Capturing stocks' volatility is a path to potential outperformance that is often overlooked in favor of the traditional betting on stocks that are likely to rise in value.
However, investors would potentially do well to pay more attention to the former alternative, since it has historically been easier to estimate volatility than to predict earnings, especially in efficient markets. Accordingly, employing rebalancing to generate returns from stock-price volatility might offer a preferable path to outperforming the market or a benchmark than conventional stock picking.
Figuring out the range of likely outcomes for any future event is typically easier than predicting the event's actual outcome. A coin toss is an excellent example: You can't accurately predict the outcome — heads or tails — but you can predict the likely range of outcomes, one or the other. Technically, it could also land on its side or not at all (a bird may snatch it in midair), but for most practical purposes, one can safely ignore these possibilities.
Properly using statistics allows one to anticipate the most probable range of outcomes for a future event and to estimate the likelihood of outliers, i.e., extremes that fall outside this range. The first type of analysis allows for making effective plans, while the second is the basis of proper contingency planning.
While the flip of a coin might appear to be a simplistic example, a similar statistics-based approach can be directly applied to investing in the stock market, where risk is usually relatively stable regardless of frequent price fluctuations. It is hard to predict what a stock's actual return will be tomorrow, even harder on a given day a few weeks from now. However, that stock's return will tend to be within a range that is consistent with the volatility exhibited over the past few months.
To see how the principles illustrated in the coin flip can be applied to the equity markets, let's use the share price of Exxon Mobil Corp. in the five-year period from 2009 through 2013 as an example. Each day we will attempt to predict the range of likely returns on a day one month in the future using only the volatility over the preceding month. One straightforward approach might be to estimate the volatility using the standard deviation of the daily returns of the past 20 trading days; we could then say that our estimate of the range of likely outcomes is four standard deviations, centered at zero. Even using this very simple recipe, we find there were only 86 days in the entire five-year period, or about 7% of the time, when our estimate was off the mark. This is an acceptable outcome, especially when compared with how hard it is to successfully predict even if Exxon Mobil will have a positive or negative return, or whether it will beat the Standard & Poor's 500 stock index, on a particular day a month in advance.