Saturday, April 11, 2015

The Small Cap Premium: Where is the beef?

For decades, analysts and investor have bought into the idea of a small cap premium, i.e., that stocks with low market capitalizations can be expected to earn higher returns than stocks with higher market capitalizations. For investors, this has led to the pursuit of small cap stocks and funds for their portfolios, and for analysts, it has translated into the addition of "small cap" premiums of between 3-5% to traditional model-based expected returns, for companies that they classify as small cap. While I understand the origins of the practice, I question the adjustment for three reasons: 
  1. On closer scrutiny, the historical data, which has been used as the basis of the argument, is yielding more ambiguous results and leading us to question the original judgment that there is a small cap premium.
  2. The forward-looking risk premiums, where we look at the market pricing of stocks to get a measure of what investors are demanding as expected returns, are yielding no premiums for small cap stocks. 
  3. If the justification is intuitive, i.e., that smaller firms are riskier than larger firms, much of that additional risk is either diversifiable, better adjusted for in the expected cash flows (instead of the discount rate) or double counted.
The small cap premium is a testimonial to the power of inertia in corporate finance and valuation, where once a practice becomes established, it becomes difficult to challenge, even if the original reasons for it have long since disappeared.

The Basis
The first studies that uncovered the phenomenon of the small cap premium came out in the 1970s. They broke companies down into deciles, based on market capitalization, and found that companies in the lowest decile earned higher returns, after adjusting for conventional risk measures, than companies in the highest decile. I updated those studies through the end of 2014, and the small cap premium seems intact (at least at first sight). In summary, looking at returns from 1926 to 2014, the smallest cap stocks (in the lowest decile) earned 4.33% more than the market, after adjusting for risk.
Source: Ken French's online data
This is the strongest (and perhaps) only evidence for a small cap premium and it is reproduced in data services that try to estimate historical risk premiums (Ibbotson, Duff and Phelps etc.).  This historical premium has become the foundation for both valuation and investment practice. In valuation, analysts have referenced this table to estimate a small cap premium (4-5%) that they then add to the required return from conventional risk and return models to estimate discount rates. For instance, in the conventional capital asset pricing model, it plays out as follows:
Expected Return = Risk free rate + Beta * Equity Risk Premium + Small Cap Premium
That discount rate is used to estimate the value of future cash flows, and not surprisingly, the use of a small cap premium lowers the value of smaller companies. 

In investing, it has been used as a weapon both for and against active investing. Those who favor active investing have pointed to the small cap premium as a justification for their activity, and during the periods of history when small cap companies outperformed the market, it did make them look like heroes but it quickly gave rise to a counterforce, where performance measurement services (like Morningstar) started incorporating portfolio tilts, comparing small cap funds against small cap indices. Since almost all of the "excess returns" disappeared on this comparison, it was only a matter of time before index funds entered the arena, creating small-cap index funds for investors who wanted to claim the premium, without paying large management fees.

The Problem with the Historical Premium
In the decades since the original small cap premium study, the data on stocks has become richer and deeper, allowing us to take a closer look at the phenomenon. There are some serious questions that can be raised about whether the premium exists and if so, what exactly it is measuring:
  1. Trend lines and Time Periods: Small cap stocks have earned higher returns than large cap stocks between 1928 and 2014 but the premium has been volatile over history, disappearing for decades and reappearing again. While the premium was strong prior to 1980, it seems to have dissipated since 1981. One reason may be that the small cap premium studies drew attention and investor money to small cap stocks, and in the process led to a repricing of these stocks. Another is that the small cap premium is a side effect of larger macroeconomic variables (inflation, real growth etc.) and that the behavior of those variables has changed since 1980.
    Source: Ken French's online data
  2. Microcap, not small cap premium: Even over the long time period that provides the strongest support for existence of a small cap premium, one study finds that removing stocks with less than $5 million in market cap causes the small firm effect to vanish. In effect, what you have is microcap premium, isolated in the smallest of stocks, not just small stocks.
  3. Standard Error: Historical equity returns are noisy and any estimates of risk premium from that data will reflect the noise in the form of large standard errors on estimates. I have made this point about the overall historical equity risk premium but it becomes magnified when you dice and slice historical data into sub-classes. The table below lists standard errors in excess returns by decile class and reinforce the notion that the small cap premium is fragile, barely making the threshold for statistical significance over the entire period.
    Source: Ken French's online data
  4. The January Effect: One of the most puzzling aspects of the small cap premium is that almost all of it is earned in one month of the year, January, and removing that month makes it disappear. So what? If your argument for the small cap premium is that small cap stocks are riskier, you now have the onus of explaining why that risk shows up only in the first month of every year. 
    Source: Ken French's online data
  5. Weaker globally: The small cap premium seems to be smaller in non-US markets than in US markets and is non-existent in some. In contrast, the value effect (where low price to book stocks outperform the market) is strong globally. 
  6. Proxy for other factors: A host of papers argue that the bulk or all of the small size effect can be attributed to a liquidity effect and that putting in a proxy for illiquidity makes the size effect disappear or diminishes it.
  7. Works only with market cap: Finally, you can take issue with the use of a market-priced based measure of size in a study of returns. Others have tried other non-price size measures such as income or revenues but there seems to be no size effect in those variables. 
A recent working paper by Asness, Frazini, Moskowitz and Pedersen tries to resurrect the size effect, but accomplishes it only by removing the subset of small companies that they classify as "low quality" or "junk". While the results are interesting and can be used by active small-cap fund managers as a justification for their activity, they are in no way a basis for adding a small cap premium to every small company, and asking analysts to add it on only for small, high quality companies is problematic. In summary, if the only justification that you can offer for the addition of a small cap premium to your discount rate is the historical risk premium, you are on thin ice. 


Market-Implied Small Cap Premium

If the historical data ceases to support the use of a historical risk premium, can we then draw on intuition and argue that since small companies tend to be riskier (or we perceive them to be), investors must require higher return when they invest in them? You can, but the onus is then on you to back up that intuition. In fact, you can check to see whether investors are demanding a forward looking "small cap" premium, by looking at how they price small as opposed to large companies, and backing out what investors are demanding as expected returns. Put simply, if small cap stocks are viewed by investors as riskier and that risk is being priced in, you should expect to see, other things remaining equal, higher expected returns on small cap stocks than large cap stocks.

As some of you are aware, I compute a forward-looking equity premium for the S&P 500 at the start of each year, backing out the number from the current level of the index and expected cash flows. On January 1, 2015, this is what I found:

In effect, to the extent that my base year cash flows are reasonable and my expected growth rate reflects market expectations, the expected return on large cap stocks on January 1, 2015 was 7.95% in the US (yielding an overall equity risk premium of 5.78% on that day).

To get a measure of the forward-looking small cap premium, I computed the expected return implied in the S&P 600 Small Cap Index, using the same approach that I used for S&P 500. In spite of using a higher expected earnings growth for small cap stocks, the expected return that I estimate is only 7.61%:


In effect, the market is attaching a smaller expected return for small cap stocks than large ones, stories and intuition notwithstanding. 

I am not surprised that the market does not seem to buy into the small cap premiums that academics and practitioners are so attached to. After all, if the proponents of small cap premiums are right, bundling together small companies into a larger company should instantly generate a bonus, since you are replacing the much higher required returns of smaller companies with the lower expected return of a larger one. In fact, small companies should disappear from the market.

The Illiquidity Fig Leaf
Looking at the data, the only argument left, as I see it, for the use of the small cap premium is as a premium for illiquidity, and even on that basis, it fails at one of these four levels:
  1. If illiquidity is your bogey man in valuation, why use market capitalization as a stand-in for it? Market capitalization and illiquidity don't always go hand in hand, since there are small, liquid companies and large, illiquid ones in the market. Four decades ago, your excuse would have been that the data on illiquidity was either inaccessible or unavailable and that market capitalization was the best proxy you could find for illiquidity. That is no longer the case and there are studies that categorize companies based on measures of illiquidity (bid ask spread, trading volume) and find an "liquidity premium" for illiquid companies.
  2. If illiquidity is what you are adjusting for in the small cap premium, why is it a constant across companies, buyers and time? Even if your defense is that the small cap premium is an imperfect (but reasonable) measure of the illiquidity premium, it is unreasonable to expect it to be the same for every company. Thus, even if you are valuing just privately owned businesses (where illiquidity is a clear and present danger), that illiquidity should be greater in some businesses than in others and the illiquidity (or small cap) premium should be larger for the former than the latter. Furthermore, the premium you add to the discount rate should be higher in some periods (during market crises and liquidity crunches) than others and for some buyers (cash poor, impatient) than others (patient, cash rich).
  3. Even if you can argue that illiquidity is your rationale for the small cap premium and that it is the same across companies, why is it not changing over the time horizon of your valuation (and especially in your terminal value)? In any valuation, you assume through your company's cash flows and growth rates that your company will change over time and it is inconsistent (with your own narrative) to lock in an illiquidity premium into your discount rate that does not change as your company does. Thus, if you are using a 30% expected growth rate on your company, your "small" company is getting bigger (at least according to your estimates) and presumably more liquid over time. Should your illiquidity premium therefore not follow your own reasoning and decrease over time?
  4. If your argument is that size is a good proxy for illiquidity, that all small companies are equally illiquid and that that illiquidity does not change as you make them bigger, why are you reducing your end value by an illiquidity discount? This question is directed at private company appraisers who routinely use small cap premiums to increase discount rates and  also reduce the end (DCF) value by 25% or more, because of illiquidity. You can show me data to back up your discount (I have seen restricted stock and IPO studies) but none of them can justify the double counting of illiquidity in valuation.
Why are we slow to give up on the “small cap” premium?

It is true that the small cap premium is established practice at many appraisal firms, investment banks and companies. Given the shaky base on which it is built and how much that base has been chipped away in the last two decades, you would think that analysts would reconsider their use of small cap premiums, but there are three powerful forces that keep it in play.
  1. Intuition: Analysts and investors not only start of with the presumption that the discount rates for small companies should be higher than large companies, but also have a “number’ in mind. When risk and return models deliver a much lower number, the urge to add to it to make it "more reasonable" is almost unstoppable. Consequently, an analyst who arrives at an 8% cost of equity for a small company feels much more comfortable after adding a 5% small cap premium. It is entirely possible that you are an idiot savant with the uncanny capacity to assess the right discount rate for companies, but if that is the case, why go through this charade of using risk and return models and adding premiums to get to your "intuited" discount rate? For most of us, gut feeling and instinct are not good guides to estimating discount rates and here is why. Not all risk is meant for the discount rate, with some risk (like management skills) being diversifiable (and thus lessened in portfolios) and other risks (like risk of failure or regulatory approval) better reflected in probabilities an expected cash flow. A discount rate cannot and is not meant to be a receptacle for all your hopes and fears, a number that you can tweak until your get to your comfort zone. 
  2. Inertia (institutional and individual): The strongest force in corporate finance practice is inertia, where much of what companies, investors and analysts do reflects past practice. The same is true in the use of the small cap premium, where a generation of analysts has been brought up to believe (by valuation handbooks and teaching) that it is the right adjustment to make and now do it by rote. That inertia is reinforced in the legal arena (where many valuations end up, either as part of business or tax disputes) by the legal system’s respect for precedence and general practice. You may view this as harsh, but I believe that you will have an easier time defending the use of a bad, widely used practice of long standing in court than you would arguing for an innovative better practice.
  3. Bias: My experiences with many analysts who use small cap premiums suggest to me that one motive is to get a “lower” value". Why would they want a lower value? First, in accounting and tax valuation, the client that you are doing the valuation for might be made better off with a lower value than a higher one. Consequently, you will do everything you can to pump up the discount rate with the small cap premium being only one of the many premiums that you use to “build up” your cost of capital. Second, there seems to be a (misplaced) belief that it is better to arrive at too low a value than one that is too high. If you buy into this “conservative” valuation approach, you will view adding a small cap premium as costless, since even it does not exist, all you have done is arrived at “too low” a value. At the risk of bringing up the memories of statistics classes past, there is always a cost. While “over estimating” discount rates reduces type 1 errors (that you will buy an over valued stock), it comes at the expense of type 2 errors (that you will hold off on buying an under valued stock).
A Requiem for the Small Cap Premium?

I have never used a small cap premium, when valuing a company and I don’t plan to start now. Needless to say, I am often asked to justify my non-use of a premium and here are my reasons. First, I am not convinced by either the historical data or by current market behavior that a small cap premium exists. Second, I do believe that small cap companies are more exposed to some risks than large cap companies but there are other more effective devices to bring these risks into valuation. If it is that they are capital constrained (i.e., that it is more difficult for small companies to raise new capital), I will limit their reinvestment and expected growth (thus lowering value). If it is that they have a greater chance of failure, I will estimate a probability of failure and reflect that in my expected value (as I do in my standard DCF model). If it is illiquidity that is your concern, it is worth recognizing that one size will not fit all and that the effect on value will vary across investors and across time and will be better captured in a  discount on value.

To illustrate how distorted this debate has become, note that those who routinely add small cap premiums to their discount rates are not put to the same test of justifying its use. So, at the risk of opening analysts up to uncomfortable questions, here are some questions that you should pose to anyone who is using a small cap premium (and that includes yourself):
  1. What is your justification for using a small cap premium? If the defense is pointing to history (or a data table in a service), it is paper thin, since that historical premium defense seems to have more holes in it than Swiss cheese. If it is intuitive, i.e., that small companies are riskier and markets must see them as such, I don't see the basis for the intuition, since the implied costs of equity for small companies are no higher than those of large companies. If the argument is that everyone does it, I am sorry but just because something is established practice does not make it right. 
  2. What are the additional risks that you see in small companies that you don't see in large ones? I am sure that you can come up with a laundry list that is a mile long, but most of the risks on the list either don't belong in the discount rate (either because they are diversifiable or because they are discrete risks) or can be captured through probability estimates. If it is illiquidity that you are concerned about, see the section on illiquidity above for my response.
If you are investors, here are the lessons I draw from looking at the data. If you are following a strategy of buying small cap stocks, expecting to be rewarded with a premium for just doing that, you will be disappointed. Even the most favorable papers on the small cap premium suggest that you have to add refinements, with some suggesting that these refinements should screen out the least liquid, riskiest small cap stocks and others arguing for value characteristics (stable earnings, high returns on equity & capital, solid growth). I do think that there is a glimmer of hope in the recent research that the payoff to looking for under valued stocks may be greater with small companies, partly because they are more likely to be overlooked, but it will take more work on your part and it won't be easy!

Data sets

Spreadsheets

Friday, April 3, 2015

Dealing with Low Interest rates: Investing and Corporate Finance Lessons

A few months ago, I tagged along with my wife and daughter as they went on a tour of the Federal Reserve Building in downtown New York. While the highlight of the tour is that you get to see large stacks of US dollars in the basement of the building, I considered making myself persona non grata with my immediate family by asking the guide (a very nice Fed employee) about the location of the interest rate room. That, of course, is the room where Janet Yellen comes in every morning and sets interest rates. I am sure that you can visualize her pulling the levers that sets T.Bond rates, mortgage rates and corporate rates and the power that comes with that act. If that sounds over the top, that is the impression you are left with, not only from reading news stories about central banks, but also from opinion pieces from some economists and investment advisors. I know that investors, analysts and CFOs are all rendered off balance by low interest rates, but I will argue that the techniques that they use to compensate are more likely to get them in trouble than solve their problems.

The what: Interest rates are at historic lows across the globe
There is little to debate. Interest rates are lower than they have been in a generation and you can see it in this graph of the US 10-year treasury bond rate going back several decades:
US 10-year T.Bond rates at the end of each year
But it is not just the US dollar where low interest rates prevail, as illustrated by the German government 10-year Euro bond rate, the Japanese government 10-year Yen bond rate and the Swiss Government 10-year Swiss franc rate trend lines:
Ten-year Government Bond Rates: End of each period
In fact, on the Swiss Franc, the 10-year bond rates rates have not just dropped but have hit zero and kept going to -0.09%, leading to the almost unfathomable phenomenon of negative interest rates on long term borrowing. A world where savers have to pay banks to keep their savings and borrowers are paid money to borrow turns everything that we have learned in economics on its head and it is therefore no surprise that even seasoned investors and analysts are unsure of what to do next.

The why: Its not just central banks
Why are interest rates so low? I know that the conventional wisdom is that it is central bank policy that has driven them there, but is that true? To answer that question, I decided to do go back to basics.

The Fundamentals
While market interest rates are set by demand and supply, as they are in any other market, there are fundamentals that determine that rate. In particular, the interest rate on an investment with no default risk (a guaranteed or risk free investment) can be written as the sum of two components:
Interest rate on a guaranteed investment = Expected inflation + Expected real interest rate
This is the simplified version of the classic Fisher equation and it is true by construction. In fact, many analysts use it to decompose market interest rates; thus if the US treasury bond rate is at 2.00% and expected inflation is 1.25%, the real interest rate is backed out at 0.75%. In the long term, I would argue that a real interest rate has to be backed up by a real growth rate in the economy. After all, you cannot deliver a 2% real interest rate in an economy growing at only 1% a year in the long term, though you can get short term deviations between the two numbers. Thus, in the long term, the interest rate on a guaranteed investment can be rewritten as:
Interest rate on a guaranteed investment = Expected inflation + Expected real growth rate
How well does this simplistic equation hold up in practice? Testing it is hard, especially when you can observe only actual inflation and real growth but not expected inflation and real growth. However, we also know that expectations for inflation and real growth are driven, for better or worse, by recent history; thus expected inflation increases after periods of high inflation and decreases after periods of low inflation, thus making actual inflation and real growth reasonable proxies for expected values. The final number we need to test out this relationship is the interest rate on a guaranteed investment, and we use the US 10-year treasury bond rate as the stand in for that number, with the concession that the last 5 years have shaken investor faith in the guarantee.
Source: FRED (Federal Reserve in St. Louis)
Even if you take issue with my proxies for expected inflation (the actual inflation rate in the US each year, as measured by the CPI), real growth (the real growth rate in US GDP and the interest rate on a guaranteed investment, the graph sends a powerful message that risk free rates are driven by inflation and real growth expectations. If expected inflation is low and real growth is anemic, as has been the case since 2008, interest rates will be low as well and they would have been low, with or without central bank intervention.

The Central Bank Effect
Do central banks have influence over interest rates? Of course, but the mechanisms they use are surprisingly limited. In the United States, the only rate that the Fed sets is the Fed Funds rate, a rate at which banks can borrow or lend money overnight. Thus, if the Fed wants to raise (lower) interest rates, it has historically hiked (cut) the Fed Funds rate and hoped that bond markets (treasury and corporate) respond accordinly. One way to measure the effect of Fed action is to compute the difference between the actual US treasury bond rate each period and the “intrinsic” treasury bond rate (computed as the sum of inflation and real GDP growth that year):
Source: FRED
Note that the Fed Funds rate hit zero in 2009 and has stayed there for the last five years, effectively eliminating it as a tool for controlling rates. Perhaps driven by desperation and partly motivated by the savior complex, the Fed has turned to a relatively unused tool in its arsenal and bought large quantities of US treasury bond in the market for the last five years, the much-talked about Quantitative Easing (QE). While it is true that T.Bond rates have stayed below intrinsic interest rates over the last 5 years, the effect of QE (at least to my eyes) seems to modest.

As the economy comes back to life, all eyes have turned towards Janet Yellen and the Fed and Fed-watching has become the central focus for many investors. While that is understandable, it is worth remembering that in today's economic environment, with low inflation and real growth, the removal of the Fed prop will not cause interest rates to pop to 5% or 6% . In fact, based upon the numbers in the most recent year, the intrinsic interest rate is 3.08% and if the central banking props disappear, that would be the number towards which US treasury bond rates move.

Given the evidence to the contrary, it is puzzling that investors continue to hold on to the belief that central banks set interest rates and can change them on whim, but I think that the delusion serves both sides (investors and central banks) well. Investors, whipsawed by market and economic forces that are uncontrollable, feel comfort in attributing the power to set interest rates to central banks. It also allows investors to attribute every phenomenon that they have trouble explaining to central banking machinations and interest rates that are either "too high" or "too low". Quantitative Easing in all its forms has proved to be absolutely indispensable as a bogey man that you can blame for the failure of active investing, the rise and fall of gold, and bubbles of every type. Central banks, which are really more akin to the Wizard of Oz, in their powers, than Masters of the Universe, are glad to play along, since their power comes from the illusion that they have real power.

The Crisis Effect
There is another factor at play that may be more powerful than central banks, at least over short periods, and that is the perception of a crisis. Whatever the origins or form of the crisis, investors respond with fear, and flee to safety. That "flight to quality" often manifests itself in declining interest rates on bonds issued by governments that are perceived as "higher quality", and may push those rates well below intrinsic levels. Looking at the chart where we outline the gap between the T.Bond rate and its intrinsic value, the quarter where we saw the US 10-year treasury bond rate drop the most, relative to its intrinsic value, was the last quarter of 2008, where the crisis in financial markets led to a rush into US treasuries. That translated into a precipitous drop in treasury rates across the board, with the 10-year rate dropping from 3.66% on September 12, 2008,  to 2.2% at the end of 2008, and the T. Bill rate declining from 1.62% to 0.02% over the same period.
Source: FRED- Constant Maturity Rates on 3-month and 10-year treasuries
One of the few constants over the last six years has been that we lurch from one crisis to another, with local problems quickly going global. While there are some who may argue that this is a passing phase, I believe that this is part and parcel of globalization, one of the negatives that need to get offset against its positives. As economies and markets become increasingly interconnected, I think that the recurring crisis mode will be a permanent feature of market. One consequence of that may be that market interest rates on government bonds will settle below their intrinsic values, a permanent "crisis discount", with or without central banking intervention.

The Interest Rate Effect 
The level of interest rates matter for all of us, as investors, consumers and businesses. For investors, interest rates drive expected returns on investments of all types through a very simple process:
Expected Return (r) = Interest rate on a risk free investment + Risk Premium
That expected return then determines what we will be willing to pay for a risky asset, with lower expected returns translating into higher prices. For businesses, these expected return becomes hurdle rates (costs of equity and capital) that they use to decide not only whether and where they should invest their money but plays a role in how much they borrow and how much to return to stockholders (as dividends or buybacks).

If the risk free rate drops and you leave the risk premiums and cash flows unchanged, the effect on value is unambiguously positive, with value rising as risk free rates drop. Thus, if you have a business that has $100 million in expected cash flows next year, with a growth rate of 4% a year in perpetuity and an equity risk premium of 4%, changing the risk free rate from 6% down to 2% will have profound effects on value. It is this value effect that has led some to blame the Fed for creating a "stock market bubble" and analysts across the world to wonder whether they should be doing something to counter that effect, in their search for intrinsic value.

While the mathematics that show the link between value and interest rates is simple, it is misleading because it does not tell the whole story. As I argued in the last section, interest rate movements, up or down, almost never happen in a  vacuum. The same forces that cause significant shifts in interest rates affect other inputs into the valuation and those changes can reduce or even reverse the interest rate effect:

To illustrate, the 2008 crisis that caused the T.Bond rate to plummet in the last quarter of the year also caused equity risk premiums to surge from 4.37% on September 12, 2008 to 6.43% on December 31, 2008. In the figure below, I back out the expected return on stocks and the equity risk premium from the index level each day and the expected future cash flows for each month from September 2008 to April 2015. Note that the cost of equity for the median US company rose in the last quarter of 2008, even as risk free rates declined. 
Source: Damodaran.com (Implied ERP)

The expected return on equities has stayed surprisingly stable (around 8%) for much of the last 5 years, nullifying the impact of lower interest rates and casting doubt on the "Fed Bubble" story. As the crisis has receded, investor concerns have shifted to real growth, as the developed market economies (US, Euro Zone and Japan) have been slow to recover and inflation has not only stayed tame but turned to deflation in the EU and Japan. Thus, looking just at lower interest rates and making judgments on value misses the big picture.

Reacting to Low Interest Rates
Given that low interest rates have shaken up the equation, what should we do to respond? Broadly speaking, there are four responses to low interest rates:
  1. Normalize: In valuation, it is common practice to replace unusual numbers (earnings, capital expenditures and working capital) with more normalized values. Some analysts extend that lesson to risk free rates, replacing today’s “too low” rates with more normalized values. While I understand the impulse, I think it is dangerous for three reasons. The first is that "normal" is a subjective judgment. I argue, only half in jest, that you can tell how long an analyst has been in markets by looking at what he or she views as a normal riskfree rate, since normal requires a time frame and the longer that time frame, the higher normal interest rates become. The second is that if you decide to normalize the risk free rate, you have no choice but to normalize all your other macro variables as well. Consequently, you have to replace today’s equity risk premium with the premium that fits best with your normalized risk free rate and do the same with growth rates. Put differently, if you want to act like it is 2007, 1997 or 1987, when estimating the risk free rate, your risk premiums and growth rates will have to be adjusted accordingly. The third is that unlike earnings, cash flows or other company-specific variables, where you are free to make your judgment calls, the risk free rate is what you can earn on your money today, if you don’t invest in risky assets. Consequently, if you do your valuation, using a normalized risk free rate of 4% (instead of the actual risk free rate of 2%), and decide that stocks are over valued, I wish you the very best of luck putting your money in that normalized treasury bond, since it exists only in your estimation.
  2. Go intrinsic: The second option, if you believe that the market interest rate on government bonds is being skewed by central banking action to abnormally low or high levels is to replace that rate with an intrinsic interest rate. If you buy into my estimates for inflation and real growth in the last section, that would translate into using a 3.08% “intrinsic” US treasury bond rate. To preserve consistency, you should continue to use the same inflation rate and real growth as your basis for forecasting earnings and cash flow growth in your company and going the distance, you should estimate an intrinsic ERP, perhaps tying it to fundamentals.
  3. Leave it alone: The third option is to leave the risk free rate at its current levels, notwithstanding concerns that you might have about it being too low or too high. To keep your valuation in balance, though, your other inputs have to be consistent with that risk free rate. That implies using forward-looking prices for risk (equity risk premiums and default spreads) that reflect the market today and economy-wide growth and inflation rates that are consistent with the current risk free rate. Thus, if you decide to use 0.21% as the risk free rate in Euros, the combination of inflation and real growth rates you have to assume in the Euro economy have to combine to be less than 0.21%. Doing so does not imply that you believe that nominal growth will be that low but ensures that you are making the same assumptions about nominal growth in the numerator (cash flows) as you are in the denominator (through the risk free rate).
  4. Leave it alone (for now) : The last option is to leave the risk free rate at current levels for now but adjust the rate in the future (perhaps at the end of your high growth period) to your normalized or intrinsic levels. Here again, the key is to make sure that your other valuation inputs are consistent with your assumption. Thus, for the period you use the current risk free rate, you have to use equity risk premiums, growth rates and inflation expectations consistent with that rate, and as you adjust the risk free rate to its normalized or intrinsic levels, you have to adjust the rest of your inputs.
To illustrate the four options when it comes to risk free rates, I value a hypothetical average-risk company with an expected cash flow of $100 million next year, using all four options. The inputs I use for the company under each option are summarized below, with the value computed in the last column:

The four choices yield different values but the most interesting finding is that the value that I get with the “leave alone” option is lower than the values that I obtain with my other options. Consequently, those who argue that we need to replace the current risk free rate with more normalized versions because it is the “conservative” path may be ending up with estimates of value that are too high (not too low).

While I prefer the "leave alone" option, I think that the other approaches are defensible, if your macro views are significantly different from mine. The danger, as I see it, comes when you mismatch your assumptions, with two of the most egregious examples listed below:


Note that while each input into these mismatched valuations may be defensible, it is the combination that skews the value vastly downwards or upwards. If you use  or do intrinsic valuations, checking for input consistency is more critical than ever before.
 
Bottom line
So, what is the bottom line? Like almost everyone else, I find myself in uncharted territory, with interest rates approaching zero in many currencies and like most others, I feel the urge to "fix" the problem. There are three broad lessons that I take away from looking at the data.

  1. Central banks tweak interest rates. They don’t set them. Consequently, I am going to spend less time worrying about what Janet Yellen does in the interest rate room and more on the fundamentals that drive rates. I will also grant short shrift to anyone who uses central banks as either an excuse or looks to them as a savior in their investing.
  2. When risk free rates are abnormally low or high, it is because there are other components in the market that are abnormal, and I am not sure what is normal. For investors in the US and Europe who yearn for the normality of decades past, I am afraid that normal is not returning. We have to recalibrate our assumptions about what is normal (for interest rates, risk premiums, inflation and economic growth) and pay less heed to rules of thumb that were developed for another market (US in the 1900s) and another time.
  3. As investors, we can rage against interest rates being too low but it is what it is. We have to value companies in the markets that we are in, not the markets we wished we were in. 
Data to download

Friday, March 27, 2015

The GM Buyback: Beyond the Hysteria!

Here is a script for a movie about the evils of stock buybacks, with the following players. The victim is an well-managed company in a business with significant growth opportunities and profit potential. The company has delivered products that its customers love, while paying its workers top-notch wages & benefits and invested heavily and prudently in its future. The villain is an activist investor, and for added color, let's make him greedy, short term and a speculator. In the story, he forces the  company to redirect money it would have spent on more great investments to buy back stock. The white knight can be a regulator, the government or a noble investor (make him/her successful, wealthy and socially conscious, i.e., Buffett-like) who rides in and saves the hapless company from the villain and stops the buyback. The story ends happily, with the defeat and humiliation of the activist investor, and the moral  is that stock buybacks are evil (and need to be stopped). As you read some of the over-the-top responses to GM's buyback, such as this one, you would not be alone in thinking that you were reading about the mythical company in the movie. But given GM's history and current standing, do you really want to make it the basis for your case against buybacks? 

GM is not well managed now, and has not been so, for a long time
Is GM a well managed firm? The answer might have been yes in 1925, when GM was the auto industry's disruptor, challenging Ford, the established leader in the business at the time. It would have definitely been affirmative in 1945, when Alfred Sloan’s strategy of letting GM's many brands operate independently won the automobile market race for GM, and it was the largest and most profitable automobile company in the world. It may have still been positive in 1965, when GM was on top of the world, a key driver of the US economy and US equity markets. 

By 1985, the bloom was off the rose, as GM (and other US auto makers) were late to respond to the oil crisis and had let Japanese car makers not only take market share but also the mantle of reliability and innovation. In 2005, GM remained the largest car maker in the world, but it was in serious financial trouble, with an ageing customer base and huge legacy costs, from promises made to employees in good times. In 2008, the problems came to a head during the financial crisis, as GM had trouble  making its debt payments, attracted government attention and a bailout. As part of the bargain, equity investors in GM were wiped out and lenders had to accept significantly less than they had been promised. If the objective of the bailout was GM's survival, it worked, as the company was able to reverse a steep drop in revenues (in 2008) and start making profits again. That recovery came at a significant cost to taxpayers, who lost $11.2 billion in the bailout.

GM was able to go public again in 2010 and since it is the new version of the company that is buying back stock and it would be unfair to burden the incumbents with the mistakes of prior managers, I focus the bulk of my attention on how well the management of this new incarnation has done in its stewardship of the company. The picture below captures the new GM's evolution as a company over the last five years:
The New GM: Investment, Revenues and Profits from 2010-2014
GM has been reinvesting actively since it went public again in 2010, adding almost $25.5 billion in investments (in plant, equipment and working capital) to it base. The good news is that revenues have gone up, albeit at an anemic rate (3.56% a year between 2010 and 2014) but the bad news is that these increasing revenues have been accompanied by declining profitability. Even in 2011, the best of the five years in terms of profitability, GM's return on capital of 6.86% lagged its cost of capital.

Does this imply that the existing management of GM is not up to the task? Not necessarily, since they were dealt a bad hand to begin with. They were saddled with brand names that evoke nothing but nostalgia, a cost structure that put them at a disadvantage (still) relative to other automobile companies and a legacy of past mistakes. At the same time, there is little that this management has done that can be viewed as visionary or exciting in the years since the IPO (in 2010). In fact, the end game for the new GM seems to be the same one that doomed the older version of the company: a fixation on market share (and number of cars sold), a desire to be all things to all people and an inability to admit mistakes. In the last two years, GM’s fumbling response to its "ignition switch" problem seem to have pushed GM back into the  “troubled automobile company” category again. The bottom line is that the best case that you can make for GM's current management is that it is a "blah" management,  keeping the company alive and mildly profitable. The worst case is that this is still a management stuck in a time warp and in denial over how much the automobile business has changed in the last few decades and that it is only a matter of time before the government is faced again with the question of whether GM is too "big to fail".

The auto business a bad one, with disruption around the corner
My measure of the quality of a business is simple and perhaps even simplistic. In a good business, the companies collectively in that business should be able to generate a return on capital that exceeds the cost of capital (based on the risk in the business) and the “best” companies in the business should earn significantly more than their costs of capital. The auto business fails both tests. In my most recent data update in January 2015, I computed the aggregated return on capital at auto companies globally (about 125+) in the trailing 12 months leading into January and arrived at 6.47%, a little more than 1% below the collective cost of capital of 7.53% that I computed for auto companies. Lest this be viewed as an outlier, the table below summarizes the aggregated return on capital and cost of capital for companies in the global automobile business each year for the last ten years:

If you are wondering whether this collective miasma is caused by the laggards in the group, I isolated the twenty largest automobile companies in the world in 2015 and estimated profitability and leverage numbers for them in March 2015:


Note that, if anything, the return on capital (which is based on operating income and invested book capital) is biased towards making a company look better than it really is (largely because accountants are quick to write off mistakes), but even on this measure, only one of the ten largest companies (Audi) earned a return on capital that is higher than its cost of capital in 2014. In fact, mass-market auto companies like Volkswagen, Toyota and Ford have abysmal returns on capital, suggesting that the club that GM is trying to rejoin is not an attractive one. The typically large automobile company in 2015 is a highly levered behemoth, which struggles to earn enough to cover its cost of capital in a market with anemic revenue growth. 

Given that the business model for automobile companies seems to have broken down, it should come as no surprise that the business is being targeted for disruption. While I have argued against the pricing premiums that the market is paying for Tesla, it is undeniable that it's entry into the market has speeded up the investments that other auto makers are making in electric cars. Given their track record of poor profitability, I would not be surprised if the next big disruption of this market comes from companies in healthier businesses and that will bring more pressures on existing automobile companies. If there is a light at the end of this tunnel for incumbent automobile companies, I don't see it.

A GM Buyback: Value Effects?
In an earlier post on buybacks, I used a picture to illustrate how a buyback may affect value and I think that picture can help in assessing the GM buyback:


Looking at the picture, I can see why activist investors were pushing GM to return more cash. It is a middling company in a bad business, where even the very best companies struggle to earn their costs of capital. Since it is possible that I am blinded by my stockholder-focus, I considered what GM could have done with the $5 billion, instead of buying back stock.
  1. Invest the cash: GM could have invested the cash back into the auto business, but given the state of the business and the returns generated by players in it, this effectively throws good money after bad. In fact, looking at how little the $25.5 billion in reinvestment has done for GM in the last five years, I think a stronger argument can be made that they would perhaps have been better off not investing that money and returning it to stockholders as well. 
  2. Hold the cash or pay down debt: Auto companies are natural cash hoarders, arguing that as cyclical companies, they need the cash to survive the next recession or downturn. In fact, that argument seems to have added resonance at a company like GM, which has just come out of a near-death experience with default. At the risk of sounding heartless, I would counter that survival for the sake of survival makes little sense. A corporation is a legal entity and there is a corporate life cycle, a time to be born, a time to grow, a time to harvest and finally a time to shut down. If your response is that you cannot let that happen to an American icon like GM, there was a time when Xerox was so dominant in its business that it's corporate name  became synonymous with its product (copies) and Eastman Kodak was the 'camera' company, but pining for those days will not bring them back. The actions driven by the "too big to fail" ethos have cost the taxpayers $11 billion already. Do you really want to do this a second time around with GM?
  3. Return the cash to other stakeholders (labor, the government): You can argue that my view of buybacks fails to take into account the interests of other stakeholders in the firm, its workers, its suppliers and perhaps even the government. It is true that GM could use the $5 billion to give its workers raises and replenish their pensions. That will be good news for those workers, but doing so will only push down the measly return on capital that GM is currently earning, make future access to capital (debt or equity) even more difficult, and set the company on the pathway to financial devastation.
The Root of the Disagreement
There are "corporate finance" reasons for arguing against buybacks in some companies and they include concerns about damaging growth potential (where buybacks come at the expensive of good investments), about timing (when companies buy back shares when prices are high, rather than low) , or managerial self-interest (if buybacks are being used to push up stock prices ahead of option exercises). Since it is almost impossible to use any of these with GM, those arguing against a GM buyback are really against all stock buybacks, no matter who does them. While I don't agree with these critics, I think that there is a simple way to understand the vehemence of their opposition and it is rooted in ideology and philosophy, not finance.  If you believe, as I do, that as a publicly traded automobile company, GM's mission is to take capital from investors and generate higher returns for them that they could have made elsewhere, in investments of equivalent risk, with that money, you can justify the buyback and perhaps even argue that it should be more. If you believe that GM's mission as a car company is to build more auto plants and produce more cars, hire more workers and pay them premium wages and save the cities of Flint and Detroit from bankruptcy (as a side benefit), this or any buyback is a bad idea. In fact, it is not just buybacks that you should have a problem with but any cash returned (including dividends) to investors, since that cash could have been used more productively (with your definition of productivity) by the company. It is also extremely unlikely that you will find anything that I have to say about buybacks to be persuasive since we have a philosophical divide that cannot be bridged. So, its best that we agree to disagree!

Past posts on buybacks

  1. Stock Buybacks: What is happening and why (January 25, 2011)
  2. Buybacks and Stock Prices: Good news or bad news (January 25, 2011)
  3. The Shift to Buybacks: Implications for Investors (February 1, 2011)
  4. Stock Buybacks: They are big, they are back and they scare some people (September 22, 2014)



Friday, March 20, 2015

Illiquidity and Bubbles in Private Share Markets: Testing Mark Cuban's thesis!

It looks like Alibaba is investing $200 million in Snapchat, translating (at least according to deal watchers) into a value of $15 billion for Snapchat,  a mind-boggling number for a company that has been struggling to find ways to convert its popularity with some users (like my daughter) into revenues. While we can debate whether extrapolating from a small VC investment to a total value for a company make sense, there are two trends that are incontestable. The first is that estimated values have been climbing at exponential rates for companies like Uber, Airbnb and Snapchat. In venture capital lingo, the number of unicorns is climbing to the point where the name (which suggests unique or unusual) no longer fits. The second is that these companies seem to be in no hurry to go public, leaving the trading in the private sharemarket space. These rising valuations in private markets led Mark Cuban to declare last week that this "tech bubble" was worse (and will end much more badly) than the last one (with dot-com stocks). In the article, Cuban makes four assertions: (1) There is a tech bubble; (2) A large portion of the tech bubble is in the private share market which is less liquid than the public markets; (3) The bubble will be larger and burst more violently because of the absence of liquidity; and (4) This bubble is worse than the dot-com bubble, though it not clear on what dimension and from whose perspective. In his trademark fashion, Cuban ends his article with a provocative questions,  "If stock in a company is worth what somebody will pay for it, what is the stock of a company worth when there is no place to sell it ?" I like Mark Cuban but I think that he is wrong on all four counts.

This is not a tech bubble
In my last post, I took issue with the widespread view that the rise in stock prices from the depths of 2008 has been largely due to tech companies using a simple statistic: the proportion of overall equity market capitalization in the United States coming from tech stocks. Unlike the 1990s, when tech companies climbed from single digits in 1990 to almost 30% of the overall market capitalization by the end of 1999, tech stocks collectively have stayed at about 20% of the overall market.

Tech stocks in S&P 500
There are other indicators that also support the argument that this is not a tech bubble, since a bubble occurs when market prices disconnect from fundamentals. Unlike the 1990s, the market capitalization of technology companies in 2014 is backed up by operating numbers that are commensurate with value. In the figure below, I compare tech companies to non-tech companies on market values (enterprise and equity) as well as on operating statistics such as revenues, EBITDAR&D, EBITDA, operating income and net income, across the entire US market (not just the S&P 500):
Tech vs Non-tech companies in US market (Source: Cap IQ)
One measure of whether a sector is in a bubble is if it accounts for a much larger share of overall market value than it delivers in revenues, earnings and cash flows. In February 2015, tech companies account for about 13.84% of overall enterprise value and 19.94% of market capitalization and they hold their own on almost every operating metric. While tech companies generate only 11% of overall revenues, they account for 19.99% of EBITDA+R&D, 17.93% of operating income and 16.46% of EBITDA, all much higher than tech's 13.84% share of enterprise value, and 18.65% of net income, close to the 19.94% of overall market capitalization. On the cash flow measure, tech firms account for almost 29% of all cash flows (dividends and buybacks) returned to investors, much higher than their share of market capitalization. To provide a contrast, in 1999, at the peak of the dot-com bubble, tech firms accounted for 30% of overall market capitalization but delivered less than 10% of net income and dividends & buybacks. That was a bubble!

Note, though, that this is not an argument against a market bubble but one specifically against a collective tech bubble. If you believe that there is a bubble (and there are reasonable people who do), it is either a market-wide bubble or one in a specific segment of the tech sector, say baby tech or young tech. In my earlier post, I broke tech companies by age and noted that young tech companies are richly priced. If Cuban's assertion is that young tech companies are being over priced, relative to fundamentals and potential earnings/cash flows, it is a more defensible one, and if it is just about young tech companies in the private share market, it may even be a likely one. Even on that front, though, the question remains whether this over pricing is a tech phenomenon or a young company phenomenon.

Illiquidity is a continuum 
Cuban's second point is that this bubble, unlike the one in the nineties, is developing in private share markets, where venture capitalists, institutional investors and private wealth funds buy stakes of private businesses and that these private share markets are less liquid than publicly traded companies. While the notion that public markets are more liquid than private ones is widely held and generally true, illiquidity is a continuum and not all private markets are illiquid and not all publicly traded stocks are liquid. 

The private share market has made strides in the last decade in terms of liquidity. NASDAQ's private market allows wealthy investors to buy and sell positions in privately held businesses and there are other ventures like SecondMarket and Sharespost that allow for some liquidity in these markets. To those who would argue that this liquidity is skin deep and will disappear in the face of a market meltdown, you are probably right, but then again, what makes you believe that public markets are any different? While it is true that some of the big names in technology have high trading volume and deep liquidity, many of the smaller technology companies often have two strikes against them when it comes to liquidity:
  1. Low Float: The proportion of the shares in these companies that are traded is only a small proportion of the overall shares in the company. Just to illustrate, only 10.5% of the shares in Box, the latest technology listing, are traded in the market and small swings in mood in this market can translate into big price changes. Looking across all stocks in the market, the notion that young tech companies tend to have lower floats is backed up by the data:
    Source: S&P Capital IQ (February 2015 data)
  2. Here today, forgotten tomorrow: The young tech space is crowded, and holding investor attention is difficult. Consequently, while many young tech companies go public to high trading volume, that volume drops off in the weeks following as new entrants draw attention to themselves, as evidenced by the trading activity on Box:
    Box: Stock Price & Volume (Yahoo! Finance)
The bottom line is a simple one. The liquidity in tech companies in public markets is uneven and fragile, with heavy trading in high profile stocks, in good times, and around earnings reports masking lack of liquidity, especially when you need it the most.  While Mark Cuban worries about the illiquidity of the private share market, I am not sure that it is any more illiquid than the public markets in dot-com stocks were in the 2000, as the market collapsed.

Liquidity can feed bubbles
Let us, for purposes of argument, accept that Mark Cuban was talking about baby tech companies in the private share market and that he is right about the private share market being less liquid than public markets, is he right in his contention that bubbles get bigger and burst more violently in less liquid markets? Intuitively, his contention makes sense. With start-ups and very young companies, it is a pricing game, not a value game, and that price is set by mood and momentum, rather than fundamentals (cash flows, growth or risk). If you cannot easily trade an asset, it would seem logical to assume that any shift in mood or momentum in this market will be accentuated. If you bring them together in a private share market, you should have the ingredients for a bigger bubble, right?

My intuition leads me down the same path, but if there is a lesson that I have learned from behavioral finance, it is that your intuition is not always right. Some of the most interesting research on bubbles, on what allows them to form, and causes them to burst, comes from experimental economics. Vernon Smith, who won a Nobel Prize in Economics for his role in developing the field, has run a series of experiments where he illustrates that adding liquidity to a market makes bubbles bigger, not smaller. To illustrate, he (with two co-authors) ran a laboratory market, where participants traded a very simple asset (that paid out an expected cash flow of 24 cents every period for 15 periods, giving it a fair value of $3.60 at the start of the trading, dropping by 24 cents each period).  Not only did they find bubbles forming in this market, where the price increased to well above the fair value in the intermediate periods, but that these bubbles were bigger and lasted longer, when they gave traders more money (liquidity) to trade in the market:


In addition, they found that adding liquidity made the bubble bigger earlier in the game. (I strongly recommend this paper to anyone interested in bubbles, because they also explored the effects of adding price limits (like futures markets do), short sales restrictions and experience.) Extrapolating from one experimental study may be dangerous, but if this study holds true, the fact that the private share market is less liquid than a public market may be a check on the market's exuberance, and especially so for young start-ups. Put differently, if liquidity adds to bubbles, Uber, Airbnb and Snapchat would be trading at even higher prices in a public market than they are in the private share markets today.

If you are struggling with the question of why liquidity adds to market bubbles, let me offer one possible explanation. A market bubble needs a propagating mechanism, a process by which new investors are attracted into the market to keep the price momentum going (on the way up) and existing investors are induced to flee (on the way down). In a public market, the most effective propagating mechanism is an observable market price, as increases in the price draw investors in and price declines chase them out. If you add, to this phenomenon, the ease with which we can monitor market prices on our online devices (rather than wait until the next morning or call our brokers, as we had to, a few decades ago) and access to financial news channels (CNBC, Bloomberg and Fox Business News, to name just the US channels) which expound and analyze these price changes, it is no surprise to me that bubbles have steeper upsides and downsides today than they used to. In a private market, we hear about Uber, Airbnb and Snapchat's valuations only when venture capitalists invest in them and our inability to trade on these valuations may be a restraint on their rising. 

A big bubble is not necessarily a bad one
The final component of Mark Cuban's thesis (though I believe that the first three are flawed) is that this bubble is "worse" than prior bubbles. But what is it that makes one bubble worse than another? To me, the cost of a bubble is not whether those invested in the bubble lose money but whether others who are not invested in the bubble are forced to bear some costs when the bubble bursts. It is that spillover effect on other players that we loosely call systemic risk and it is the magnitude of these systemic costs which made the 2007-08 banking bubble so costly.

With this framework in mind, is this young (baby) tech bubble more dangerous than the one in the late nineties? I don't see why. If the bubble bursts, the immediate losers are the wealthy investors (VCs, private equity investors, and private banking clients) who partake in the private share market. Not only can they afford the losses, but perhaps they need a sobering reminder of why they should not let their greed get ahead of their common sense. In a public market collapse, there will be far more small investors who are hurt, and though they deserve the same wake-up call as wealthier investors, they may less equipped to deal with the losses. This could change if institutions that have no business playing in the private share market (like university endowments and public pension funds) decide to invest big amounts in it and screw it up big time.

It is true that there will be side costs, as there are in any bubble. First, when a bubble bursts, the lenders/banks that lent money to companies in the bubble will feel the pain (which does not bother me) and then pass it on to taxpayers (which does). Since young tech companies are lightly levered, these costs are likely to be small.  Second, the bursting of a bubble can have consequences for governments that collect tax revenues from these companies (corporate tax), their employees  (income tax) and investors (dividends & capital gains taxes). Again, since young tech companies are money losers, the vast majority of employees settle for deferred compensation and investors in private markets don't cash out quickly, the tax revenue loss will be contained. Third, every burst bubble carries consequences for the real estate in the region (of the bubble). So, yes, the Bay Area will see a drop in real estate value, and is that a bad thing? I don't think so, since anyone in that area, who is not part of the tech boom, has been reduced to living in cardboard boxes. Finally, I believe that the collapse in the private share market, if it happens, will follow a collapse of young tech companies in the public markets (Facebook, Twitter, Box, Linkedin et al.), which I will take as an indication that it is public markets that lead the bubble, not private markets. 

If this is a bubble, I don't see why its bursting is any more consequential or painful than the implosion of the dot-com bubble. There will undoubtedly be books written by people who claimed to see it coming (perhaps Mark Cuban is vying for a front spot), warnings from the Merchants of Doom (you know who they are) pointing out that this is what happens when greed runs its course and there will be government/market/regulatory action (almost all of it bad, and most of it ineffective) to stop something like this from happening again. So, don't be surprised to see curbs on private share markets or on institutions investing in these markets, as if those curbs will stop the next bubble from occurring. 

Bottom line
Mark Cuban's entry into the ranks of the very rich was greased by the 1990s dot-com boom where he built a business of little value, but sold at the right time . Since that is how you win at the pricing game, I tip my hat to him. For him to point fingers at other people who are playing exactly the same game and accuse them of greed and short-sightedness takes a lot of chutzpah. In fact, Cuban's assertion about this being a worse bubble than the dot-com bubble gives us some insight into one very self-serving way to classify bubbles into good and bad ones. A good bubble is one where you are making money of the excesses and a bad one is one where other people are making money (or more money than you are) from the over pricing. If Cuban is serious about staying out of bubbles, he should look at the largest investment in his portfolio, which is in a market where prices have soared, good sense has been abandoned and there is very little liquidity. In a market where the Los Angeles Clippers are priced at $2 billion and the Atlanta Hawks could fetch a billion, the Dallas Mavericks should go for more, right?

Thursday, February 26, 2015

The Aging of the Tech Sector: The Pricing Divergence of Young and Old Tech Companies

As the NASDAQ approaches historic highs, Apple’s market cap exceeds that of the Bovespa (the Brazilian equity index) and young social media companies like Snapchat have nosebleed valuations, there is talk of a tech bubble again. It is human nature to group or classify individuals or entities and assign common characteristics to the group and we tend to do the same, when investing. Specifically, we categorize stocks into sectors or groups and assume that many or most stocks in each group share commonalities. Thus, we assume that utility stocks have little growth and pay large dividends and commodity and cyclical stocks have volatile earnings largely because of macroeconomic factors. With “tech” stocks, the common characteristics that come to mind for many investors are high growth, high risk and low cash payout. While that would have been true for the typical tech stock in the 1980s, is it still true? More specifically, what does the typical tech company look like, how is it priced and is its pricing put it in a bubble? As I hope to argue in the section below, the answers depend upon which segment of the tech sector you look at.

A Short History of Tech Stocks
My first foray into investing was in the early 1980s, as the market started its long bull market run that lasted for almost two decades. In 1981, the technology stocks in the market were mainframe computer manufacturers, led by IBM and a group of smaller companies lumped together as the seven dwarves (Burroughs, Univac, NCR, Honeywell etc.). Not only were they collectively a small proportion of the entire market, but of the list of top ten companies, in market capitalization terms, in 1981, only one (IBM) could have been categorized as a technology stock (though GE had a small stake in computer-related businesses then):

During the 1980s, the personal computer revolution created a new wave of technology companies and while IBM fell from grace, companies catering to the PC business such as Microsoft, Compaq and Dell rose up the market cap ranks. By 1991, the top ten stocks still included only one technology company, IBM, and it had slipped in the rankings. However even in 1991, technology stocks remained a small portion of the market, comprising less than 7% of the S&P 500. During the 1990s, the dot-com boom created a surge in technology companies and their valuations, and while the busting of that boom in 2000 caused a reassessment, technology has become a larger piece of the overall market, as evidenced by this graph that describes the breakdown, by sector, for the S&P 500 from 1991 to 2014:

Market Capitalization at the end of each year (S&P Capital IQ)
There are two things to note in this graph. 
  1. The first is that technology as a percentage of the market has remained stable since 2009, which calls into question the notion that technology stocks have powered the bull market of the last five years. 
  2. The second is that technology is now the largest single slice of the equity market in the United States and close to the second largest in the global market. So what? Just as growth becomes more difficult for a company as it gets larger and becomes a larger part of the economy, technology collectively is running into a scaling problem, where its growth rate is converging on the growth rate for the economy. While this convergence is sometimes obscured by the focus on earnings per share growth, the growth rate in revenues at technology companies collectively has been moving towards the growth rate of the economy.
The Diversity of Technology
As technology ages and becomes a larger part of the economy, a second phenomenon is occurring. Companies within the sector are becoming much more heterogeneous not only in the businesses that they operate in, but also in their growth and operating characteristics. To see these differences, let’s start by looking at the sector and its composition in terms of age at the start of 2015. In February 2015, there were 2816 firms that were classified as technology companies, just in the United States, accounting for 31.7% for all publicly traded companies in the US market. Some of these companies have been listed for only a few years but others have been around for decades. Using the year of their founding as the birth year, I estimated the age for each company and came up with the following breakdown of tech stocks, by age:

Age: Number of years from founding of company to 2015
Note that 341 technology companies have been in existence for more than 35 years and an additional 427 firms have been in existence between 25 and 35 years, and they collectively comprise about 41% of the firms that we had founding years available in the database. While being in existence more than 25 years may sound unexceptional, given that there are manufacturing and consumer product companies that have been around a century or longer, tech companies age in dog years, as the life cycles tend to be more intense and compressed. Put differently, IBM may not be as old as Coca Cola in calendar time but it is a corporate Methuselah, in tech years.

The Pricing of Technology
The speedy rise of social media companies like Facebook, Twitter and Linkedin from nothing to large market cap companies, priced richly relative to revenues and earnings, has led some to the conclusion that this rich pricing must be across the entire sector. To see if this is true, I look at common pricing metrics across companies in the technology sector, broken down by age.
Pricing as of February 2015, Trailing 12 month values for earnings and book value
To adjust for the fact that cash holdings at some companies are substantial, I computed a non-cash PE, by netting cash out of the market capitalization and the income from cash holdings from the net income. While it is true that the youngest tech companies look highly priced, the pricing becomes more reasonable, as you look across the age scale. For instance, while the youngest companies in the tech sector trade at 4.34 times revenues (based upon enterprise value), the oldest companies trade at 2.44 times revenues. 

How do tech companies measure up against non-tech companies? After all, any story that is built on the presumption that tech companies are the sources of a market bubble has to backed up by data that indicates that tech companies are over priced relative to the rest of the market. To answer this question, I looked at the youngest (<10 and="" companies="" oldest="" tech="" years="">35 years) relative to the  youngest (<10 and="" companies:="" div="" non-tech="" oldest="" years="">
Based on  February 2015 Pricing & Trailing 12 month numbers: 2807 US technology and  6076 non-technology companies.
The assessment depends upon what part of the technology sector you are focused on. While the youngest tech companies trade at much higher multiples of revenues, earnings and book value than the rest of the market, the oldest tech companies actually look under priced (rather than over priced) relative to both the rest of the market and to the oldest non-tech companies. In fact, even focusing just on the youngest companies, it is interesting that while young tech companies trade at higher multiples of earnings (EBITDA, for instance) than young non-tech companies, the difference is negligible if you add back R&D, an expense that accountants mis-categorize as an operating expense.

Does this mean that you should be selling your young tech companies and buying old tech companies? I am not quite ready to make that leap yet, because the differences in these pricing multiples can be partially or fully explained by differences in fundamentals, i.e., young tech companies may be highly priced because they have high growth and old tech companies may trade at lower multiples because they have more risk and tech companies collectively may differ fundamentally from non-tech companies.

The Fundamentals of Tech Companies
There are three key fundamentals that determine value: the cash flows that you generate from your existing assets, the value generated by expected growth in these cash flows and the risk in these cash flows. Again, rather than look at tech stocks collectively, I will break them down by age and compare them to non-tech stocks.

a. Cash Flows and Profitability
To measure profitability, I looked at two statistics, the percentage of money making companies in each group and the aggregate profit margins (using EBITDA, operating income and net income):


Young technology companies are far more likely to be losing money and have lower profit margins that young non-technology companies, even if you capitalize R&D expenses and restate both operating and net income (which I did). At the other end of the spectrum, old technology companies are much more profitable, both in terms of margins and accounting returns, than old non-technology companies, adding to their investment allure, since they are also priced cheaper than non-technology companies.

b. Growth – Level and Quality
To test the conventional wisdom that technology companies have higher growth potential than non-technology companies, I looked at both past and expected future growth in different operating measures starting with revenues and working down the income statement:


The results are surprising and cut against the conventional wisdom, on most measures of growth. Young non-technology companies have grown both revenues and income faster than young technology companies, though analyst estimates of expected growth in earnings per share remains higher for young tech companies. With old tech companies, the contrast is jarring, with historic growth at anemic levels for technology companies but at much healthier levels for non-tech companies, perhaps explaining some of the lower pricing for the former. It is true, again, that the expected growth in earnings per share is higher at tech companies than non-tech companies, reflecting perhaps an optimistic bias on the part of analysts as well as more active share buyback programs at tech companies.

c. Risk – Financial and Market
Are tech companies riskier than non-tech companies? Again, the conventional wisdom would say they are, but I look at two measures of risk in the table below: standard deviation in stock prices and debt ratios across groups:


I get a split verdict, with much higher volatility in stock prices in tech companies, young and old, than non-tech companies, accompanied by much lower financial leverage at tech companies, again across the board, than non-tech companies. As we noted in the earlier table, young tech companies are more likely to be losing money and that may explain why they borrow less, but I think that the high price volatility has less to do with fundamentals and more to do with the fact the investors in young tech companies are too busy playing the price and momentum game to even think about fundamentals. 

d. Cash Return – Dividends, Buybacks and FCFE
In the final comparison, I look at how much cash is being returned in the form of dividends and buybacks by companies in each group, as well as how much cash is being held back in the company as a percent of overall firm value (in market value terms):
FCFE = Cash left over after taxes, debt payments and reinvestment; Firm value = Market Cap + Total Debt; Cash Return = Dividends + Buybacks - Stock Issues

Note that both young tech and young non-tech companies have raised more new equity than they return in the form of dividends and buybacks, giving them a negative cash return yield. Old tech companies return more cash to stockholders both in dividends and collectively, with buybacks, than old non-tech companies. Finally, notwithstanding the attention paid to Apple's cash balance, old tech companies hold less cash than old non-tech companies do. 

In summary, here is what the numbers are saying. Young technology companies are less profitable, have higher growth, higher price risk and are priced more richly than the young non-tech companies. Old technology companies are more profitable, have less top line growth and are priced more reasonably than old non-tech companies. 

Bottom line
The size of the technology sector and the diversity of companies in the sector makes it difficult to categorize the entire sector. In my view, the data suggests that we should be doing the following:
  1. Truth in labeling: We are far too casual in our classifications of companies as being in technology. In my book, Tesla is an automobile company, Uber is a car service (or transportation) company and The Lending Club is a financial services company, and none of them should be categorized as technology companies. The fact that these firms use technology innovatively or to their advantage cannot be used as justification for treating them as technology companies, since technology is now part and parcel of even the most mundane businesses. Both companies and investors are complicit in this loose labeling, companies because they like the “technology” label, since it seems to release them from the obligation of explaining how much they need to invest to scale up, and investors, because it allows them to pay multiples of revenues or earnings that would be difficult (if not impossible) to justify in the actual businesses that these firms are in.
  2. Age classes: We should start classifying technology companies by age, perhaps in four groups: baby tech (start up), young tech (product/service generating revenues but not profits), middle-aged tech (profits generated on significant revenues) and old tech (low top line growth, though sometimes accompanied by high profitability), without any negative connotations to any of these groupings. If we want to point to mispricing, we should be specific about which group the mispricing is occurring. In this market, for instance, if there is a finger to be pointed towards a group, it is not technology collectively that looks like it is richly priced, but baby and young technology companies. By the same token, if you follow rigid value investing advice, where you are told to stay away from technology on the grounds that it is high growth, high risk and highly priced, that may have been solid advice in 1985 but you will be missing your best “value” opportunities, if you follow it now.
  3. Youth or Sector: When we think of start-ups and young firms, we tend to assume that they are technology-based and that presumption, for the most part, is backed up by the numbers. However, there are start-ups in other businesses as well, and it is worth examining when mispricing occurs, whether it is sector or age-driven. It is true that young social media companies have gone public to rapturous responses over the last few years but Shake Shack, which is definitely not a technology company (unless you can have a virtual burger and an online shake) also saw its stock price double on its offering day and biotechnology companies  had their moment in the limelight in 2014, as well. 
  4. Life Cycle dynamics: I have talked about the corporate life cycles in prior posts and as I have noted in this one, there is evidence that the life cycle for a technology company may be both shorter and more intense than the life cycle for a non-technology company. That has implications for how we value and price these companies. In valuation, we may have to revisit the assumptions we make about long lives (perpetual) and positive growth that we routinely attach in discounted cash flow models to arrive at terminal value, when valuing technology companies, and perhaps replace them with finite period, negative growth terminal value models for fading technologies. In pricing, we should expect to see a much quicker drop off in the multiples of earnings that we are willing to pay, as tech companies age, relative to non-tech companies. I will save that for a future post.
I am under no illusions that this post will change the conversation about technology companies, but it will give me an escape hatch the next time I am asked about whether there is a technology bubble. If nothing else, I can point the questioner to this post and save myself the trouble of saying the same thing over and over again.