Saturday, March 28, 2015

Review of The Missing Risk Premium: Why Low Volatility Investing Works by Eric Falkenstein

Eric Falkenstein has a very underrated finance blog (no longer active), which we have mentioned before talking about his excellent Batesian Mimicry hypothesis, his well founded criticisms of Taleb, where the money made at trade desks really comes from, and on competitive advantage.

He gathered his thoughts on the non-existent risk premium in finance (which means that modern portfolio theory is wrong) and on low volatility investing into a short book, The Missing Risk Premium: Why Low Volatility Investing Works. Modern portfolio theory (MPT) is the idea that the expected return of a financial asset is a function of its risk.

MPT is incorrect and has been proven incorrect repeatedly, but taxpayer money is used to pretend it is still true for a number of reasons. Economists and finance professors like it because they have invested their careers in it, it is easy to teach and generates a mathematically tidy curriculum, and it is essential for thousands of 20th century finance papers to be relevant. Managers of pension funds need it because it implies that they can achieve higher investment returns, and therefore pretend they will meet their pension goals, by taking more risk. As Falky says, "there is no shortage of people believing [this] theory is true because of its convenient implications."

By the way, one complaint that people have about Falky's book is that it's old news. Nobody believes in MPT, and as he argues, "if risk premiums were really ubiquitous, finance-specific tools would be valuable to hedge funds." It is true; there are no successful investors who are using this theory. But it is still part of the CFA curriculum! Taxpayer money is going to finance professors trying to overcome all the empirical data against it.

Rather than return being a function of risk as MPT claims, "as a first-order approximation, asset pricing theory has the wrong sign," with either no correlation or a negative correlation between risk and return. Some examples, including papers he cites in the book:

  • "[T]he return premium for the smallest capitalization group [of stocks] is an order of magnitude lower than what was originally discovered around 1980."
  • In corporate bonds, "the rate of return lined up almost perfectly with the rating, with AAA having the highest return, C the lowest." Investing in senior debt beats investing in subordinated debt, over time.
  • "Karl Diether et al. (2002) found the quintile of stocks with the greatest opinion dispersion underperformed a portfolio of otherwise similar stocks".
  • "Sophie Ni (2007) looked at data from 1996 through 2005 and found that the highest out-of-the-money calls, with one month to expiration, have average returns of −37 percent over a month".
  • For motion pictures, R-rated movies can be high grossing movies but have very high variance. G-rated movies are a lower variance strategy that have higher expected value. (see Hollywood Economist)
  • "Barro (2006) surveyed a number of financial collapses in the twentieth century and found that this adjustment suggested a 3 percent reduction to equity risk premia."
  • "Giesecke (2011) found that the total default rate for the 1873–1875 period was a whopping 36 percent, which for an entire bond market is much larger than what occurred in the Great Depression."
  • "Snowberg and Wolfers (2010) looked at more than 200,000 races and reported the rate of return to betting on horses with odds of 100/1 or greater is about 61 percent, betting randomly yields average returns of 23 percent, whereas betting the favorite in every race yields losses of only around 5.5 percent. They found this bias has been persistent for fifty years at least..."
In general, gamblers (like the retail investors who buy worthless stocks), prefer bets that offer the greatest maximum return even though they have very poor (negative) expected returns. "[T]he rich are stupid because they contain a disproportionate number of lucky morons who did not realize they were taking as much risk as there were," see "Noise Trader Risk in Financial Markets" [pdf].

Philosophically, "the idea that financial courage [to take risk] produces a strictly increasing and linear expected payoff to risk bearing is contrary to the payoffs to every virtue, which all require moderation and trade-offs with competing virtues" He points out that "a theory that implies a ubiquitous linear payoff to an action like exposure to volatility, regardless of context or quantity, would be unprecedented"

For Falkenstein, the result of the knowledge that risk is actually inversely proportional to return leads him to constructing low-volatility portfolios. This is something that he was on the cutting edge of, although it was simultaneously invented by a number of people and there are now a variety of low-volatility exchange traded funds. There is now ample evidence that these low-volatility portfolios outperform the market indices, and they are cheap to run. And as Falky points out, it's pretty funny that you can beat the index just by applying the idea that risk does not lead to reward!

One funny thing about low-volatility superiority is that is that we already know what ideosyncratic volatility means: it is a sign that something is worthless. Right now the low-volatility indexes are full of utility stocks: the S&P 500 utility weighting is 3.2% but the largest LV ETF has a 13% weight in utilities. It will be interesting to see whether, if electric utilities suffer from distributed solar, they are kicked out of the LV indexes because of rising volatility before they can cause too much damage.

I give this 5/5; nice and brief with lots of well-articulated points. Some of the more detailed rebuttals of MPT are irrelevant for practicing value investors. What's important is that it discredits buy-and-hold investing and asset allocation. I agree with Falky's advice for how you should invest, in light of MPT being wrong:
  • "[I]f you have no reason to presume you have an edge assume it is negative and invest in assets where this hurts you the least." (Similar to Whitebox principles)
  • "Finding good investments is like finding good ideas in general, things that are new, true, and important." (Thiel job interview question)
  • Stupid money buys "lottery tickets hoping to get rich quick with no effort. The effect is for really high-risk investments to have the most delusional investors, the most opportunistic sellers, and pathetic returns. [...] By ridding your asset classes of these objectively bad assets, you can improve your returns"
  • "It is essential to have the right connections when you have a good idea, more so the bigger the idea." Meaning people who can give you money. He did not have the right connections and did not make the money he should have on his low-volatility investing idea.
  • "Classic investors like J.P. Morgan and Benjamin Graham distinguished between gambling and investing, the former being simple exposure to randomness, the latter something amenable to special insight and intuition. A good investment has the odds decidedly stacked in its favor via some special insight."
Having special insight is the key. There's only so much one person, or company, can know or focus on. And if you don't have a special insight, be in cash. His thoughts are similar to those of another Minnesotan, Andy Redleaf (see 1,2,3).

1 comment:

CP said...

Also:

"[L]ess informed investors earn the highest (and lowest) rates of return on their total portfolios because they irrationally believe they have a more favorable risk-return opportunity and hence invest in securities with a higher return. In effect, their ignorance effectively diminishes their risk aversion, and in the long run allows a lucky few of them to reap the financial rewards that would accrue to the less risk averse (one could call it the 'Forrest Gump' effect). As opposed to speculation weeding out the irrational traders and making only the best opinions matter, the irrational can dominate the class of winners."

http://www.creditbubblestocks.com/2014/07/billionaires-are-mostly-random.html