Ed. Originally written in 2011. Published in 2013
“Look ma, I have skill!”
An idea that would have been regarded as heresy in the 1990s has gained acceptance and respectability: the idea that investors are not rewarded for risk, systematic or otherwise.
Thanks to the long-term performance dominance of low volatility assets over the past few decades, producing an apparently informative backtest has become easy. Just make sure your ranking process favors lower volatility assets and your strategy has a nice tailwind.
Prior to the Fama/French litany it had been just as easy to find attractive backtest results by favoring Value and Small Caps. (And eventually, Momentum). That’s why regressing against Fama/French factors has become standard in any kind of investment anomaly or strategy analysis hoping to be taken seriously.
While Small Caps performed better than Large Caps in the long run, they have endured cycles of being out of favor for entire decades. Value and Growth have seen pronounced cycles too, and by construction the stocks favored by Momentum today might be quite different from the stocks favored by Momentum a year ago or a year from now.
Further, stocks can conceivably cross over categories. Small Caps can become Large Caps; Value can become Growth, and today’s Momentum stock might not be one in a year.
Stickiness of Low Volatility Means Low Volatility Strategies Enjoy Low Turnover
But when you rank stocks by volatility, you’re ranking stocks by something more permanent than Momentum, Capitalization, or Valuation. Stocks ranked today as Volatile are likely to have been ranked as Volatile a year ago, and probably will be in another year (if they’re still around).
The table below displays the rank correlation of the constituents of the SPY ETF as of July 29, 2011, sorted by trailing 1-year standard deviation of daily log returns, to their ranks the following year. The following year they’re sorted both by standard deviation and downside risk.
| Year-end | Correlation of this year’s Standard Deviation with Next year’s | Correlation of this year’s Standard Deviation with Next year’s Downside Risk |
|---|---|---|
| 2009 | 0.84 | 0.84 |
| 2008 | 0.88 | 0.89 |
| 2007 | 0.72 | 0.76 |
| 2006 | 0.67 | 0.61 |
| 2005 | 0.87 | 0.85 |
| 2004 | 0.83 | 0.8 |
| 2003 | 0.77 | 0.77 |
| 2002 | 0.86 | 0.87 |
| 2001 | 0.77 | 0.82 |
| 2000 | 0.77 | 0.77 |
| 1999 | 0.83 | 0.78 |
| 1998 | 0.84 | 0.81 |
| 1997 | 0.83 | 0.79 |
| 1996 | 0.84 | 0.82 |
| 1995 | 0.87 | 0.85 |
| 1994 | 0.89 | 0.85 |
| 1993 | 0.86 | 0.79 |
| 1992 | 0.85 | 0.84 |
| 1991 | 0.86 | 0.82 |
| 1990 | 0.86 | 0.82 |
| 1989 | 0.77 | 0.76 |
| 1988 | 0.73 | 0.75 |
| 1987 | 0.71 | 0.82 |
| 1986 | 0.59 | 0.71 |
| 1985 | 0.69 | 0.74 |
| 1984 | 0.84 | 0.79 |
Source:PortfolioWizards
Notice two things: first, today’s volatile stocks tend to be next year’s; second, whether you rank by standard deviation or by downside risk doesn’t seem to make much difference.
While this data set is survivorship-biased, even in data sets that aren’t subject to survivorship bias this pattern remains. Which means if you want to manage a Low Volatility portfolio, chances are it won’t have to have high turnover.
Lake Woebegone Backtests
We’ve now endured a few decades when systematic risk has mostly been punished, which is one reason why you’re seeing so many “low volatility” and “minimum volatility” strategies appearing. All these back-tested results are above average! Whether the return to systematic risk turns out to have been a myth remains an open question to many, but when you’re exploring new investment products and strategies, keep in mind that we’ve just lived through an era when almost any strategy with lower risk than cap weighted indices will have outperformed those indices. Look for low volatility bias. Is low volatility an explicit part of the author’s strategy, or was it an unintended consequence that happened to be in favor?
Given the dominance of the superior performance of Low Volatility over the past several decades, superior backtest results you see today are likely to have another feature in addition to exposure to the Fama/French factors: a Low Volatility tilt.
Not that there’s anything wrong with Low Volatility – just make sure that whenever you’re evaluating the performance of a manager, an ETF, or a vendor, you’re aware of how much of a Low Vol effect there is in the data.