The Equity Risk Premium: Applications for Investment Decision-Making

Professor Aswath Damodaran’s opening remarks at CFA Society Chicago’s Equity Risk Premium event on April 2, 2019 at the W Chicago City Center.

Aswath Damodaran, Kerschner Family Chair in Finance Education and a Professor of Finance at New York University Stern School of Business, is well known for his books and articles in the fields of valuation, corporate finance, and investment management, philosophies, and strategies. On April 2, he treated the CFA Society Chicago to a tour de force through the foundations of risk premia, the macroeconomic determinants of equity risk, and how the risk premium can me misused.

Damodaran’s talk was followed by a panel which included himself, Michele Gambera, co-head of Strategic Asset Allocation Modeling at UBS Asset Management, and Bryant Matthews, global director research at HOLT. The panel discussion was moderated by Patricia Halper, CFA, co-chief investment officer at Chicago Equity Partners.

Damodaran pointed out that while the risk-premium is referred to as one number, it contains several various risk factors, such as political and economic risks, information opacity, and liquidity risks. Despite the underlying complexity, a common way to derive the risk premium is from the average volatility of some historical period. This, Damodaran warns, is a dangerous approach. By using historical data you can derive any risk premium you want by using the time horizon of your choosing. When you look at historical averages, you are also searching for a number that nobody has ever experienced. And even if they did, you should not believe that history will simply repeat itself. And even if history did repeat itself, you are still estimating a number with large error margins. In the end, the exercise is just not useful.

Damodaran has done a lot of work determining equity risk premia for different countries and makes his data available on his homepage. His approach is to derive an implied risk premium based on consensus forecasts of earnings and adding country risk premia for different countries. He cautions that there is no pure national premium thanks to our integrated world. Much of S&P earnings, for instance, are derived from abroad, and this must be taken into account.

For a person who has devoted so much time to estimating risk premia, it may come as a surprise that Damodaran thinks people should spend less time on it. His approach is that once you observe the market-implied risk premium, you should use this in your valuation model and devote your attention to estimating cash-flows. Right now, too many people are wasting too much time on valuing companies through finding the perfect risk-premia when cash-flows are ultimately going to determine whether they will get valuations right. Academic finance is another culprit here, which spends too much research time on discount rates.

Ask yourself this, are you working on your model’s risk premia because that is where you have superior knowledge, or because it is your comfort zone?

Damodaran is also critical of the use of the price-to-earnings ratio to assess valuation, since it looks at earnings only for the current period. In the US market the ratio may look high, but the pictures very different for current implied risk premia. Since 2008, risk-free rates have come down while expected stock returns have remained roughly the same. This actually implies a higher risk premium.

 Michele Gambera shares Damodaran’s criticism of historically derived risk premia. He also pointed out that while the risk premium fluctuates a lot, we pretend in our models that it is constant. In effect, Gambera stressed, we are estimating a random-walk variable. A better approach for your valuations is to use a forward-looking covariance matrix with various factor loadings.

Should we therefore throw the historical data out the window? When asked the question, Bryant Matthews of HOLT pointed out that historical data are not all useless in a world where variables tend to mean-revert. But you may need to wait a long time for it to happen.

Is there a small-cap premium? Damodaran pointed out that if you estimate the historical premium since 1981, it is negative, which is clearly fictional. However, Matthews estimated a small cap premium of 0.6%, albeit with a standard error that makes it statistically zero. By slicing the equity market in other ways, he estimates that value stocks tend to have a 3.5% equity premium over growth stocks, while Fama and French’s quality stocks-factor enjoys a 2.1% premium over non-quality stocks.

Matthews has also calculated market implied risk premia for over 70 countries, and found it rising in the US from 0% in 2000 to 4% today. Such estimates, he pointed out, are often counterintuitive for clients. Surely, equities were riskier in 2000 when valuations were high. But precisely because valuations were so high, the implied risk premium, which was part of the discount rate, was low.

Can we make money by investing in high-risk premium stocks? After all, theory tells us returns are the reward for taking risk. Yet as Gambera pointed out, high-volatility stocks tend to be favored by investors in part as a way to leverage up according to the CAPM-models, as is done for instance in risk-parity models. At the same time, pointed out Matthews, low-volatility stocks are generally also high-quality stocks and therefore tend to have high return, despite their historically low risk.

Matthews argued that while profits are high for the US market as a whole, this really applies to only 100 companies. This concentration, he suggested, is due to lax regulations. Damodaran, however, suggested that antitrust measures cannot be relied on to change this fact. They may have been politically attractive in the time of Standard Oil, when that company’s dominated position allowed it to raise prices. The dominant firms of today are offering consumers very low prices. Break them apart and any politician will be met with discontent from voters.

Let us end with some historical perspective from Michele Gambera. Much of the early work on risk premia was made at a time of a very different market structure of industrialized countries. Steel and railroads ruled the day and many of today’s giants were not listed. The likes of Alphabet and Facebook pose new challenges in estimating risk premia. This suggests that now more than ever historical data will be misleading in estimating the risk premium, a modest number that means so much.

Distinguished Speaker Series: Howard Marks, CFA, Oaktree Capital

Howard Marks, CFA, is co-chairman of Oaktree Capital, where he contributes his experience to big-picture decisions relating to investments and corporate direction. He shared his insights on investing and managing the business cycle for the CFA Society Chicago community on February 22, 2019. His presentation, entitled “Investing in a Low-Return World,” touched on some of the big questions investors are asking themselves today: Should we lower our return expectations? And if so, how do we make money in a low-return world?

Marks describes today’s environment as a “low-return, high-risk world.” Prospective returns and safety are hard to come by in the current over-optimistic climate where people have great trust in the future. Combined with higher risk-aversion, such sentiments lead to asset price appreciation, which means lower future returns, without any lower risk.

Let us follow Marks back to basics to consider what lower returns actually mean. Consider the CAPM model, which shows the trade-off between risk and return. As central banks have lowered interest rate, this line has shifted down. For the same level of risk, you now have lower returns, whether you are investing in T-bills or equity. The CAPM model hints at two reasons why taking more risk is no surefire way to higher returns. For one, the downward shift in the CAPM-line means that returns are lower even for such risky ventures like private equity. Secondly, and more fundamentally, the CAPM does not ensure higher return for riskier assets. As Marks explains, if higher returns were guaranteed for these assets, they would not be risky. For risky assets, therefore, while required returns appear to be higher, there is a wide range of possible outcomes that offer no safe way to high returns.

In Marks’ view, the seven worst words are ”too much money chasing too few deals.” This is what we are seeing today, with returns lower across the board. As Marks clarifies in a memo, “too much money” does not mean investors have more money on their hands to invest, but that they are moving resources out of cash, where returns are low, to seek more risky opportunities, and as such, push down required returns on riskier investments.

What, then, is an asset manager to do in this environment? You cannot both position yourself correctly in a heated bull market and be positioned for reversal at the same time. Counting on historical returns being the same in the future is foolish but settling for today’s low returns contradicts the business plan of most organizations. You may not survive in the business if you go all into cash and wait for a better environment.

As an asset manager, argues Marks, you have two jobs, that of asset selection and cycle positioning. You cannot give up on timing when to be aggressive because then you cannot ever be defensive. Cycle positioning does not mean forecasting economic growth for the next year. Marks makes very clear that he does not believe in forecasting. Instead, you need to understand where you are in the relevant cycles, such as the business cycle, credit cycle, and the market psychology cycle. Knowing where you are gets the odds on your side. It does not mean you can predict what will happen tomorrow but it should tell you whether to be more aggressive or more cautious. Marks explains that there are times for aggressiveness and times for caution:

  • When prices are low, pessimism is widespread and investors flee from risk, it is time to be aggressive.
  • When valuations are high, enthusiasm is rampant and investors are risk-tolerant, it is time for caution.

It seems Oaktree’s view is that the current environment is a mixed bag. For the past three years, their mantra has been “move forward but with caution.” This, as Marks explains, means being fully invested while biasing the portfolio towards defense rather than offence.

In addition to getting the cycles on your side, explains Marks, there are opportunities for alpha also in the current environment. Despite low returns overall, there are mispricings to exploit. You do have more and less efficient markets, and with the right set of skills, you can identify them. This is harder than it used to be, when there were more structural and persistent inefficiencies to exploit. Nowadays, most inefficiencies are cyclical, and emerge only once in a while.

In inefficient markets, some investors will earn positive alpha, and some negative alpha, so you should enter these markets only if you think you can be on the right side of the trades. You can do this only if you dare to be a contrarian. Going this rout is risky and costly but it is the right way to invest if you have the skills to do it.

For additional reading, see Howard Mark’s memo “Risk and Return Today.” You can find all his memos while at Oaktree here. You can also view the CFA Society Chicago luncheon presentation below.