What Is The Best Way To Measure Risk?

This is the first part of a guest article by Market Wizards author & hedge fund expert Jack Schwager about the best way to measure risk based on a question submitted by a reader on Bidnessetc.com.

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This is a very broad question—so much so that I will take three articles to answer it. In this article, I will focus on the validity and applicability of using volatility as a proxy for risk. In the second article, I will consider alternative—and I would argue, superior—measures of risk. Finally, in the third article, I will focus on gauging (and controlling) future risk as opposed to measuring past risk. Since risk measurement is equally pertinent to both traders and investors, I will use both perspectives in the first two articles.

“Volatility” is the layman’s term used to refer to a statistical measure: the standard deviation. Many readers will know the mathematical definition of the standard deviation, but for those who do not, think of standard deviation as a measure of how variable returns are. The more widespread returns are around the historical mean return, the higher the standard deviation. To provide a tangible sense of the standard deviation, assuming returns are normally distributed (a convenient simplifying assumption subject to many exceptions in markets and trading), then 95% of the time returns would be expected to fall within two standard deviations of the average return (assuming we use the historical average return as the expected future return level). For example, if a manager has a 15% average annual return (which is assumed to be the future expected return) and a 5% standard deviation, there would a 95% probability for the annual return to fall in a range between +5% and +25%. If another manager also has a 15% average annual return but has a 20% standard deviation, the 95% probability range for return would widen to -25% to +55%. Both managers are assumed to have the same expected return but there is much more uncertainty in the return level for the manager with higher standard deviation.

It is important to understand that the standard deviation measures the variability in returns and does not necessarily reflect the risk of losing money. Consider a fund that lost 1.0% every month. Such a fund would have a standard deviation of 0.0 because there is no variability in returns, but it would have an absolute certainty of losing money. This quirky example was provided by Milt Baehr, the cofounder of Pertrac, in a conversation we had years ago.

Volatility (i.e., the standard deviation) is often viewed as being synonymous with risk—a confusion that lies at the heart of the mismeasurement of risk. Volatility is only part of the risk picture—the part that can be easily quantified, which is no doubt why it is commonly used as a proxy for risk. A comprehensive risk assessment, however, must also consider and weigh hidden (or event) risks, especially since these risks may often be far more important.

The confusion between volatility and risk often leads investors to equate low-risk funds with low-volatility funds. The irony is that many low-volatility funds may actually be far riskier than high-volatility funds. The same strategies that are most exposed to event risk (e.g., short volatility, long credit) also tend to be profitable a large majority of the time. As long as an adverse event does not occur, these strategies can roll along with steadily rising NAVs and limited downside moves. They will exhibit low volatility (relative to return) and look like they are low risk. But the fact that an adverse event has not occurred during the track record does not imply that the risk is not there.

Consider, for example, Fund A that employs a strategy of selling out-of-the-money options. Barring abrupt, large moves, the fund will collect premium on options that expire worthless and will be profitable. The track record will be dominated by a large percentage of profitable months and relatively low volatility, providing an appearance of both consistent profitability and low risk. But does this apparent volatility actually imply low risk? Not at all! Should the market witness a sudden, large price decline, the risk would explode, as formerly out-of-the-money options move in the money—a transition that would be associated with a sharp increase in the delta of the options (the percentage by which the option price changes in response to a price change in the underling market). Effectively, then, in this strategy, the greater the adverse price move, the larger the exposure becomes—the exact antithesis of a low-risk strategy.

The behavior of investments vulnerable to event risk operates in two radically different states: the predominant phase when conditions are favorable and the sporadic phase when an adverse event occurs. It is folly to estimate overall performance characteristics based on just one of these phases. Assuming that low volatility implies that a fund is low risk is like assuming a Maine lake will never freeze based on daily temperature readings taken only during the summer.

Trading strategies can embed both low volatility and high risk. Strategies that fall into both categories would have the following characteristics:

• The strategy has a high probability of moderate return and a small probability of large loss.
• The strategy track record overlaps a favorable market environment for the particular approach.
• There were no major stress events for the strategy during the available track record.

My intention is to caution that low volatility does not necessarily imply low risk. There is, however, no intention to suggest that low volatility implies high risk. Of course, some low-volatility strategies will also be low-risk. The key is determining the reason for the low volatility. If low volatility can be attributed to a strategy that assumes a trade-off of frequent moderate wins in exchange for the risk of occasional large losses (e.g., selling out-of-the-money options, leveraged long credit positions), then the risk evaluation must incorporate the implications of an adverse event, even if one did not occur during the available track record. If, however, low volatility can be attributed to a strategy that employs rigorous risk-control—for example, a risk management discipline that limits losses to a maximum of 0.5% per trade—then low volatility may indeed reflect low risk.

Not only does volatility, as typically measured by the standard deviation, often dramatically understate risk in circumstances when hidden risks apply, in some cases, volatility can also significantly overstate risk. Some managers pursue a strategy that curtails the downside, but allows for large gains. Consider Fund B in which the manager buys out-of-the-money options at times when a large price move is anticipated. The loss on these trades would be limited to the premium paid, but the gain would be open-ended. If, on balance, the manager was successful in timing these trades, the track record might reflect high volatility because of large gains. The risk, though, would be limited to the loss of the option premium. In effect, the manager’s track record would exhibit both high volatility and low risk.

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It is important to stress that the just-described Fund B is not the inverse of previously discussed Fund A, which consistently sold out-of the-money options. The opposite strategy of consistently buying out-of-the-money options might have limited monthly losses, but it would certainly be prone to large cumulative drawdowns over time because of the potential of many consecutive losing months. Also, since option sellers are effectively selling insurance (against price moves), it is reasonable to assume that they will earn some premium for taking on this risk. Over broad periods of time, consistent sellers of options are likely to earn some net profit (albeit at the expense of taking on large risk exposure), which implies an expected net negative return for consistent buyers of options. In order for a long option strategy to be successful, as well as exhibit constrained drawdowns over time, the manager needs to have some skill in selecting the times when options should be brought (as opposed to being a consistent buyer of options).

So high volatility is neither a necessary nor a sufficient indicator of high risk. It is not a necessary indicator because frequently the track record volatility may be low, but the strategy is vulnerable to substantial event risks that did not occur during the life span of the record (that is, hidden risks). It is not a sufficient indicator because, in some cases, high volatility may be due to large gains, while losses are well controlled.

Volatility is most useful as a risk indicator for highly liquid trading strategies. For example, for long/short strategies in markets such as future, FX, and mid-to-large cap stocks, high volatility will usually be a good proxy for risk, in the sense that there will be a strong correlation between the volatility maximum loss over any specified holding period. But even for these types of strategies, volatility may be misleading because high volatility could be due to outsize gains rather than outsize losses. This characteristic of volatility underlies the main weakness of the Sharpe ratio, the most widely used return/risk measure, which is defined as the average return in excess of the risk-free return divided by the standard deviation.

By Jack Schwager

Jack Schwager is an industry expert in futures & hedge funds, perhaps best known for his best-selling series of interviews with the greatest hedge fund managers of the last three decades, which includes Market Wizards ,The New Market Wizardsand Stock Market Wizards. 

Schwager was also a partner at London-based hedge fund advisory firm Fortune Group and has 22 years experience as Director of Futures research for some of Wall Street’s leading firms, most recently Prudential Securities.

He is now the co-founder of FundSeeder, a platform designed to find undiscovered trading talent worldwide & connect unknown successful traders with investment capital.