk free rates in different currencies.

1. Government Bond Rate

In this, the most common practice in valuation, analysts assume that the local currency government bond rate is the risk free rate in that currency. To justify this usage, they argue that governments will not default on local currency bonds, since they can always print off enough currency to pay off debt. In table 1, I graph local currency 10-year government bond rates as of January 1, 2017 for those currencies where I was able to obtain them.

This approach has the advantage of simplicity and is perhaps even intuitively defensible but there are real dangers associated with it. The first is that the government bond may not be liquid and traded and/or the government exercises control over the rate, it is not a market-set rate reflecting demand and supply. The second is that implicit in the use of the government bond rate as the risk free rate is the assumption that governments never default in the local currency. That assumption has been violated at least a half a dozen times just in the last twenty years, thus making the government bond rate a "risky", rather than a risk free, rate. The third is that using government bond rates as local currency risk free rates while using actual inflation rates as expected inflation can lead to both inconsistent and currency dependent valuations. For instance, assume that you decide to value Natura, the Brazilian cosmetics company, in $R and use the Brazilian government $R bond rate of 11.37%, on January 1, 2017, as the risk free rate while using the actual inflation rate of 6.29% (inflation rate last year, according to government statistics) as the expected inflation rate. The value that you estimate for the company will be much lower than the value that you estimate for the company if you valued it in US dollars, with a risk free rate of 2.50% and an expected inflation rate of 2%. The reason for the valuation difference is intuitive. By using the $R numbers, you are effectively using a real risk free rate of 5.08%, when you do your valuation in $R, and only 0.5%, when you do your valuation in US dollars.

2. Government Bond Rate, net of default spread

In this approach, you do not start with the presumption that governments are default free. Instead, you start with the local currency government bond rate and subtract out the portion of that rate that you believe is due to perceived default risk:

Risk free rate in local currency = Local Currency Government Bond rate â Default Spread in Local Currency Government Bond rate

The practical question then becomes how best to estimate the local currency default spread and there are a few approaches, though each comes with limitations. The first is to find a US dollar denominated bond issued by the government in question and netting out the US T.Bond rate, thus getting a default spread on the bond. The second is to use a sovereign CDS spread for the country as a proxy for default risk. In the table below, Subtracting these default spreads from the local currency bond rates, on the assumption that default risk in both local and foreign currency borrowing is equivalent, would yield local currency risk free rates. Using the sovereign rating-based default spreads, we can estimate the risk free rates in different currencies in January 2017:

This approach comes with its own perils that are layered on top of the assumption that the government bond rate is a market-set interest rate. First, it assumes that the local currency sovereign rating is measuring the default risk in the currency and that you can estimate the default spread based on it. Second, both the rating-based and sovereign CDS default spreads are US dollar based and netting it out against a local currency government bond rate can be viewed as inconsistent.

3. Differential Inflation Based Rates

The third approach is to ignore government bond rates in the local currency entirely, either because you believe that they are not liquid enough to yield reliable numbers or because they contain default risk. Instead, you start with a risk free rate in a currency where you believe that the government bond rate is a reliable measure of the risk free rate (US Treasury Bond, German Euro Bond) and then add to this number the differential inflation rate between the US dollar and the local currency.

Local Currency Risk free Rate = US $ Risk free Rate + (Expected inflation in local currency â Expected inflation in US $)

This is an approximation that works reasonably well when local currency inflation is low (close to the US dollar inflation rate) but the more precise version of this formulation will be based upon compounding, just as the Fisher equation was:

The linked table lists differential inflation based risk free rates in all currencies, using expected inflation rates (the World Bank's estimates) and the US dollar (estimated at about 2%, the difference between the US 10-year T.Bond and TIPs rates). If you are concerned about being able to forecast expected inflation in the local currency, you should rest easy. As long as you use that same expected inflation rate in your cash flow estimation, your valuation will be inflation-invariant and currency consistent, since the effects of under or over estimating inflation will cancel out.

4. Intrinsic Risk Free Rates

In the differential inflation approach, using the US dollar risk-free rate as the starting point, you are assuming a global real risk free rate, set equal to that rate embedded in the US treasury bond rate as the base for all local currency risk free rates. If you feel uncomfortable with this assumption, you can estimate a synthetic risk free rate from scratch, drawing on the Fisher equation:

Risk free Rate = Expected Real Interest Rate + Expected inflation rate

You can augment this equation with the assumption that long term real growth in an economy will converge on the long term real interest rate.

Expected Real Interest Rate = Expected Real Growth Rate

Synthetic Risk free Rate = Expected Real Growth Rate + Expected inflation rate

This approach yields the maximum flexibility but it will also create differences in valuations in different currencies. This linked table lists out synthetic risk free rates using this approach, using average real GDP growth as your expected real growth rate. The downside of this approach will be that your valuations will vary across currencies, yielding difficult-to-defend conclusions sometimes, where a company looks cheap when analyzed in US dollars but expensive when valued again in the local currency. The advantage of this approach, as with the differential inflation approach, is that you can estimate risk free rates for many more countries than with the government bond approach.

Currency Cost of Capital

If you start with a risk free rate in a local currency and build up to a cost of capital using equity risk premiums and default spreads, often available only in dollar-based markets, you are effectively assuming that risk premiums are absolute numbers that don't change as the risk free rate changes. Thus, the equity risk premium of 5.69%, estimated in a dollar-based US market, applies not only to the US dollar risk free rate of 2.45% but also to the Nigerian Naira risk free rate of 10.77%. That is a stretch, since you would expect to risk premium you charge to be higher with the latter than the former. There is an easy and logical fix for it and it lies in the differential inflation approach. Rather than apply it to adjust the US$ riskfree rate to a local currency rate, you could apply it to the cost of equity or capital instead:

Thus, if your cost of capital in US $ is 8%, the inflation rate in $R is 6% and in US$ is 2%, your cost of capital would be 12.24%. (Using the short cut of just adding the differential inflation would yield 12%). As part of my data update, I have reported costs of capital, by industry, in US dollars, for the last two decades. In this year's update, I have added a differential inflation feature allowing you to change that cost of capital to any currency of your choice in this spreadsheet. You will need to input the inflation rate in the local currency to get the costs of capital to update and you are welcome to use either the estimates that I supply in an additional worksheet or enter your own. Remember, though, that you should stay true to whatever this estimate is when estimating growth rates and cash flows in that currency.

The Closing

If your valuations are sensitive to your currency choice, you face a fundamental problem. You can find the same company, at the same pricing and point in time, to be both under and over valued, an indefensible conclusion. That conclusion, though, is being driven by some aspect of your valuation process that is making your company's fundamentals (risk, growth and cash flow potential) look different when you switch currencies. That, in my view, is a violation of intrinsic valuation and it requires you to make your inflation assumptions explicit and check for consistency.

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Datasets

Data 2017 Posts

Data Update 1: The Promise and Perils of Big Data
Data Update 2: The Resilience of US Equities
Data Update 3: Cracking the Currency Code - January 2017
Data Update 4: Country Risk and Pricing, January 2017
Data Update 5: Death and Taxes in January 2017- Changes Coming?
Data Update 6: The Cost of Capital in January 2017
Data Update 7: Profitability, Excess Returns and Corporate Governance- January 2017
Data Update 8: The Debt Trade off in January 2017
Data Update 9: Dividends and Buybacks in 2017
Data Update 10: A Pricing Update in January 2017

In my last post, I pointed to currency confusion as one of the side effects of globalization. In this one, I will argue that as companies and investors globalize, investors and analysts have no choice but to learn how to deal with the rest of the world, both in terms of risk and pricing. One reason that I take a detailed look at country risk and pricing numbers every year is that my valuations and corporate finance rest so heavily on them.

Why country risk matters
It seems to me an intuitive proposition that a companyâs value and pricing can depend upon the geography of its business. Put simply, cash flows generated in riskier countries should be worth less than equivalent cash flows generated in safer ones but there are two follow up propositions worth emphasizing:

Operation, not incorporation: I believe that it is where a company operates that determines its risk exposure, not just where it is incorporated. Thus, you can have US companies like Coca Cola (through its revenues) and Exxon Mobil (from its oil reserves) with substantial emerging market exposure and emerging market companies like Tata Consulting Services and Embraer with significant developed market exposure. In fact, what we face in valuation increasingly are global companies that through the accident of history happen to be incorporated in different countries.
Company, Country and Global Risks: Not all country risk is created equal, especially as you are look at that risk as a diversified investor. Some country risk can be isolated to individual companies and is therefore averaged out as you diversify even across companies in that country. Still other country risk is country-specific and can be mitigated as your portfolio includes companies from across the globe. There is, however, increasingly a portion of country risk that is global, where even a global investor remains exposed to the risk and more so in some countries than others. The reason that we draw this distinction is that risks that can be diversified away will affect only the expected cash flows; that adjustment effectively takes the form of taking into account the likelihood and cash flow consequences of the risk occurring when computing the expected cash flow. The risks that are not diversifiable will affect both the expected cash flows and also the discount rates, with the mode of adjustment usually taking the form of higher risk premiums for equity and debt. That may sound like double counting but it is not, since the expected cash flows are adjusted for the likelihood of bad scenarios and their consequences and the discount rate adjustment is to demand a premium for being exposed to that risk:
If you make the assumption that all country risk is diversifiable, you arrive at the conclusion that you don't need to adjust discount rates for country risk, a defensible argument when correlations across countries were very low (as in the 1980s) but not any more.

Thus, dealing with country risk correctly becomes a key ingredient of both corporate finance, where multinational companies try to measure hurdle rates and returns on projects in different countries and in valuation, where investors try to attach values or prices to the same companies in financial markets.

Country Default Risk

Since I have had extended posts on country risk before, I will not repeat much of what I have said before and instead focus this post on just updating the numbers. Simply put, the most easily accessible measures of country risk tend to be measures of default risk:

Sovereign Ratings: Ratings agencies like S&P, Moodyâs and Fitch attach sovereign ratings to countries, where they measure the default risk in government borrowing just as they do for individual companies. These ratings agencies often also provide separate ratings for local currency and foreign currency borrowings by the same government. The picture below summarizes ratings by country, in January 2017, and the linked spreadsheet contains the same data.
Link to live version of map
Government Bond Default Spreads: When a government issues bonds in a foreign currency, that are traded, the interest rate on those bonds can be compared to the risk free rate in a bond issued in the same currency to arrive at measures of default risk for the government. In much of Latin America, for instance, where countries has US-dollar denominated bonds, comparing the rates on those bonds to the US T.Bond rate (of equivalent maturity) provides a snapshot of default risk. The table below summarizes government bond default spreads as of January 1, 2017, for Latin American countries with US dollar denominated bonds:
Sovereign CDS Spreads: This measure of default risk is of more recent vintage and is a market-determined number. It is, roughly speaking, a measure of how much you would have to pay, on an annual basis, to insure yourself against country default and unlike ratings can move quickly in response to political or economic developments in a country, making them both more timely and more volatile measures of country risk. In January 2017, sovereign CDS spreads were available for 64 countries and you can see them in the picture below and download them as a spreadsheet at this link.
Link to live version of the map

Country Equity Risk

There are many who use country default spreads as a proxy for the additional risk that you would demand for investing in equity in that country, adding it on to a base equity risk premium (ERP) that they have estimated for a mature market (usually the US).

ERP for Country A = ERP for US + Default Spread for Country A

The limitation of the approach is that there are not only are equities affected by a broader set of risks than purely default risk but that even default can have a larger impact on equities in a country than its bonds, since equity investors are the residual claimants of cash flows.

There are broader measures of country risk, taking the form of country risk scores that incorporate political, economic and legal risks, that are estimated by entities, some public (like the World Bank) and some private (like PRS and the Economist). The first is that they tend to be unstandardized, in the sense that each service that measures country risk has its own scoring mechanism, with World Bank scores going from low to high as country risk increases and PRS going from high to low. The second is that they are subjective, with variations in the factors considered and the weights attached to each. That said, there is information in looking at how the scores vary across time and across countries, with the picture below capturing PRS scores by country in January 2017. The numbers are also available in the linked spreadsheet.

Link to live map

I have my own idiosyncratic way of estimating the country risk premiums that builds off the country default spreads. I use a ratio of market volatility, arguing that default spreads need to be scaled to reflect the higher volatility of equities in a market, relative to government bonds in that market.

Since the volatility ratio can be both difficult to get at a country level and volatile, especially if the government bond is illiquid, I compute volatilities in an emerging market equity index and an emerging market government bond index and use the resulting ratio as a constant that I apply globally to arrive at equity risk premiums for individual countries. In January 2017, I started my estimates with a 5.69% equity risk premium for mature markets (set equal to the implied premium on January 1, 2017, for the S&P 500) and then used a combination of default spreads for countries and a ratio of 1.23 for relative equity market volatility (from the index volatilities) to arrive at equity risk premiums for individual countries.

For countries that had both sovereign CDS spreads and sovereign ratings, I was able to get different measures of equity risk premium using either. For countries that had only a sovereign rating, I used the default spread based on that rating to estimate equity risk premiums (see lookup table here). For those countries that also had sovereign CDS spreads, I computed alternate measures of equity risk premiums using those spreads. Finally, for those frontier countries (mostly in the Middle East and Africa) that were neither rated nor had sovereign CDS spreads, I used their PRS scores to attach very rough measures of equity risk premiums (by looking at other rated countries with similar PRS scores). The picture below summarizes equity risk premiums by country and the link will give you the same information in a spreadsheet.

Link to live map

Closing

The one prediction that we can also safely make for next year is that just as we have each year since 2008, there will be at least one and perhaps even two major shocks to the global economic system, precipitated by politics or by economics or both. Those shocks affect all markets globally, but to different degrees and it behooves us to not only be aware of the impact after they happen but be proactive and start building in the expectation that they will happen into our required returns and values.

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Datasets

Data 2017 Posts

Data Update 1: The Promise and Perils of Big Data
Data Update 2: The Resilience of US Equities
Data Update 3: Cracking the Currency Code - January 2017
Data Update 4: Country Risk and Pricing, January 2017
Data Update 5: Death and Taxes in January 2017- Changes Coming?
Data Update 6: The Cost of Capital in January 2017
Data Update 7: Profitability, Excess Returns and Corporate Governance- January 2017
Data Update 8: The Debt Trade off in January 2017
Data Update 9: Dividends and Buybacks in 2017
Data Update 10: A Pricing Update in January 2017

There are three realities that you cannot avoid in business and investing. The first is that your returns and value are based upon the cash flows you have left over after you pay taxes. The second is that the taxes you pay are a function of both the tax code of the country or countries that you operate in and how you, as a business, work within (or outside) that code. The third is that the tax code itself can change over time, as countries institute changes in both rates and rules. The upcoming year looks like it will be more eventful than most, especially for US companies, as there is talk about major changes coming to both corporate and individual taxation.

Why taxes matter
While we are often casual in our treatment of taxes, the value of a business is a affected substantially by tax policy, with our measures of expected cash flows and discount rates both being affected by taxes.

In the numerator, you have expected cash flows after taxes, where the taxes you pay will reflect not only where in the world you generate income (since tax rates and rules vary across countries) but how the country in which you are incorporated in treats that foreign income. The US, for instance, requires US companies to pay the US tax rate even on foreign income, though the additional tax is due only when that income is remitted back to the US, leading to a predictable result. Multinational US companies leave their foreign income un-remitted, leading to the phenomenon of trapped cash (amounting to more than $2 trillion at US companies at the start of 2017).
The denominator, which is the discount rate, is also affected by the tax code. To the extent that tax laws in much of the world benefit debt over equity, using more debt in your financing mix can potentially lower your cost of capital. In computing this tax benefit from debt, there are two points to keep in mind. The first is that interest expenses save you taxes at the margin, i.e., your dollar in interest expense offsets your last dollar of income, saving you taxes on that last dollar, making it imperative that you use the marginal tax rate when computing your tax benefit from borrowing. The second is that companies have a choice on where to borrow money and not surprisingly choose those locations where they get the highest tax benefit (with the highest marginal tax rate). Is it any surprise that while Apple generates its income globally and finds ways to pay an effective tax rate of 21% on its taxable income in 2016, almost all of its debt is in the United States, saving taxes at an almost 40% marginal tax rate?

Following up, then, the values of all companies in a country can change, some in positive and some in negative ways, when tax codes get rewritten. Even if the corporate tax codes donât change, a companyâs decisions on how to structure itself and where geographically to go for growth will affect its cash flows and discount rates in future years.

Marginal Tax Rates

If the marginal tax rate is the rate that a business pays on its last dollar of income, where in its financial statements are you most likely to find it? The answer in most companies is that you do not, and that you have to look in the tax code instead. Fortunately, KPMG does a yeoman job each year of pulling these numbers together and reporting them and the most recent update can be found here. The map below lists marginal tax rates by country and you also download a spreadsheet with the latest numbers at this link:

Link to live map

As you survey the world's marginal tax rates, you can see why trapped cash has become such a common phenomenon at US companies. The US has one of the highest marginal tax rates in the world at 40% (including a federal tax rate of 35%, topped off with state and local taxes) and is one of only a handful of countries that still insist on taxing companies incorporated in their domiciles on their global income, rather than adopting the more defensible practice of territorial taxation, where you require businesses to pay taxes in the countries that they generate their income in. As Congress looks at what to do about âtrapped cashâ, with many suggesting a one-time special deal where companies will be allowed to bring the cash back, they should also realize that unless the underlying reason for it is fixed, the problem will recur. That will mean either lowering the US marginal tax rate closer to the rest of the world (about 25%) or changing to a territorial tax model.

The marginal tax rate is the number that you use to compute your after-tax cost of debt but that practice is built on the presumption that all interest expenses are tax deductible (and that you have enough taxable income to cover the interest deduction). That is still true in much of the world but there are parts of the world, where you either cannot deduct interest expenses (such as the Middle East) or you have taxes computed on a line item like revenues (thus nullifying the tax benefit of debt), where you will have to alter the practice of giving debt a tax benefit. For multinational companies that face different marginal tax rates in different operating countries, my recommendation is that you use the highest marginal tax rates across countries, since that is where these companies will direct their borrow.

Effective Tax Rates: Country Level Differences

If the marginal tax rate is the tax rate on your last dollar of income, what is the effective tax rate, the number that you often see reported in financial statements? In most cases, it is a computed tax rate that comes directly from the income statement and is computed as follows:

Effective Tax Rate = (Accrual) Taxes Payable / (Accrual) Taxable Income

Both number are accrual income number and thus can be different from cash taxes paid, with the differences usually visible in the statement of cash flows. Letâs start with looking at what companies pay as effective tax rates in the United States, a country with a marginal tax rate of 40%. In the most recent twelve months leading into January 2017, the distribution of effective tax rates paid by tax-paying US companies is captured below.

The most interesting numbers in this distribution are the average effective tax rate of 26.42% across profitable US companies, well below the marginal tax rate of 40%. and the fact that 88% of US companies have effective tax rates that are lower than the marginal. The most important reason for this difference, in my view, is foreign operations with those firms that generate revenues outside the United States paying lower taxes, simply because the tax rate on income outside the United States is much lower (and that differential tax is not due until the cash is remitted). While there are some who suggest that a simple fix for this is to force US firms to pay the entire marginal tax rate when they make their income in foreign locales immediately (rather than on repatriation), this will be a powerful incentive for US companies to move their headquarters overseas.

In these populist times, you may be convinced that US companies are not paying their fair share of taxes but is that true? To make that judgment, I looked at effective tax rates paid by companies in different countries in the picture below and you can download the data in a spreadsheet in the link below:

Link to live map

At least, based upon the data on taxes paid in 2017, US companies measure up well against the rest of the world, in terms of paying taxes, with only Japanese companies paying significantly more in taxes; Indian and Australian companies pay about what US companies do and the rest of the world pays less.

Sub Group	Effective Tax Rate	Sub Group	Effective Tax Rate
Africa and Middle East	15.48%	India	27.65%
Australia & NZ	26.76%	Japan	31.07%
Canada	19.68%	Latin America & Caribbean	22.91%
China	21.72%	Small Asia	21.59%
EU & Environs	23.03%	UK	22.26%
Eastern Europe & Russia	19.88%	United States	26.22%

As US companies market their products and services in other countries, it is true that some of this tax revenue is being collected by foreign governments, but that is the nature of a multinational business and is something that every country in the world with multinational corporations has as a shared problem.

Effective Tax Rates: Industry and Company Differences

As a final analysis, I compared the effective tax rates by US companies, categorized by industry. This table, which I have reported before, lists the ten industry groups that pay the highest effective tax rate and the ten that pay the lowest:

Download spreadsheets with all industries

The entire list can be downloaded here. Again, there are many reasons for the differences, with companies that generate more income from foreign operations paying lower taxes than domestic companies being a primary one. It is also true that the US tax code is filled with sector-specific provisions that provide special treatment for these sectors in the form of generous tax deductions. Most of these tax deductions (like higher depreciation allowances) show up as expenses in the income statement and the taxable income should already reflect them and so should the effective tax rate, but in some cases it does show up as a marginal tax rate.

While in most years, these differences across sectors is a just a source of discussion or a reason to vent on the unfairness of taxes, I believe that investors, this year, should be paying particular attention to them. If Congress is serious about rewriting the tax code this year, there is reason to believe that the changed tax code is going to create winners and losers, and especially so, if it is designed to be revenue neutral. Those winners and losers will of course be different, depending on which version of corporate tax reform passes.

At one extreme in the version that is least disruptive to the current system, the marginal tax rate for corporations will be lowered, perhaps with a loss of some tax deductions/credits and adjustments on how foreign income gets taxed to reduce the problem of trapped cash. If this change occurs, the effects on value will be mixed, with cash flows increasing for those firms that will have lower effective tax rates as a consequence and the costs of debt and capital increasing as the tax benefits of debt will decrease. The biggest beneficiaries will be firms that pay high effective tax rates today (see the table above for the sectors) and have little debt. The biggest losers will be firms that pay low effective tax rates today and fund their operations with lots of debt.
At the other extreme, the House of Representatives is considering a more radical version of tax reform, where the current corporate income tax will be scrapped and replaced with a "Destination Based Cash-flow Tax" (DBCT), a value added tax system, with a deduction for wages, where the tax rate that you pay as a company will be a function of how much of your input material you import and where you sell your output. The first side product of the DBCT will be that debt will lose its historical tax-favored status, relative to equity. The second side product is that, if left unadorned, it will eliminate any incentives to move profits across countries or borders, since the tax is not based on income. Companies who produce their goods with inputs from the US that then export these goods and services will benefit the most, paying the lowest taxes, whereas companies that are heavily reliant on imported inputs that sell their products in the United States would pay the most in taxes. And firms that are heavily debt funded will be adversely affected, relative to those that are not debt funded.

There are numerous other proposals that float in the middle, most offering lower corporate tax rates in exchange for loss of tax deductions. It is early in the game and we have no idea what the final version will look like. I will cheerfully confess that I am not expert on tax law and have absolutely no interest in providing specific directions on how the tax code should be rewritten but I will offer two simple pieces of advice having watched other attempts to rework corporate taxes:

Keep it simple: When tax law gets complex, bad corporate behavior seems to follow. Unfortunately, the way legislative processes work seems to conspire against simplicity, as legislators trying to protect specific industries try to make sure that their ox does not get gored.
The tax code is not an effective behavior modifier for businesses: I understand the desire of some to use tax law as a corporate behavior modification tool but it is not a very effective one. Thus, if Congress is serious about the DBCT, it should be because they believe it is a more effective revenue generating mechanism that the current complex system and not because it wants to encourage companies to move manufacturing to the United States. If that is a byproduct, that is a plus but it should not be the end game.
Make it predictable: Companies have enough uncertainty on their plates to worry about without adding uncertainty about future tax law changes to the mix. It would help if the tax code, once written, was not constant revisited and revised.

I am also a realist and believe that the likelihood of either of these pieces of advice being followed is close to zero.

Closing

In the process of computing an implied equity risk premium for the S&P 500, I collected analyst estimates of growth in earnings for the S&P 500 companies. Many of these analysts are predicting that earnings for the S&P 500 will grow strongly in 2017 and one shared reason seems to be that companies will pay less in taxes. Since legislative bodies are not known for speedy action, I am not sure that change, even if it does happen, will show up in 2017 earnings but I think that the ultimate test is not in what the tax code does to marginal tax rates (since I think it is a safe assumption that they will come down from) but the changed tax code will mean for effective tax rates. Assuming that the tax code does get rewritten, how will we know whether it is doing more good or harm? I have two tests. First, if companies think about, talk about and factor in taxes less in their decision making, that is a good sign. Second, if fewer people are employed as tax lawyers and in transfer pricers, that is an even better one. I won't be holding my breath on either!

YouTube Video

Datasets

Data 2017 Posts

Data Update 1: The Promise and Perils of Big Data
Data Update 2: The Resilience of US Equities
Data Update 3: Cracking the Currency Code - January 2017
Data Update 4: Country Risk and Pricing, January 2017
Data Update 5: Death and Taxes in January 2017- Changes Coming?
Data Update 6: The Cost of Capital in January 2017
Data Update 7: Profitability, Excess Returns and Corporate Governance- January 2017
Data Update 8: The Debt Trade off in January 2017
Data Update 9: Dividends and Buybacks in 2017
Data Update 10: A Pricing Update in January 2017

I have described the cost of capital as the Swiss Army knife of finance, a number that shows up in so many different places in corporate financial and analysis and valuation and in so many different contexts, that it is easy to mangle and misunderstand. In this post, my objective is simple. I will start with a description of the sequence that I use to get to a cost of capital for companies in January 2017, but the bulk of the post will be describing what the cost of capital looks like at the start of 2017 for companies around the world.

The Cost of Capital: Hurdle Rate, Opportunity Cost and Discount Rate
As I move from corporate finance to valuation to investment philosophies, the one number that seems to show up in almost every aspect of analysis is the cost of capital. In corporate finance, it is the hurdle rate that determines whether companies should make new investments, the optimizer for financing mix and the divining rod for how much to return to stockholders in dividends and buybacks. In valuation, it is the discount rate in discounted cash flow valuations and the determinants of enterprise value multiples (of EBITDA and sales).

It is perhaps because it is used in so many different contexts by such varied sub-groups that it remains a vastly misunderstood and misused number. If you are interested in reading more about the cost of capital, you may want to try this paper that I have on the topic (it is not technical or theoretical).

The Cost of Capital Calculation

The cost of capital is the weighted average of the costs of equity and debt for a business. While entire books have been written on the measurement questions, I will keep it simple.

1. The cost of equity is the rate of return that the marginal investors, i.e., the investors who are most influential at setting your market price, are demanding to invest in equity in your business. To get to that number, you need three inputs, a risk free rate to get started, a measure of how risky your equity is, from the perspective of the marginal investors, and a price for taking that risk.

Cost of Equity = Risk Free Risk + Relative Risk Measure * Price of Risk

In the rarefied world of the capital asset pricing model, you assume that the marginal investor is diversified, beta measures relative risk and the equity risk premium is the price of risk, yielding a cost of equity.

2. The cost of debt is the rate at which you can borrow money, long term and today. It is not a historic cost of borrowing, nor can it be influenced by decisions on changing debt maturity. It can be computed by adding a credit or default spread to the risk free rate but it does come, in many markets, with a tax benefit which is captured by netting it out of your cost.

After-tax Cost of Debt = (Risk Free Rate + Default Spread) (1- Marginal Tax Rate)

The default spread can sometimes be observed, if the company issues long term bonds, sometimes easily estimated, if the company has a bond rating and you trust that rating, and sometimes requires more work, if you have to estimate default risk yourself.

3. The weights on debt and equity should be based upon market values, not book values, and can change over time, as your company changes.

Since I want to compute the cost of capital for every one of the 42,668 firms that comprised this yearâs sample, I had to make some simplifying (and perhaps even simplistic) assumptions, some of which were necessitated by the size of my sample and some by data limitations. I have summarized them in the picture below.

I have computed the costs of capital for all companies in US dollar terms, not for parochial reasons, since converting to another currency is trivial (as I noted in my post on cracking the currency code) but to allow for consolidation and comparison.

The costs of capital that I compute for individual companies have two shortcomings, driven primarily by data limitations. The first is that the beta that I use for a company comes from the business that it is categorized in, rather than a weighted average of the multiple businesses that it may operate in. The second is that I have attached the equity risk premium of the country of incorporation rather than a weighted average of the ERPs of the countries in which a company operates; I had to do this since the revenue breakdowns by country were either not available for many companies or in too difficult a form to work with. If you want to compute the cost of capital for a company using my data, I have a spreadsheet that you can use that will let you break out of these bounds, allowing you to compute a beta across multiple businesses and an equity risk premium across many countries/regions.

Differences across Geographies

The first comparison I make is in the costs of capital across different countries and regions. The picture below shows cost of capital by country and you can download the data in a spreadsheet at this link.

Link to live map

Given that these are all US-dollar based costs of capital, the differences across countries can be attributed to four factors:

Country risk: Country risk shows up in two places in the cost of capital calculation, the equity risk premium for the company (which is set equal to the equity risk premium of the country it is in) and an additional default spread in the cost of debt.
Industry concentration: Since my measure of relative risk comes from looking at the global beta for the sector in which a company operates, the cost of capital for a country will reflect the breakdown of industries in that country. Thus, the cost of capital for Peru, a country with a disproportionately large number of natural resource companies, will reflect the beta of mining and natural resource companies.
Marginal tax rate: To the extent that a higher marginal tax rate lowers the after-tax cost of debt, holding all else constant, countries with higher marginal tax rates will have lower after-tax costs of debt and perhaps lower costs of capital.
Debt ratio: Twinned with the marginal tax rate, in computing how much a company is being helped by the tax benefit of debt, is the amount of debt that the company uses, with higher debt ratios often translating into lower costs of capital.

Differences across Industry Groups

I next turn to industry groupings and differences in cost of capital across them. In the table below, I list the ten (non-financial service) industry groupings globally, with the highest costs of capital, and the ten, with the lowest, at the start of 2017.

Spreadsheet with all industries

The reason for excluding financial service companies is simple. For banks, insurance companies and investment banks, the only hurdle rate that has relevance is a cost of equity, since debt is more raw material than a source of capital for these firms. You can download the entire industry list (with Global, European, Emerging Market and Australia/Canada worksheets) at this link, but again there are only a few reasons for the differences:

Business risk: Some businesses are clearly more risky than others and I am using my sector betas to capture the differences in risk.
Leverage differences: Companies in some sectors borrow more than others, with mixed effects on the cost of capital. The resulting higher debt to equity ratios push up sector betas more, leading to higher costs of equity. That, though, is more than partially offset by the benefit of raising financing at the after-tax cost of debt, a bargain relative to equity.
Country exposure: Some industry groupings have geographic concentrations and to the extent that those concentrations are in countries with very low or very high risk, relative to the rest of the world, your cost of capital will be skewed low or high.

Distributional Perspective

I have long argued that analysts spend far too much time on tweaking and finessing costs of capital in valuation and not enough on estimating earnings and cash flows, and I base my argument on a very simple fact. The distribution of costs of capital for publicly traded companies is a tight one, with a large proportion of companies falling in a very narrow range. Rather than talk in abstractions, consider the histogram of costs of capital for US and global companies at the start of 2017:

The median US $ cost of capital for a US company is 7.22%, 50% of all US companies have costs of capital between 5.69% and 8.14%, and 80% have costs of capital between 4.59% and 8.87%. If you expand the distribution to include all global stocks, your distribution widens but not by as much as you might think. The median US $ cost of capital for a global company is 8.03%, half of all global companies have costs of capital between 6.88% and 9.15% and 90% of all companies globally have costs of capital between 5.63% and 10.68%. In other words, you don't have a lot of leeway to move your cost of capital for publicly traded firms. It is true that as you bring in other currencies into the mix, you can make the differences larger, but as I noted in my post on currencies, it is because of differences in inflation. You may want to pay heed to these distributions the next time that you see an analyst using a 20% US$ cost of capital to value a "risky" company or a 3% US$ cost of capital for a "safe" company, since neither number looks defensible, given the distribution.

Cost of Capital Maxims
I think that we not only spend too much time on estimating costs of capital in valuation but we also misunderstand what it is designed to measure. At the risk of repeating myself, here are four suggestions that I have on the cost of capital:

Don't make the cost of capital the receptacle of all your hopes and fears: Many analysts take to heart the principle that riskier firms should have higher costs of capital (or discount rates) but then proceed to intuit what that discount rate should be for company, given how risky they think it is. In the process, they often incorporate risks that don't belong in discount rates and attach prices for those risks that reflect their gut responses rather than what the market is paying.
Focus on cash flows, not discount rates: When your valuations go awry, it is almost never because of the mistakes that you made on the discount rate and almost always because of errors in your estimates of cash flows (with growth, margins and reinvestment).
Spend less time on estimating discount rates: It follows then that when you have a limited amount of time that you can spend on a valuation (and who does not?), that time is better spent on assessing cash flows than in fine tuning the discount rate.
An approximation works well : When I am in a hurry to value a company, I use my distributional statistics (see graph above) to get started. Thus, if I am valuing an average risk company in US dollars, I will start off using an 8% cost of capital (the global median is 8.03%) and complete my valuation with that number, and if I still have time, I will come back and tweak the cost of capital. If it is very risky firm, I will start off with a 10.68% cost of capital (the 90th percentile) and gain revisit that number, if I have the time.

All in all, if your find yourself obsessing about the minutiae of discount rates in a valuation, it is perhaps because you want to avoid the big questions that make valuation interesting and challenging at the same time.

YouTube Video

Paper on the cost of capital

The Cost of Capital: The Swiss Army Knife of Finance

Spreadsheets

Cost of Capital Calculator for individual company

Datasets

Data 2017 Posts

Data Update 1: The Promise and Perils of Big Data
Data Update 2: The Resilience of US Equities
Data Update 3: Cracking the Currency Code - January 2017
Data Update 4: Country Risk and Pricing, January 2017
Data Update 5: A Taxing Year Ahead?
Data Update 6: The Cost of Capital in January 2017
Data Update 7: Profitability, Excess Returns and Corporate Governance- January 2017
Data Update 8: The Debt Trade off in January 2017
Data Update 9: Dividends and Buybacks in 2017
Data Update 10: A Pricing Update in January 2017

If asked to describe a successful business, most people will tell you that it is one that makes money and that is not an unreasonable starting point, but it is not a good ending point. For a business to be a success, it is not just enough that it makes money but that it makes enough money to compensate the owners for the capital that they have invested in it, the risk that they are exposed to and the time that they have to wait to get their money back. That, in a nutshell, is how we define investment success in corporate finance and in this post, I would like to use that perspective to measure whether publicly traded companies are successful.

Measuring Investment Returns

The first step towards measuring investment success is measuring the return that companies make on their investments. This step, though seemingly simple, is fraught with difficulties. First, corporate measures of profits are not only historical (as opposed to future expectations) but are also skewed by accounting discretion and practice and year-to-year volatility. Second, to measure the capital that a company have invested in its existing investments, you often have begin with what is shown as capital invested in a balance sheet, implicitly assuming that book value is a good proxy for capital invested. Notwithstanding these concerns, analysts often compute a return on invested capital (ROIC) as a measure of investment return earned by a company:

This simple computation has become corporate financeâs most widely computed and used ratio and while I compute it and use it in a variety of contexts, I do so with the recognition that it comes with flaws, some of which can be fatal. In the context of reporting this statistic at the start of last year, I reported my ROIC caveats in a picture:

Put simply, it would be unfair of me to tar a company like Tesla as a failure because it has a negative return on invested capital, because it is a company early in its life cycle, and dangerous for me to view HP as a company that has made good investments, because it has a high ROIC, because that is only because it has written off almost $16 billion of mistakes, reducing its invested capital and inflating its ROIC. I compute the return on invested capital at the start of 2017 for each company in my public company sample of 42,668 firms, using the following judgments in my estimation:

I do make adjustments to operating income and invested capital that reflect my view that accounting miscategorizes R&D and operating leases. I am still using a bludgeon rather than a scalpel here and the returns on invested capital for some companies will be off, either because the last yearâs operating income was abnormally high or low and/or accountants have managed to turn the invested capital at this company into a number that has little to do with what is invested in projects. That said, I have the law of large numbers as my ally.

Measuring Excess Returns

If the measure of investment success is that you are earning more on your capital invested than you could have made elsewhere, in an investment of equivalent risk, you can see why the cost of capital becomes the other half of the excess return equation. The cost of capital is measure of what investors can generate in the market on investments of equivalent risk. Thus, a company that can consistently generate returns on its invested capital that exceed its cost of capital is creating value, one that generates returns equal to the cost of capital is running in place and one that generates returns that are less than the cost of capital, it is destroying value. Of course, this comparison can done entirely on an equity basis as well, using the cost of equity as the required rate and the return on equity as a measure of return:

In general, especially when comparing large numbers of stocks across many sectors, the capital comparison is a more reliable one than the equity comparison. My end results for the capital comparison are summarized in the picture below, I break my global companies into three broad groups; the first, value creators, includes companies that earn a return on invested capital that is at least 2% greater than the cost of capital, the second, value zeros, includes companies that earn within 2% (within my estimation error) of their cost of capital in either direction and the third, value destroyers, that earn a return on invested capital that is 2% lower than the cost of capital or worse.

The public market place globally, at least at the start of 2017, has more value destroyers than value creators, at least based upon 2016 trailing returns on capital. The good news is that there are almost 6000 companies that are super value creators, earning returns on capital that earn 10% higher than the cost of capital or more. The bad news is that the value destroying group has almost 20,000 firms (about 63% of all firms) in it and a large subset of these companies are stuck in their value destructive ways, not only continuing to stay invested in bad businesses, but investing more capital.

If you are wary because the returns computed used the most recent 12 months of data, you are right be. To counter that, I also computed a ten-year average ROIC (for those companies with ten years of historical data or more) and that number compared to the cost of capital. As you would expect with the selection bias, the results are much more favorable, with almost 77% of firms earning more than their cost of capital, but even over this much longer time period, 23% of the firms earned less than the cost of capital. Finally, if you are doing this for an individual company, you can use much more finesse in your computation and use this spreadsheet to make your own adjustments to the number.

Regional and Sector Differences
If you accept my numbers, a third of all companies are destroying value, a third are running in place and a third are creating value, but are there differences across countries? I answer that question by computing the excess returns, by country, in the picture below:

Link to live map

Just a note on caution on reading the numbers. Some of the countries in my sample, like Mali and Kazakhstan have very few companies listed and the numbers should taken with a grain of salt. Breaking out the excess returns by broad regional groupings, here is what I get:

Spreadsheet with country data

Finally, I took a look at excess returns by sector, both globally and for different regions of the world, comparing returns on capital on an aggregated basis to the cost of capital. Focusing on non-financial service sectors, the sectors that delivered the most negative and most positive excess returns (ROIC - Cost of Capital) are listed below:

Spreadsheet with sector data

Many of the sectors that delivered the worst returns in 2016 were in the natural resource sectors, and depressed commodity prices can be fingered as the culprit. Among the best performing sectors are many with low capital intensity and service businesses, though tobacco tops the list with the highest return spread, partly because the large buybacks/dividends in the sector have shrunk the capital invested in the sector.

For investors, looking at this listing of good and bad businesses in 2017, I would offer a warning about extrapolating to investing choices. The correlation between business quality and investment returns is tenuous, at best, and here is why. To the extent that the market is pricing in investment quality into stock prices, there is a very real possibility that the companies in the worst businesses may offer the best investment opportunities, if markets have over reacted to investment performance, and the companies in the best businesses may be the ones to avoid, if the market has pushed up prices too much. There is, however, a corporate governance lesson worth heeding. Notwithstanding claims to the contrary, there are many companies where managers left to their own devices, will find ways to spend investor money badly and need to be held to account.

What next?

I am not surprised, as some might be, by the numbers above. In many companies, break even is defined as making money and profitable projects are considered to be pulling their weight, even if those profits donât measure up to alternative investments. A large number of companies, if put on the spot, will not even able to tell you how much capital they have invested in existing assets, either because the investments occurred way in the past or because of the way they are accounted for. It is not only investors who bear the cost of these poor investments but the economy overall, since more capital invested in bad businesses means less capital available for new and perhaps much better businesses, something to think about the next time you read a rant against stock buybacks or dividends.

YouTube Video

Spreadsheet

ROIC Calculator

Datasets

Data 2017 Posts

Data Update 1: The Promise and Perils of Big Data
Data Update 2: The Resilience of US Equities
Data Update 3: Cracking the Currency Code - January 2017
Data Update 4: Country Risk and Pricing, January 2017
Data Update 5: A Taxing Year Ahead?
Data Update 6: The Cost of Capital in January 2017
Data Update 7: Profitability, Excess Returns and Corporate Governance- January 2017
Data Update 8: The Debt Trade off in January 2017
Data Update 9: Dividends and Buybacks in 2017
Data Update 10: A Pricing Update in January 2017

There is no aspect of corporate finance where morality plays a bigger role than the decision of how much to borrow. That should come as no surprise. For generations, almost every religion has inveighed against debt, with some seeking outright bans and others strongly urging followers to "neither a borrower nor a lender be", and perhaps with good reason. History is filled with instances of human beings, caught up in the mood of the moment, borrowing money and then finding themselves destitute in bad times. That said, there is no denying that the decision of whether to borrow money, and if so how much to borrow, has become a critical part of running a business.

The trade off on debt

In corporate finance, the discussion of debt begins with an examination of the trade offs on using debt, instead of equity, to finance operations. I have described debt as a double-edged sword before, and running out of analogies, I am going to draw on Star Wars framing, and talk about the light side (benefits) of debt and the dark side (costs) of debt. In the course of the discussion, I want to separate the illusory benefits and costs of debt from the real benefits and costs, partly because I see them mixed up in practice all the time.

In terms of the real factors that drive the trade off, debt creates two benefits. The biggest comes from the tilt in the tax code, which allows interest expenses to be tax deductible and cash flows to equity to be not. The secondary benefit is that debt can operate as a disciplinary mechanism, with the discipline of having to make debt payments restraining managers from taking truly abysmal projects. These benefits have to be offset against two big costs, the first and biggest being the increased likelihood of distress and the second being the potential for disagreements between lenders and equity investors about the future of the firm (and how it plays out as debt covenants). All of these factors show up in the cash flows and risk assessment of a business. There are however illusory factors that can be distracting. On the benefit side, there are some who argue that debt is good because it can push up your return on equity or point to the fact that the cost of debt is lower than the cost of equity. Both statements are generally right, but the flaw in reasoning in both is that they assume that as you borrow more money, your cost of equity will remain unchanged, and it will not. In fact, in the absence of debt and distress, the positive and negative effects will offset each other, leading to no value change. On the cost side, debt detractors will note that the interest expenses associated with debt will lower net income, ignoring the fact that the lower net income is now being earned on a lower equity base. If the argument is that debt will increase default risk and the cost of debt, it is worth pointing out that even at the higher cost, debt is still cheaper than equity. Finally, there are transient factors that come from market frictions, where if your equity is mis-priced or the interest rate on your debt is set too low or high (given your default risk), you (as the company) may take advantage of the friction, using more debt if equity is under priced and debt carries too low an interest rate and less debt if equity is over priced and debt carries too high a rate. This, of course, will require CFOs of companies to embark on that most dangerous of expeditions, of judging market assessments of their value and risk. The picture below brings together all of the elements:

As we debate why companies borrow money and how it affects their value, it is good to be clear eyed about how debt changes value. It is almost entirely because of the tax benefit that it is endowed with, and if you take that tax benefit away, the reasons for borrowing quickly dissipate.

The Cross Sectional Distribution

Before we embark on an examination of debt loads across companies, let's start by looking at three different measures of financial leverage:

Debt to Capital = Debt/ (Debt + Equity): This is a measure of how much of the capital in a company comes from debt. It can be measured as accountants see value (with book values for debt and equity) or as the market sees it (with market values for debt and equity).
Debt to Equity = Debt/Equity: This is a close variant of debt to capital, with debt stated as a percent of equity, again in book value or market value terms.
Debt to EBITDA = Debt/EBITDA: This measures how much debt a company has relative to the cash it generates from operations, before taxes and capital expenditures.

In computing my total debt for the 42,668 companies in my sample, I include all interest bearing debt (short term, as well as long term) as well as the present value of lease commitments (which I treat as debt, and which accountants will start treating as debt in 2018 or 2019). I will start by looking at the distribution of debt to capital ratios, in both book and market terms, across all companies:

A large percentage of firms, more than 25% in the US and almost 20% globally, have no debt. Regionally, on a market debt to capital ratio, Eastern Europe(with Russia) and Latin America are the most highly levered regions of the world, but in terms of debt as a multiple of EBITDA, Canadian and Chinese companies have the highest debt burden.

I follow up by looking at debt to capital ratios for companies, by country, in the picture below and the statistics for all four measures of leverage in this spreadsheet.

Link to live map

Latin America and Eastern Europe remain the most indebted region in the world, with almost every country in each region having debt ratios of 30% or higher in market value terms and often 50% or higher in book value terms. While some of this can be attributed to the drop in commodity prices over the last few years, I think that one reason is that many Latin American companies are hooked on a combination of high (and often unsustainable) dividends and a desire for control (manifested in an unwillingness to dilute equity ownership). The same factors explain why many Middle Eastern companies, where there is no tax benefit from debt, continue to borrow money.

Industry Differences

You would expect companies in different sectors to have very different policies on financial leverage, and most of the differences have to do with where they fall on the debt trade off. In the table below, I list the most highly levered and lightly levered non-financial service sectors in the United States, in terms of market debt to capital ratios.

Spreadsheet with debt ratios, by sector

There are few surprises on this list, as you see technology sectors (software, online retail, semiconductor, semiconductor equipment and electronics) on the least-levered list and capital intensive sectors (power, trucking, telecom) on the most-levered list. It is interesting that integrated oil/gas companies are among the least levered sectors but oil/gas distribution is on the most levered list. If you want to see the full list of industries, not just for the United States but also for other regions of the world, try this spreadsheet.

Closing

In my earlier post on taxes, I noted that 2017 is likely to be a year of change, at least for the US tax code and almost every version of tax reform that is being talked about will reduce the marginal tax rate and therefore the tax benefits of debt. In fact, there are some versions where the entire tax benefit of debt will be removed. While I believe that this will be healthier in the long term for businesses, it will be a seismic shift that will have massive effects not just on corporate borrowing but on the corporate bond market. I am not sure that we (as investors and companies) are ready for that big a change. So, small steps way from the status quo, which is skewed strongly towards borrowers, may be all that you can expect to see!

YouTube Video

Spreadsheets

Datasets

Data 2017 Posts

Data Update 1: The Promise and Perils of Big Data
Data Update 2: The Resilience of US Equities
Data Update 3: Cracking the Currency Code - January 2017
Data Update 4: Country Risk and Pricing, January 2017
Data Update 5: A Taxing Year Ahead?
Data Update 6: The Cost of Capital in January 2017
Data Update 7: Profitability, Excess Returns and Corporate Governance- January 2017
Data Update 8: The Debt Trade off in January 2017
Data Update 9: Dividends and Buybacks in 2017
Data Update 10: A Pricing Update in January 2017

If you are from my generation, I am sure that you remember Rodney Dangerfield, whose comedy routine was built around the fact that "he got no respect". This post is about dividends and cash return, the Rodney Dangerfield of Corporate finance, a decision that gets no respect and very little serious attention from either academics or practitioners. In many companies, the decision of how much to pay on dividends is made either on auto pilot or on a me-too basis, which is surprising, since just as a farmerâs payoff from planting crops comes from the harvest, an investorâs payoff from investing should come from cash flows being returned. The investment decisions get the glory, the financing decisions get in the news but the dividend decisions are what complete the cycle.

The Dividend Decision
The decision of whether to return cash to the owners of a business and if yes, in what form, is the dividend decision. Since these cash flows are to equity investors, who are the residual claim holders in a business, logically, the dividend decision should be determined by and come after the investment and financing decisions made by a business. The picture below captures how dividends would be set, if they were truly residual cash flows:

The process, which mirrors what you see in a statement of cash flows, starts with the cash flow to equity from operations, computed by adding back non-cash charges (depreciation and amortization) to net income. From that cash flow, the firm decides how much to reinvest in short term assets (working capital) and long term assets (capital expenditures), supplementing these cash flows with debt issuances and depleting them with debt repayments. If there is any cash flow left over after these actions, and there is not guarantee that there will be, that cash flow is my estimate of potential dividend or if you prefer a buzzier word, the free cash flow to equity. With this free cash flow to equity, the firm can do one of three things: hold the cash (increasing its cash balance), pay a dividend or buy back stock. To the right of the picture, I use a structure that I find useful in corporate finance, which is the corporate life cycle, to illustrate how these numbers change as a company ages.

Early in a companyâs life, the operating cash flows are often negative (as the company lose money) and the hole gets deeper as the company has to reinvest to generate future growth and is unable to borrow money. Since the potential dividends (FCFE) are big negative numbers, the company will be raising new equity rather than returning cash.
As the company starts to grow, the earnings first turn positive but the large reinvestment needs to sustain future growth will continue to keep potential dividends negative, thus justifying a no-cash return policy still.
As the company matures, there will be two developments: the operating cash flows to equity will start exceeding reinvestment needs and the companyâs capacity to borrow money will open up. While the initial response of the company to these developments will be denial (about no longer being growth companies), you cannot hide from the truth. The cash balance will mount and the companyâs capacity to borrow money will be increasingly obvious and pressure will build on it to return some of its cash and borrow money.
Even the most resistant firms will eventually capitulate and they will enter the period of plentiful cash returns, with large dividends supplemented by stock buybacks, at least partially funded by debt.
Finally, you arrive at that most depressing phase of the corporate life cycle, decline, when reinvestment is replaced with divestitures (shrinking the firm and increasing free cash flows to equity) and the cash return swells. The company, in a sense, is partially liquidating itself over time.

The truth is that there are companies where the decision on how much to pay in dividends in not the final one but the one made first. Put differently, rather than making investment and financing decisions first, based upon what works best for the firm, and paying the residual cash flow as dividends, firms make their dividend decisions (and I include buybacks in dividends) first and then modify their financing and investing decisions, given the dividends.

The companies that follow this backward sequence, and there are a lot of them, can easily end up with severely dysfunctional dividend policies that can destroy them, unless good sense prevails. It is an attitude that was best captured by Andrew Mackenzie, CEO of BHP Billiton, who when analysts asked him in 2015 whether he planned to cut dividends, as commodity prices plummeted and earnings dropped, responded by saying "over my dead body".

Dividends, Cash Return and Potential Dividends: The US History

Letâs start with some history on dividends, using the US market. In the graph below, I start by providing the basis for my inertia theory of dividends by looking at the proportion of US firms each year that increase dividends, decrease dividends and leave dividends unchanged:

In every year, since 1988, far more firms left dividends untouched than increased or decreased them, and when dividends did get changed, they were far more likely to be increased than decreased.

Letâs follow with another fact about US companies. Increasingly, they are replacing dividends, the time-tested way of returning cash to stockholders, with stock buybacks, as you can see in the figure below, where I graph dividends and stock buybacks from the S&P 500 companies from 1988 to 2016.

The shift is remarkable. In 1988, almost 70% of all cash returned to stockholders took the form of dividends and by 2016, close to 60% of all cash returned took the form of buybacks. I have written about why this shift has occurred in this post and also why much of the breast beating you hear about how buybacks represent the end of the economy is misdirected. That said, the amount of cash that US companies are returning to stockholders is unsustainable, given the earnings and expectations of growth. In the figure below, I look at for the S&P 500, the cash returned to investors as a proportion of earnings each year from 2001 to 2016:

In 2015 and 2016, the companies in the S&P 500 returned more than 100% of earnings to investors. It is the reason that I highlighted the possibility of a pull back on cash flows as on the stock marketâs biggest vulnerabilities this year in my post on US equities.

Cash Return: A Global Comparison

Having looked at US companies, letâs turn the focus to the rest of the world. The stickiness of dividends that we see in the United States is a global phenomenon, though it takes different forms in some parts of the world; in Latin America, for instance, it is payout ratios, not absolute dividends, that companies try to maintain. To provide a measure of cash returned, I report on three statistics:

Cash Return Statistic	Definition	What it measures
Dividend Yield	Dividends/Market Cap	Portion of equity return that comes from dividends.
Dividend Payout	Dividends/Net Income (if net income is positive, NA if negative)	Proportion of earnings held back by the company for reinvestment or as cash balance.
Cash Return/FCFE	(Dividends + Buybacks)/FCFE (if FCFE is positive, NA if negative)	Percentage of potential dividends returned to stockholders. Remaining goes into cash balance.

The picture below looks at these dividend yields and payout ratios across the globe:

Link to live map

Unlike investment and debt policy, it is difficult to determine what number here would be the âbestâ number to see. Clearly, over time, you would like companies to return residual cash to stockholders but prudent companies, facing difficult business times, should try to hold back some cash as a buffer. Returning too little cash (low payout ratios) for long periods, though, is indicative of an absence of stockholder power and a sign that managers/insiders are building cash empires. Returning too much cash can mean less cash available for good projects and/or increasing debt ratios. In the table below, you can see the statistics broken down by region:

Link to full country spreadsheet

Let's take a look at the numbers in this table. The shift towards buybacks which has been so drastic in the United States seems to be wending its way globally. While there are markets like India, where buybacks are still uncommon (comprising only 6.36% of total cash returned), almost 30% of cash returned in Europe and 33% of cash returned in Japan took the form of buybacks. In Canada and Australia, companies returned over 150% of potential dividends to investors, perhaps because natural resource companies are hotbeds of dysfunctional dividend policy, with top managers maintaining dividends even in the face of sustained declines in commodity prices (and corporate earnings). The Mackenzie "over my dead body" dividend policy is live and well at many of other natural resource companies. With buybacks counted in, you see cash return rising above 100% for the US as well, backing up the point made earlier about unsustainable dividends.

Cash Return: A Company and Sector Comparison

Dividend policy varies across firms, the result of not only financial factors (where the company is in its life cycle, what type of business it is in and how investors get taxed) but also emotional ones (how risk averse managers are and how much they value control). As a result dividend yields and payout ratios vary widely across companies, and the picture below captures the distribution of both statistics across US and global companies:

There are wide variations in cash return across sectors, some reflecting where they stand in the life cycle and some just a function of history. In the table below, I highlight the sectors that returned the most cash, as a percent of net income, in the table below:

It is difficult to see a common theme here. You can see the residue of sticky dividends and inertia in the high cash return at oil and gas companies, perhaps still struggling to adapt to lower oil prices. There are surprises, with application software and biotech firms making the list. Looking at the sectors that returned the least cash, here is the list of the top ten:

If the cash that companies can return increases as they age, you should see the cash return policies change over time for sectors. Many of the technology firms that were high growth in the 1980s are now ageing and they are returning large amounts of cash to their stockholders; Apple, IBM and Microsoft are at the top of the list of companies that have bought back the most stock in the last decade.

Cash Balances

While this post has been about how much cash companies return to stockholders, the inverse of whatever is said about cash return can be said about cash retained in companies, which shows up as cash balances. In fact, if you use potential dividend (FCFE) as your measure of cash that can be returned and dividends plus buybacks as your measure of cash that is actually returned, your cash balance at any point in time for a publicly traded firm can be written as:

When companies accumulate large cash balances, it is never by accident but a direct consequence of having held back cash for long periods. So, how much cash do publicly traded companies hold? To answer that question for US companies, I look at a distribution of cash as a percent of firm value (market value of equity + total debt) in the figure below:

Thus, the median company in the United States at the start of 2017 held 2.45% of its value in cash; remember that with the US tax codeâs strictures on foreign income being taxed on repatriation, a significant portion of this cash may be beyond the reach of stockholders, at least for the moment. The median company globally holds 5.50% of value in cash, with small differences across regions with one exception. Japan is the outlier, with the median company holding 22.24% of its value in cash. Expanding the comparison globally, I look at cash as a percent of firm value by country in the picture below:

Link to live map

Note that, as with dividend payout, it is difficult to decide what to make of a large (or a small) cash holding. Thus, large cash balances may provide a buffer against bad times, but they may also indicative of poor corporate governance, where stockholders are powerless while manager accumulate cash.

Conclusion

Since equity is a residual claim, it has never made sense to me that companies commit to paying a fixed dividend every year. I know that this is how dividend policy has been set since the beginning of equity markets, but that reflects the fact that stocks, when first traded, were viewed as bonds with price appreciation, with dividends standing in for coupons. As companies increasingly face global competition and much more uncertainty about future earnings, their reluctance to increase dividend commitments is understandable. If you buy into my characterization of dividends as analogous to getting married and buybacks as the equivalent of hooking up, companies and investors are both choosing to hook up, and who can blame them?

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Datasets

Data 2017 Posts

Data Update 1: The Promise and Perils of Big Data
Data Update 2: The Resilience of US Equities
Data Update 3: Cracking the Currency Code - January 2017
Data Update 4: Country Risk and Pricing, January 2017
Data Update 5: A Taxing Year Ahead?
Data Update 6: The Cost of Capital in January 2017
Data Update 7: Profitability, Excess Returns and Corporate Governance- January 2017
Data Update 8: The Debt Trade off in January 2017
Data Update 9: Dividends and Buybacks in 2017
Data Update 10: A Pricing Update in January 2017

As as sports fan, watching Brady and Belichick win the Super Bowl, Roger Federer triumph at the Australian Open and LeBron James carry the Cleveland Cavaliers to victory over the Warriors, it struck me how we take uncommon brilliance for granted. It is so easy, in the moment, to find fault, as many have, with these superstars and miss how special they are. That was the same reaction that I had as I watched another earnings report from Apple and the usual mix of reactions to it, some ho hum that the company made only $45 billion last year, some relieved that the company was able to post a 3% growth rate in revenues and the usual breast beating from those who found fault with it for not delivering another earth-shaking disruption. Since this is a company that I have valued after every quarterly earnings report since 2010, I thought this would be a good time to both take stock of what the company has managed to do over the last decade and to value it, given where it stands today.

The Cash Machine Revs up

In my last post on dividend payout and cash return globally, I noted that large cash balances don't happen by accident but are a direct result of companies paying out less than they have available as potential dividends or free cash flows to equity, year after year. Since Apple's cash balance almost reached $250 billion in its most recent quarterly report, by far the largest cash balance ever accumulated by a publicly traded company, I decided that the place to start was by looking at how it got to its current level. I started by collecting the operating, debt financing and reinvestment cash flows each year from 2007 to 2016 and computing a free cash flow to equity (or potential dividend) each year.

Starting in 2014, when Apple started to tap into its debt capacity, the company has been able to add to its potential dividends each year. In 2016 alone, Apple generated $93.6 billion in FCFE or potential dividends, an astounding amount, larger that the GDP of half the countries in the world in 2015. Each year, I also looked at how much Apple has returned to stockholders in the form of dividends and stock buybacks.

Note that while Apple took a while to start returning cash, and it needed prompting from David Einhorn and Carl Icahn, it not only initiated dividends in 2013 but has supplemented those dividends with stock buybacks of increasing magnitude each year. In fact, Apple returned $183 billion in cash to stockholders in the last five years, making it, by far, the largest cash-returner in the world over that period.

There are two amazing (at least to me) aspects to this story. The first is that in spite of the immense amounts of cash that Apple has returned each year, its cash balance has increased each year, partly because its operating cash flows are so high and partly because they are being supplemented by debt payments. You can see the cash build up between 2007 and 2016 in the chart below:

Note that while Apple was returning $183 billion in cash between 2013-2016, its cash balance continued to increase, as its cash inflows increased even more. If having a cash spigot that never turns off is a problem, Apple has it, but I am sure that it will not get about as much sympathy from the rest of the world as a supermodel who complains that she cannot put on weight, no matter how much she eats. The other equally surprising feature of this story is that Apple's managers have not felt the urge (yet) to use their huge cash reserves to buy a company, a whole set of companies or even an entire country, a fact that those who like Apple will attribute to the discipline of its management and Apple haters will argue is due to a lack of imagination.

My Apple Valuation History

As many of you who have been reading this blog are aware, I have valued Apple many times before but rather than rehash old history, let me summarize. For Apple, the story that I have been telling about the company for the last five years has been remarkably unchanged. In my July 2012 valuation, where I looked at Apple just after it had become the largest market cap company in the world and had come off perhaps the greatest decade of disruption of any company in history (iTunes, iPod, iPhone and iPad), I concluded that while Apple was one of the great cash machines of all time, its days of disruption were behind it, partly because Steve Jobs was no longer at the helm but mostly because of its size; it is so much more difficult for a $600 billion company to create a significant enough disruption to change the trend lines on earnings, cash flows and value.

So, in my story, I saw Apple continuing to produce cash flows, with low revenue growth and gradually decreasing margins, as the smartphone business became more competitive. I won't make you read all of the posts that I have on Apple, but let me start with a post that I had in August 2015, when I updated the Apple story (and looked at Facebook and Twitter at the same time). The value I estimated for Apple in that post was $130, higher than the stock price of $110 at the time, prompting me to buy the stock. I revisited the story after an earnings report from Apple in February 2016 and compared it to Alphabet. At the time, I valued Apple at about $126 per share, well above the $94/share that it was trading at the time. In May 2016, Carl Icahn, a long time bull on Apple sold his shares, and Warren Buffett, a long time avoider of tech companies, bought shares in the company. In a post at the time, I argued that while these big names entering and exiting the stock may have pricing consequences, I saw no reason to change my story and thus my value, leaving my Apple holdings intact.

Apple's Earnings Report & My Narrative

Last week, Apple released its latest 10Q and in conjunction with its latest 10K (Apple's fiscal year end is in September). It contained a modicum of good news, insofar as there was growth in revenues as opposed to the decline posted in the prior quarter and still-solid profit margins, but the revenue growth was only 3% and the margins are still lower than they used to be. Using the numbers in the most recent report, I took at look at my Apple story and guess what? It looks just like it did last year, a great cash machine, with very slow-growing revenues and declining margins. Using the process that I describe, perhaps in too much detail in my book on narrative and numbers, I converted my story in inputs to my valuation:

Some of you may find my story too cramped , seeing a greater possibility than I do of Apple breaking through into a new, big market (with Apple Pay or the Apple iCar). If you are in that group, please take my structure and make it yours, with a higher growth rate coming from your disruptive story, accompanied by lower margins and higher reinvestment. Others may find this story too optimistic, perhaps seeing a more precipitous fall of profit margins in the smart phone business and a greater tax liability from trapped cash. You too can alter the inputs to your liking and make your own judgment on Apple!

An Updated Valuation of Apple

Once you have a story for a company and convert that story into valuation inputs, the rest of the process becomes just mechanics. In the picture below, I have my February 2017 valuation of Apple.

Download spreadsheet with valuation

Just as my valuation looked too optimistic a year, when the earnings report contained darker news, it may seem too pessimistic this year, after a much sunnier report. That said, it is worth emphasizing how much Apple is on the iPhone roller coaster ride, reporting better earnings in the quarters immediately after a new iPhone is released and much worse earnings in the quarters thereafter. While the market seems to want to go on a ride with Apple on its ups and downs, my fundamental story for Apple has barely shifted in the last few years and my valuations reflect that story stability.

Apple's Price/Value Dynamics

I have taken my share of punishment on investments that have not gone well, with Valeant being a source of continuing pain (which I will return to after its next earnings report). Apple, though, has served me well in the last decade, but even with Apple, I have had extended periods where my faith has been tested. The picture below graphs Apple's stock price from 2010 and 2017 with my valuations shown across time:

I held Apple from 2010 to 2012, as it traded under my estimated value. I sold in April 2012, just before a brief interlude where the price popped above value in June 2012, it reverted back to being under valued until June 2014. After spending a few months as an overvalued stock, the price plummeted in the late summer of 2015, making me a buyer, but it continued to drop until almost April 2016. It's been a good ride since, and much as I want to attribute this to my valuation insights and brilliant timing, I have a sneaking suspicion that luck had just as much or perhaps more to do with it. Now that the stock is fully valued, decision time is fast approaching and I am ready with my sell trigger at $140/share, the outer end of the range that I have for Apple's value today.

Conclusion

Apple is the greatest corporate cash machine in history and it is fully deserving of its market value. Its history as a disruptive force has led some investors to expect Apple to continue what it did a decade ago and come up with new products for new markets. Those expectations, though, don't factor in the reality that as a much larger player with huge profit margins, Apple is more likely to be disrupted than be disruptor. Until investors learn to live with the company, as it exists now and not the company that they wish would exist in its place, there will continue to be mood swings in the market translating into the ebbs and flows of its stock price, and I hope to take advantage of them.

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My book

Narrative and Numbers (Columbia University Press)

Prior Blog Posts on Apple

Spreadsheets

Five years ago, when my daughter asked me whether I had Snapchat installed on my phone, my response was âSnapwhat?". In the weeks following, she managed to convince the rest of us in the family to install the app on our phones, if for no other reason than to admire her photo taking skills. At the time, what made the app stand out was the impermanence of the photos that you shared with your circle, since they disappeared a few seconds after you viewed them, a big selling point for sharers lacking impulse control. In 2013, when Facebook offered $3 billion to buy Snap, it was a clear indication that the new company was making inroads in the social media market, especially with teenagers. When Evan Spiegel and Bobby Murphy, Snap's founders, turned down the offer, I am sure that there were many who viewed them as insane, since Snap had trouble attracting advertisers to its platform and little in revenues, at the time. After all, what advertiser wants advertisements to disappear seconds after you see them? Needless to say, as the IPO nears and it looks like the company will be priced at $20 billion or more, it looks like Snap's founders will have the last laugh!

Snap: A Camera Company?

The Snap prospectus leads off with these words: Snap Inc. is a camera company. But is it? When I think of camera companies, I think of Eastman Kodak, Polaroid and the Japanese players (Fuji, Pentax) as the old guard, under assault as they face disruption from smartphone cameras, and companies like GoPro as the new entrants in the space, struggling to convert sales to profits. I don't think that this is the company that Snap aspires to keep and since it does not sell cameras or make money on photos, it is difficult to see it fitting in. If you define business in terms of how a company plans to make money, I would argue that Snap is an advertising business, albeit one in the online or digital space. I do know that Snap has hardware that it is selling in the form of Spectacles, but at least at the moment, the glasses seem to be designed to get users to stay in the Snap ecosystem for longer and see more ads.

So, why does Snap present itself as a camera company? I think that the answer lies in the social media business, as it stands today, and how entrants either carve a niche for themselves or get labeled as me-too companies. Facebook, notwithstanding the additions of Instagram and WhatsApp, is fundamentally a platform for posting to friends, LinkedIn is a your place for business networking, Twitter is where you go if you want to reach lots of people quickly with short messages or news and Snap, as I see it, is trying to position itself as the social media platform built around visual images (photos and video). The question of whether this positioning will work, especially given Facebook's investments in Instagram and new entrants into the market, is central to what value you will attach to Snap.

The Online Advertising Business

If you classify Snap as an online advertising company, the next step in the process becomes simple: identifying the total market for online advertising, the players in that market and what place you would give Snap in this market. Letâs start with some basic data on the online advertising market.

It is a big market, growing and tilting to mobile: The digital online advertising market is growing, mostly at the expense of conventional advertising (newspapers, TV, billboards) etc. You can see this in the graph below, where I plot total advertising expenditures each year and the portion that is online advertising for 2011-2016 and with forecasted values for 2017-2019. In 2016, the digital ad market generated revenues globally of close to $200 billion, up from about $100 billion in 2012, and these revenues are expected to climb to over $300 billion in 2020. As a percent of total ad spending of $660 billion in 2016, digital advertising accounted for about 30% and is expected to account for almost 40% in 2020. The mobile portion of digital advertising is also increasing, claiming from about 3.45% of digital ad spending to about half of all ad spending in 2016, with the expectation that it will account for almost two thirds of all digital advertising in 2020.
Sources: Multiple
With two giant players: There are two dominant players in the market, Google with its search engine and Facebook with its social media platforms. These two companies together control about 43% of the overall market, as you can see in this pie chart:
If you are a small player in the US market, the even scarier statistic is that these two giants are taking an even larger percentage of new online advertising than their historical share. In 2015 and 2016, for instance, Google and Facebook accounted for about two-thirds of the growth in the digital ad market. Put simply, these two companies are big and getting bigger and relentlessly aggressive about going after smaller competitors.

In a post in August 2015, I argued that the size of the online advertising market may be leading both entrepreneurs and investors to over estimate their chances of both growing revenues and delivering profits, leading to what I termed the big market delusion. As Snap adds its name to the mix, that concern only gets larger, since it is not clear that the market is big enough or growing fast enough to accommodate the expectations of investors in the many companies in the space.

Snap: Possible Story Lines

To value a young company, especially one like Snap, you have to have a vision for what you see as success for the company, since there is little history for you to draw on and there are so many divergent paths that the company can follow, as it ages. That might sound really subjective, but without it, you are at the mercy of historical data that is both scarce and noisy or of metrics (like users and user intensity) that can lead you to misleading valuations.

Link to my book

That is, of course, another shameless plug for my book on narrative and numbers, and if you have heard it before or have no interest in reading it, I apologize and let's go on. To get perspective on Snap, letâs start by comparing it to three social media companies, Facebook, Twitter and LinkedIn and to Google, the old player in the mix, at the time of their initial public offerings. The table below summarizes key numbers at the time of their IPOs, with a comparison to Snap's numbers.

	Google	LinkedIn	Facebook	Twitter	Snap
IPO date	19-Aug-04	19-May-11	18-May-12	7-Nov-13	NA
Revenues	$1,466	$161	$3,711	$449	$405
Operating Income	$326	$13	$1,756	$(93)	$(521)
Net Income	$143	$2	$668	$(99)	$(515)
Number of Users	NA	80.6	845	218	161
User minutes per day (January 2017)	50 (Includes YouTube)	NA	50	2	25
Market Capitalization on offering date	$23,000	$9,000	$81,000	$18,000	?
Link to Prospectus (from IPO date)	Link	Link	Link	Link	Link

At the time of its IPO, Snap has less revenues than any of its peer group, other than LinkedIn, and is losing more money than any of them. Before you view this is a death knell for Snap, one reason for Snapâs big losses is that unlike its competitors, Snap pay for server space as it acquires new users, thus pushing up its operating expenses (and pushing down capital investment in servers). There is one other dimension where Snap measures up more favorably against at least two of the other companies: its users are spending more time on its platform that they were either on Twitter and LinkedIn and it ranks second only to Facebook on this dimension.

The more important question that you face with Snap, then, is which of these companies it will emulate in its post IPO year. The table below provides the contrasting rather by looking at the years since the IPO for each company.

Google and Facebook stand out as success stories, Google because it has maintained high revenue growth for almost a decade with very good profit margins and Facebook doing even better on both dimensions (higher growth in the earlier years and even higher margins). The least successful company in this mix is Twitter which has seen revenue growth that has trailed expectations and has been unable to unlock the secret to monetizing its user base, as it continues to post losses. Linkedin falls in the middle, with solid revenue growth for its first four years and some profits, but its margins are not only small but showed no signs of improvement from year to year. Now that it has been acquired by Microsoft, it will be interesting to see if the combination translates into better growth and margins.

My Snap Story & Valuation

To value Snap, I built my story by looking at what its founders have said about the company, how its structured and the strengths and weaknesses of its platform, at least as I see them. As a consequence, here is what I see the company evolving.

Snap will remain focused on online advertising: I believe that Snap's revenues will continue to come entirely or predominantly from advertising. Thus, the payoff to Spectacles or any other hardware offered by the company will be in more advertising for the company.
Marketing to younger, tech-savvy users: Snap's platform, with its emphasis on the visual and the temporary, will remain more attractive to younger users. Rather than dilute the platform to go after the bigger market, Snap will create offerings to increase its hold on the youth segment of the market.
Source: The Economist
With an emphasis on user intensity than users: Snap's prospectus and public utterances by its founders emphasize user intensity more than the number of users, in contrast to earlier social media companies. This emphasis is backed up by the company's actions: the new features that it has added, like stories and geofilters, seem designed more to increase how much time users spend in the app than on getting new users. Some of that shift in emphasis reflects changes in how investors perceive social media companies, perhaps sobered by Twitter's failure to convert large user numbers into profits, and some of it is in Snap's business model, where adding users is not costless (since it has to pay for server space).

These assumptions, in turn, drive my forecasts of revenues, margins and reinvestment. In my story, I don't see Snap reaching revenues of the magnitude delivered by Google and Facebook, the two big market players in the game, settling instead for smaller revenues. If Snap is able to hold on to its target market (young, tech savvy and visually inclined) and keep its users engaged, I think Snap has a chance of delivering high operating profit margins, perhaps not of the magnitude of Facebook today (45% margin) but close to that of Google (25% margin). Finally, its reinvestment will take the form of acquisition of technology and server space to sustain its user base, but by not trying to be the next Facebook, it will not have to over reach. Is there substantial risk that the story may not work out the way I expect it to? Of course! While I will give Snap a cost of capital of close to 10% (and in the 85th percentile of US companies), reflective of its online advertising business, I will also assume that there remains a non-trivial chance (10%) that the company will not make it. The picture below captures my story and the valuation inputs that emerge from it:

To complete the valuation, there are two other details that relate to the IPO.

Share count: For an IPO, share count can be tricky, and especially so for a young tech company with multiple claims on equity in the form of options and restricted stock issues. Looking through the prospectus and adding up the shares outstanding on all three classes of shares, including shares set aside for restricted stock issues and assorted purposes, I get a total of 1,243.10 million shares outstanding in the company. In addition, I estimate that there are 44.90 million options outstanding in the company, with an average exercise price of $2.33 and an assumed maturity of 3 years.
IPO Proceeds: This is a factor specific to IPOs and reflect the fact that cash is raised by the company on the offering date. If that cash is retained by the company, it adds to the value of the company (a version of post-money valuation). In the case of Snap, it is estimated that roughly $3 billion in cash from the offering that will be held by the company, to cover costs like the $2 billion that Snap has contracted to pay Google for cloud space for the next five years.

These valuation inputs become the basis for my valuation and yield a value of $14.4 billion for the equity (and you can download the spreadsheet at this link).

Download spreadsheet

Allowing for the uncertainty inherent in my estimates, I also computed probability distribution for three key inputs, revenue growth, operating margin and cost of capital, and my value for Snap's equity is in the distribution below:

Snap Simulation Details

Assuming that my share count is right, my value per share is about $11 per share. As you can see though, as is the case with almost any young company where the narrative can take you in other directions, there is a wide range around my expectations, with the lowest value being less than zero and the highest value pushing above $66 billion ($50/share). The median value is $13.3 billion and the average is $14.9 billion; one attractive feature to investors is that there is potential for breakout values (optionality) that exceed $30 billion.

The numbers at the high end of the spectrum reflect a pathway for Snap that I call the Facebook Light story, where it emerges as a serious contender to Facebook in terms of time that users spend on its platform, but with a smaller user base. That leads to revenues of close to $25 billion by 2027, an operating margin of 40% for the company and a value for the equity of $48 billion.
The numbers at the other end of the spectrum capture a darker version of the story, that I label Twitter Redux, where user growth slows, user intensity comes under stress and advertising lags expectations. In this variant, Snap will have trouble getting pushing revenue growth past 35%, settling for about $4 billion in revenues in 2027, is able to improve its margin to only 10% in steady state, yielding a value of equity of about $4 billion.

As I learned the painful way with my Twitter experiences, the quality of the management at a young company can play a significant role in how the story evolves. I am impressed with both the poise that Snap's founders are showing in their public appearances and the story that they are telling about the company, though I am disappointed that they have followed the Google/Facebook path and consolidated control in the company by creating shares with different voting rights. I know that is in keeping with the tech sector's founder worship and paranoia about "short term" investors , but my advice, unsolicited and perhaps unwelcome, is that Snap's founders should trust markets more. After all, if you welcome me to invest me in your company and I do, you should want my input as well, right?

The Pricing Contrast
As I finish this post, I notice this news story from this morning that suggests that bankers have arrived at an offering price, yielding a pricing for the company of $18.5 billion to $21.5 billion for the company, about $4 billion above my estimate. So, how do I explain the difference between my valuation and this pricing? First, I have never felt the urge to explain what other people pay for a stock, since it is a free market and investors make their own judgments. Second, and this is keeping with a theme that I have promoted repeatedly in my posts, bankers don't value companies; they price them! If you are missing the contrast between value and price, you are welcome to read this piece that I have on the topic, but simply put, your job in pricing is not to assess the fair value of a company but to decide what investors will pay for the company today. The former is determined by cash flows, growth and risk, i.e., the inputs that I have grappled with in my story and valuation, and the latter is set by what investors are paying for other companies in the space. After all, if investors are willing to attach a pricing of $12 billion to Twitter, a social media company seeming incapable of translating potential to profits, and Microsoft is paying $26 billion for LinkedIn, another social media company whose grasp exceeded its reach, why should they not pay $20 billion for Snap, a company with vastly greater user engagement than either LinkedIn or Twitter? With pricing, everything is relative and Snap may be a bargain at $20 billion to a trader.

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Link to book

Narrative and Numbers: The Value of Stories in Business

Attachments

In nine posts, stretched out over almost two months, I have tried to describe how companies around the world make investments, finance them and decide how much cash to return to shareholders. Along the way, I have argued that a preponderance of publicly traded companies, across all regions, have trouble generating returns on the capital invested in them that exceeds the cost of capital. I have also presented evidence that there are entire sectors and regions that are characterized by financing and dividend policies that can be best described as dysfunctional, reflecting management inertia or ineptitude. The bottom line is that there are a lot more bad companies with bad managers than good companies with good ones in the public market place. In this, the last of my posts, I want to draw a distinction between good companies and good investments, arguing that a good company can often be a bad investment and a bad company can just as easily be a good investment. I am also going argue that not all good companies are well managed and that many bad companies have competent management.

Good Businesses, Managers and investments
Investment advice often blurs the line between good companies, good management and good investments, using the argument that for a company to be a "good" company, it has to have good management, and if a company has good management, it should be a good investment. That is not true, but to see why, we have to be explicit about what makes for a good company, how we determine that it has good management and finally, the ingredients for a good investment.

Good and Bad Companies
There are various criteria that get used to determine whether a company is a good one, but every one of them comes with a catch. You could start with profitability, arguing that a company that generates more in profits is better than generates less, but that statement may not be true if the company is capital intensive (and the profits generated are small relative to the capital invested) and/or a risky business, where you need to make a higher return to just break even. You could look at growth, but growth, as I noted in this post, can be good, bad or neutral for value and a company can have high growth, while destroying value. The best measure of corporate quality, for me, is a high excess return, i.e., a return on capital that is vastly higher than its cost of capital, though I have noted my caveats about how return on capital is measured. Reproducing my cross sectional distribution of excess returns across all global companies in January 2017, here is what I get:

Blog Post on Excess Returns

To the extent that you want the capital that you have invested in companies to generate excess returns, you could argue that the good companies in this graph as the value creators and the bad ones are the value destroyers. At least in 2017, there were a lot more value destroyers (19,960) than value creators (10,947) listed globally!

Good and Bad Management

If a company generates returns greater (less) than its opportunity cost (cost of capital), can we safely conclude that it is a well (badly) managed company? Not really! The âgoodnessâ or âbadnessâ of a company might just reflect the ageing of the company, its endowed barriers to entry or macro factors (exchange rate movements, country risk or commodity price volatility). The essence of good management is being realistic about where a company is in the life cycle and adapting decision making to reflect reality. If the value of a business is determined by its investment decisions (where it invests scarce resources), financing decisions (the amount and type of debt utilized) and dividend decisions (how much cash to return and in what form to the owners of the business), good management will try to optimize these decisions at their company. For a young growth company, this will translate into making investments that deliver growth and not over using debt or paying much in dividends. As the company matures, good management will shift to playing defense, protecting brand name and franchise value from competitive assault, using more debt and returning more cash to stockholders. At a declining company, the essence of âgoodâ management is to not just avoid taking more investments in a bad business, but to extricate the company from its existing investments and to return cash to the business owners. My way of capturing the quality of a management is to value a company twice, once with the management in place (status quo) and once with new (and "optimal" management).

I term the difference between the optimal value and the status quo value to be the âvalue of controlâ but I would argue it is also just as much a measure of management quality, with the value of control shrinking towards zero for âgoodâ managers and increasing for bad ones.

Good and Bad Investments
Now that we have working definitions of good companies and good managers, letâs think about good investments. For a company to be a good investment, you have to bring price into consideration. After all, the greatest company in the world with superb managers can be a bad investment, if it is priced too high. Conversely, the worst company in the management with inept management may be a good investment is the price is low enough. In investing therefore, the comparison is between the value that you attach to a company, given its fundamentals, and the price at which it trades.

As you can see at the bottom, investing becomes a search for mismatches, where the market's assessment of a company (and it's management) quality is out of sync with reality.

Screening for Mismatches
If you take the last section to heart, you can see why picking stocks to invest in by looking at only one side of the price/value divide can lead you astray. Thus, if your investment strategy is to buy low PE stocks, you may end up with stocks that look cheap but are not good investments, if these are companies that deserve to be cheap (because they have made awful investments, borrowed too much money or adopted cash return policies that destroy value). Conversely, if your investment strategy is focused on finding good companies (strong moats, low risk), you can easily end up with bad investments, if the price already more than reflects these good qualities. In effect, to be a successful investor, you have to find market mismatches, a very good company in terms of business and management that is being priced as a bad company will be your âbuyâ. With that mission in hand, letâs consider how you can use multiples in screening, using the PE ratio to illustrate the process. To start, here is what we will do. Starting with a very basic dividend discount model, you can back out the fundamentals drivers of the PE ratio:

Now what? This equation links PE to three variables, growth, risk (through the cost of equity) and the quality of growth (in the payout ratio or return on equity). Plugging in values for these variables into this equation, you will quickly find that companies that have low growth, high risk and abysmally low returns on equity should trade at low PE ratios and those with higher growth, lower risk and sold returns on equity, should trade at high PE ratios. If you are looking to screen for good investments, you therefore need to find stocks with low PE, high growth, a low cost of equity and a high return on equity. Using this approach, I list multiples and the screening mismatches that characterize cheap and expensive companies.

Multiple	Cheap Company	Expensive Company
PE	Low PE, High growth, Low Equity Risk, High Payout	High PE, Low growth, High Equity Risk, Low Payout
PEG	Low PEG, Low Growth, Low Equity Risk, High Payout	High PEG, High Growth, High Equity Risk, Low Payout
PBV	Low PBV, High Growth, Low Equity Risk, High ROE	High PBV, Low Growth, High Equity Risk, Low ROE
EV/Invested Capital	Low EV/IC, High Growth, Low Operating Risk, High ROIC	High EV/IC, Low Growth, High Operating Risk, Low ROIC
EV/Sales	Low EV/Sales, High Growth, Low Operating Risk, High Operating Margin	High EV/Sales, Low Growth, High Operating Risk, High Operating Margin
EV/EBITDA	Low EV/EBITDA, High Growth, Low Operating Risk, Low Tax Rate	High EV/EBITDA, Low Growth, High Operating Risk, High Tax Rate

If you are wondering about the contrast between equity risk and operating risk, the answer is simple. Operating risk reflects the risk of the businesses that you operate in, whereas equity risk reflects operating risk magnified by financial leverage; the former is measured with the cost of capital whereas the latter is captured in the cost of equity.

The Bottom Line

If the length of this post has led you to completely forget what the point of it was, I donât blame you. So, let me summarize. Separating good companies from bad ones is easy, determining whether companies are well or badly managed is slightly more complicated but defining which companies are good investments is the biggest challenge. Good companies bring strong competitive advantages to a growing market and their results (high margins, high returns on capital) reflect these advantages. In well managed companies, the investing, financing and dividend decisions reflect what will maximize value for the company, thus allowing for the possibility that you can have good companies that are sub-optimally managed and bad companies that are well managed. Good investments require that you be able to buy at a price that is less than the value of the company, given its business and management.

Thus, you can have good companies become bad investments, if they trade at too high a price, and bad companies become good investments, at a low enough price. Given a choice, I would like to buy great companies with great managers at a great price, but greatness on all fronts is hard to find. So. Iâll settle for a more pragmatic end game. At the right price, I will buy a company in a bad business, run by indifferent managers. At the wrong price, I will avoid even superstar companies. At the risk of over simplifying, here is my buy/sell template:

Company's Business	Company's Managers	Company Pricing	Investment Decision
Good (Strong competitive advantages, Growing market)	Good (Optimize investment, financing, dividend decisions)	Good (Price < Value)	Emphatic Buy
Good (Strong competitive advantages, Growing market)	Bad (Sub-optimal investment, financing, dividend decisions)	Good (Price < Value)	Buy & hope for management change
Bad (No competitive advantages, Stagnant or shrinking market)	Good (Optimize investment, financing, dividend decisions)	Good (Price < Value)	Buy & hope that management does not change
Bad (No competitive advantages, Stagnant or shrinking market)	Bad (Sub-optimal investment, financing, dividend decisions)	Good (Price < Value)	Buy, hope for management change & pray company survives
Good (Strong competitive advantages, Growing market)	Good (Optimize investment, financing, dividend decisions)	Bad (Price > Value)	Admire, but don't buy
Good (Strong competitive advantages, Growing market)	Bad (Sub-optimal investment, financing, dividend decisions)	Bad (Price > Value)	Wait for management change
Bad (No competitive advantages, Stagnant or shrinking market)	Good (Optimize investment, financing, dividend decisions)	Bad (Price > Value)	Sell
Bad (No competitive advantages, Stagnant or shrinking market)	Bad (Sub-optimal investment, financing, dividend decisions)	Bad (Price > Value)	Emphatic Sell

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