Mastery or Ignorance Part III

This post was also featured at Fortune Financial Advisors

Written by Lawrence Hamtil and Daniel Sotiroff with help from Alpha Architect’s Jack Vogel and Severian Asset’s Sam Lee

In the first installment in this series, we discussed how, contrary to conventional wisdom, the most profitable industries historically have tended to be not the companies most closely associated with technological innovation, but rather those that are least subject to disruption. In other words, industries such as tobacco and beer have tended have higher risk-adjusted returns than more glamorous industries such as software and financials.

In Mastery or Ignorance Part II, we elaborated on this theme, suggesting that it is the under-the-radar nature of these consumer staple-type industries that make them less prone to investor enthusiasm and resultant over-investment such as what happened in the utilities bubble of the 1920s, and the tech bubble of the 1990s when valuations in those sectors exploded well beyond anything fundamental. In fact, when examining historical industry returns in a process we like to call “financial archaeology,” the recurring theme seems to be that investors have a tendency to overpay for innovation, while discounting stability.

To build on this theme, I asked a good friend of mine, the Personal Finance Engineer, Dan Sotiroff, to help me with the numbers. We wanted to take the analysis a step further, and see just how stable the various industries have been over time, not just in terms of returns, but in terms of valuation multiples. To do this, we examined three major valuation ratios for ten industry portfolios (the same 10 industries available from Ken French’s data library) were compiled with the help of Alpha Architect’s Jack Vogel. We examined price-to-earnings, price-to-book, and EV/EBIT (enterprise value/earnings before interest and tax). Here’s what we found:

Greater Volatility Doesn’t Always Equal Higher Reward
As our previous posts have demonstrated, not only do Non-Durable (also known as consumer staples) industries have the highest risk-adjusted returns (e.g. higher Sharpe ratios), they have also posted some of the best absolute returns. Conversely, the highly volatile technology and durable goods sectors are near the bottom when it comes to absolute returns. At first blush this would appear to run counter to conventional wisdom: that investors receive higher rates of return in compensation for bearing additional volatility/risk. In practice, however, this has not been the case:

Return vs. Volatility of 10 Industries, 1926-2015

Since 1974, the non-relationship between greater volatility and higher returns has been even more stated:

Return vs. Volatility of 10 Industries, 1974-2015

A hallmark of the most profitable industries seems to be stability of valuation multiples
One of the astonishing things about so-called “defensive” sectors (consumer staples / non-durables, utilities, etc.) is that they have shown healthy historical returns, but they have done so while not commanding excessive multiples from investors. In other words, there has been less volatility in the price-to-earnings and EV/EBIT multiples over time for consumer staples than for high-tech and telecommunications (Note: In the French dataset, “Other” includes financials and banks, which explains that categorization’s plot placement.)

Return vs. P/E Volatility of 10 Industries

Return vs. EV/EBIT Volatility of 10 Industries

It is only on a price-to-book basis that consumer staples have shown a higher degree of volatility than other market participants:

Return vs. P/B Volatility of 10 Industries

At this point we draw two conclusions. First, the volatility of returns, as well as price-to-earnings, enterprise value-to-EBIT, and price-to-book all have a shared input: market capitalization. It’s worth noting, while not explicit, that enterprise value has an aspect of price “baked in” as the market capitalization of the company/sector/asset makes up a substantial portion of total enterprise value. The major implication here is that price movements have been responsible for a large portion (if not the majority) of volatility as the volatility of earnings, book value, and EBIT fail to alter the observable trends in a meaningful way (they are all flat to slightly negative).

Second, and perhaps more importantly, we note that simply taking on a higher level of absolute risk (as measured by standard deviation) is insufficient to generate additional return. One of the fundamental ideas of the Capital Asset Pricing Model is that investors should only be compensated for bearing systematic risk—or risk that is highly correlated with the overall market and therefore can’t be diversified away. Simply taking on higher levels of absolute risk shouldn’t pay off because uncorrelated but volatile returns can be diversified away. Along these lines of reasoning we should expect to see annualized returns correlate with beta, a measure of systematic risk.

Return vs. Beta of 10 Industries

Finally, because of their a-cyclical nature, consumer staple stocks have seemingly been taken for granted. Their returns have been largely consistent, but the stability of their valuations means they have been less prone to return-killing over-valuation. Take, for example, a comparison of the most profitable industry of the last 100 years, tobacco, versus what many would likely assume would be the technology of the future, software. Using the EV/EBIT multiple, you can see clearly the tech bubble of the late 1990s, while tobacco’s multiples have been remarkably stable:

Similarly, you can see the same relative volatility in valuations of the hardware technology industry versus the soda industry:

EV/EBIT Volatility of Tobacco and Software

Similarly, you can see the same relative volatility in valuations of the hardware technology industry versus the soda industry:

EV/EBIT Volatility of Soda and Hardware

But despite the stability in its valuation multiple over time, tobacco has crushed software:

Growth of $10k for Tobacco and Software

…and soda has outperformed hardware technology:

Growth of $10k for Soda and Hardware

Despite the fact that additional forms of risk—the Fama French factors such as small cap and value–were not accounted for, we note that these trends run counter to expectations. We defer to famed value investor Howard Marks for a shrewd explanation of the relationship between risk and return:

But riskier investments absolutely cannot be counted on to deliver higher returns. Why not? It’s simple: if riskier investments reliably produced higher returns, they wouldn’t be riskier!

The correct formulation is that in order to attract capital, riskier investments have to offer the prospect of higher returns, or higher promised returns, or higher expected returns. But there’s absolutely nothing to say those higher prospective returns have to materialize. [1]

Our data set shows a slight negative trend between return and Beta. Frazzini and Pederson of AQR point out that many investors expose themselves to high Beta assets in an attempt to earn higher returns. [2] The result of tilting towards these high Beta assets results in lower risk adjusted returns compared to low-beta assets. Their analysis shows similar results in multiple markets including foreign equities, Treasuries, foreign bonds and commodities. Thus the results observed here, while constrained in time and focused on domestic stocks*, are not a product of a specific period or market, but instead are somewhat consistent with outcomes present in multiple markets and stretches of time.

Perhaps the phenomenon we’ve described is best encapsulated by the commentary of Severian Asset’s Sam Lee. Sam has written extensively on the historical outperformance of low-volatility stocks such as consumer staples, and he attributes their excess performance to three key factors:

  1. Due to their tendency to over-extrapolate from current conditions, investors systematically fail to appreciate the earnings power of very stable companies, while overestimating the longevity of earnings for firms in highly cyclical businesses.
  2. Investors have lottery-seeking tendencies which leads them to overpay for firms that have the potential for making enormous gains, while devaluing firms that earn low but steady returns.
  3. Investors are leverage-constrained and so in order to earn higher returns seek out higher-risk assets, which, ironically, don’t produce higher returns.

In conclusion, it would appear that taking on higher levels of volatility or overpaying for innovation and glamour may make for great chatter at a dinner party, but don’t expect it to provide higher rates of return.

*While our study on volatility of valuations focused solely on domestic stocks, we found similar risk-reward characteristics for low-volatility sectors in both foreign and emerging market stocks, albeit without the luxury of having valuation data available:

Return vs. Volatility, ex-US Industries

Return vs. Max Drawdown, ex-US Industries

Return vs. Volatility, Emerging Market Industries

Return vs. Max Drawdown, Emerging Market Industries

References
1. Marks, Howard. The Most Important Thing Illuminated. Columbia University Press. 2013. p. 41.
2. Frazzini, Andrea and Lasse Pederson. Betting Against Beta. Journal of Financial Economics. Volume 111. Issue 1. January 2014. pp. 1-25. http://www.sciencedirect.com/science/article/pii/S0304405X13002675.
3. Data for ex-US and Emerging Market portfolios courtesy of Morningstar.

The Sharpe Ratio As An Efficiency Metric

Ratios and normalized metrics are used regularly in the hard sciences, particularly when it comes to comparing scenarios and outcomes. The efficiency of a vehicle, for instance, is typically measured in miles per gallon, or the distance traveled per unit of energy. A Toyota Prius at about 50 MPG is without a doubt substantially more efficient compared to say a top fuel dragster.

The financial world has its equivalent of miles per gallon: the Sharpe Ratio, which combines both return and volatility into a single metric

Sharpe Ratio Equation

In it’s original form, presented here, the ratio quantifies an assets return in excess of a risk-free rate (the risk premium) per unit of volatility. In his 1966 paper Nobel Laureate William Sharpe derived this measure of investment efficiency from a linear relationship between return and volatility (risk). [1] The plot below shows this linear relationship between US Large Company Stocks (S&P 500) and the thirty day Treasury Bill. The volatility of the thirty day T-Bill was set to zero to satisfy the “risk-free” criteria assumed in Sharpe’s work.

sr_sp500

In the absolute sense risk-free returns don’t really exist. The thirty day Treasury Bill does indeed have a small amount of volatility associated with it. From 1926 through 2015 the annualized standard deviation was approximately 0.9%. To build a more accurate model this volatility should be accounted for, and as Harry Markowitz demonstrated, the standard deviation of a portfolio is not simply the weighted sum of the constituent standard deviations. Using Markowitz’s formulas results in the following efficient frontier

sharpe_markowitz

Admittedly I’m splitting hairs. Sharpe’s model is in fact a very close approximation of the Markowitz efficient frontier when comparing various mixes of an asset and the 30 day Treasury Bill. The linearity only begins to break down as the portfolio approaches a 100% allocation to Treasury Bills–it’s rather trivial.

But there’s a bigger issue with the Sharpe Ratio, and it isn’t the fault of the ratio itself, rather how the ratio is interpreted. At first glance it would appear that higher Sharpe Ratios indicate more desirable assets. Is a higher Sharpe Ratio always better? Consider the performance of the 5 year Treasury Note and Large Company US stocks

Asset Performance
(1926 – 2012)
US Large Co. Stocks 5 Year Treasury Note
Annualized Total Return 9.8% 5.4%
Standard Deviation 19.1% 4.4%
Sharpe Ratio 0.33 0.42
Source: SBBI [3]

If one were to use the Sharpe Ratio as the sole criteria for making investment decisions then Treasury Notes have clearly been superior to US stocks. The comparison here isn’t all that different from the Prius and the drag racer I mentioned previously. Efficiency and absolute performance are very different things. One option may be more efficient, but is it really sufficient to accomplish the task at hand? It probably depends on what the objective is in the first place. Sharpe himself recognized that using only mean return and variance (or standard deviation) was too simple to fully capture the needs of every investment decision

Clearly, comparisons based on the first two moments of a distribution do not take into account possible differences among portfolios in other moments or in distributions of outcomes across states of nature that may be associated with different levels of investor utility.

When such considerations are especially important, return mean and variance may not suffice, requiring the use of additional or substitute measures. [2]

Efficiency may be one useful measure to consider, but it doesn’t necessarily equate to “better.”

Offered without comment…

rolling_30year_sharpe

Addendum
26 September 2016 8:38 pm CDT

When I originally put this post together I struggled with the topic of leverage as it does play an important role in the overall theory that Sharpe presented. The perspective I shared above was viewed through the lens that leverage was not a choice available to investors. This was a conscious decision as I felt it distracted from the bigger message I was trying to communicate. Consequently some of the feedback I received revolved around this omission.

The manner in which leverage makes higher Sharpe ratios more appealing can be demonstrated in the following two scenarios. Both were constructed using the numbers above for the 5 year Treasury Note and US stocks.

Scenario 1
A portfolio of Treasury Notes is levered to the same level of volatility as US stocks. The resulting return would have been 3.5% + 0.42*19.8% = 11.8%. This would require a leverage ratio of 11.8%/5.4% = 2.19.

Scenario 2
Again, a portfolio of Treasury Notes is levered, but this time to achieve the same return as US stocks. The resulting volatility would be (9.8% – 3.5%)/0.42 = 15.0% with a required leverage ratio of 9.8%/5.4% = 1.81. Clearly less volatile than US stocks.

The use of leverage is key to understanding why a higher Sharpe Ratio–the risk adjusted return–is considered the preferred choice. But this thought pattern assumes that investors are comfortable with borrowing to finance investment, and can do so at a reasonable interest rate. In practice the use of leverage should not be taken lightly, and is not something that I believe is best for the do-it-yourself set. Hence my hesitation to bring it up in the initial discussion. My original intent, in a pragmatic way, was to demonstrate the necessity to look beyond simple metrics that appear to be an all-in-one solution to investment decisions.

References
1. Sharpe, William F. Mutual Fund Performance. Journal of Business. January 1966. pp. 119-138.
2. Sharpe, William F. The Sharpe Ratio. The Journal of Portfolio Management. Fall 1994. https://web.stanford.edu/~wfsharpe/art/sr/sr.htm
3. 2013 Ibbotson SBBI Classic Yearbook. Morningstar Inc. Chicago, IL. pp. 184-211.


The Traits and Processes That Lead to Better Forecasts (Charles Rotblut and Philip Tetlock)
Mean Reversion: Gravitational Super Force or Dangerous Delusion? (Aswath Damodaran)
Is Momentum Really Momentum? (Robert Novy-Marx)
The Mistrust of Science (Atul Gawande)
The Professor Who Was Right About Index Funds All Along (Bloomberg)
The Free-Time Paradox In America (Derek Thompson)
The Myth of Progress (Lawrence Hamtil)
Tactical Asset Allocation: A Practitioner’s Defense of Return Predictability (Wes Gray)

Confessions Of An Asset Allocator

Several years ago when I made my first real attempts at managing my own assets the idea of a fixed asset allocation strategy made a lot of sense. Diversify by allocating broadly to a wide range of foreign and domestic securities using fixed income to control volatility. Rebalance regularly, limit transactions as much as possible, and always mind fees. When you run strategies such as these through a back-test the results come out to be fairly decent over many different time periods and market cycles. There is nothing wrong with these strategies, and the vast majority of individual retail investors out there are most likely well served through such investment policies. The difficulty is often finding a strategy that aligns with one’s personal preferences and tolerance for volatility.

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The Five Laws of Gold

The Richest Man In Babylon was originally a collection of parables penned by George Clason in 1926 that focused on the judicious handling of money. Ninety years later these stories are still very applicable to our modern financial lives, with many of the lessons having been repeated numerous times in various forums. For all the time spent analyzing portfolio strategies and understanding asset class behavior there are some foundational concepts that must be in place to ensure personal financial success. Sound advice seldom, if ever, changes.

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Quantitative Value

The idea of buying stocks that are cheap and holding on as they appreciate in value over time is well aligned with the simple heuristic “buy low and sell high.” This central concept has created, for myself, a natural and intuitive pull towards value investing. The problem is that not all “cheap” stocks eventually go on to appreciate in value. Some are cheap for a reason–they have poor prospects and will likely end up in Wall Street’s corporate boneyard.

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Getting Real With Inflation

Inflation is one of the oldest and most well known adversaries faced by investors. Simply put it measures the change in price of goods and services that we purchase or consume including food, fuel, utilities, housing, clothing, entertainment, etc. That being said, investors must achieve a rate of return in excess of the rate of inflation in order to improve their purchasing power.

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Cost of Capital

Good businesses, by definition, earn more than they spend. Those that can’t or don’t simply cease to exist. A quick glance at any corporate balance sheet reveals a wide ranging list of liabilities including: wages and salaries, accounts payable, employee benefits, etc. But there is an additional liability not disclosed on GAAP compliant balance sheets: the cost of capital.

Cost of capital is essentially what a company must pay it’s investors for financing its business activities. It is roughly equivalent to the return an investor should expect to receive for investing in a company.

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