The Last Word on Low Risk, High Return

Oh look, here’s another CFA all breathless about the need to Rewrite the Finance Textbook: Low Risk Offers High Return:

As investment professionals, we were taught wrong. We were taught capital asset pricing model (CAPM) and efficient market hypothesis (EMH), which are overly simplistic. And contrary to what we were taught, low-volatility stock portfolios consistently outperform. This was the bold assertion made by Nardin Baker, CFA, chief investment strategist at Guggenheim Partners, who spoke to a hall full of investment professionals at the CFA UK Annual Conference 2013.
Referring to “Low Risk Stocks Outperform within All Observable Markets of the World,” a research paper he coauthored with Robert A. Haugen, Baker added that not only do these low-volatility stock portfolios outperform, but they also outperform in all equity markets of the world across time. Baker and Haugen’s study extends from 1990 to 2011 and covers stocks in 21 developed markets and 12 emerging markets.

There is no need to rewrite any textbooks. When prices rise, they don’t fluctuate much compared to when prices decline, thanks to their human traders puking and heaving all the way down. These ups and downs are quantified by calculating the standard deviation of price changes, which is exactly what they did:

Beginning with the first month of 1990, we compute the volatility of total return for each company in each country over the previous 24 months. Stocks in each country are ranked by volatility and formed into deciles, quintiles, and halves.

So basically, they separated the stocks that are neutral/going up from the ones that are going down, and found that the trend continued for one more month:

We then observe the total return for each decile in the first month of January. Next we re-rank stocks and observe the returns for February. Finally, we continue the process for each of the 264 months of the total period.
. . .
Obviously, the first set of columns in this Figure also show that past volatility is a good predictor of future volatility.

The Path of Least Volatility

God help them. As we have said many times before, the first principle is simple: increasing volatility is always bad. Big ups and big downs are bad because as Rama Cont points out in his landmark paper [PDF], “one observes large drawdowns in stock prices and stock index values but not equally large upward movements.”
So there you have it. What they are re-discovering over and over is a well-known fact. They are just seeing it backward and confusing cause and effect. Uptrends are simply less volatile than downtrends because the swings in prices are much smaller. Low volatility is just a statistical way of saying “this is not a downtrend”, which leads back to something to ponder:

The best problems, like the best toys, are hard to exhaust. You can approach them from a variety of different angles, each new angle making the problem fresh again, and bringing the opportunity to discover something new. Any idea, no matter how crazy seeming, might work and can be worth exploring. Indeed, the harder the problem, the more degrees of freedom one can allow in tackling it. Fischer relished hard problems because he relished that freedom, but in practice he did not try just anything. In his view, if a problem does not yield to known methods, that doesn’t mean we need more sophisticated methods, indeed probably just the opposite. Usually problems are hard not because our technique is deficient but because our understanding is deficient. Fischer Black and the Revolutionary Idea of Finance

Empirical properties of asset returns

For the keeners. (Nothing displayed below?)
[pdf width=”100%” height=”1100px”][/pdf]