Blog - Investing Notes

March 11, 2008 - Beat the Market with Hot-Anomaly Switching?

Can investors beat the market by iteratively finding and exploiting the current hot anomaly? In his February 2008 paper entitled "Real-Time Profitability of Published Anomalies: An Out-of-Sample Test", Zhijian Huang investigates whether a trader can realize excess returns by repeatedly picking the anomaly with the best return during a rolling historical window from an expanding universe of anomalies as published. The universe includes anomalies that: (1) have been published in at least one of three top-ranked finance journals; (2) relate to the calendar or to cross-sectional predictability; and, (3) can be re-evaluated annually. Using monthly return data associated with nine anomalies published during 1977-1991 (Monday effect, January effect and cross-sectional effects related to size, book-to-market ratio, momentum, earnings/price ratio, cash flow/price ratio, dividend yield and and debt/equity ratio) as available through 2006, he concludes that:

• Excess returns for eight of the nine anomalies decline after publication, sometimes markedly.
• A trader can outperform the market by by an average 5.25% to 12.66% annually by iteratively switching to the best past performer among published anomalies. (See the chart below.)
• Excess returns are highest for past performance (training) periods of two to five years.
• While the January effect and momentum effect are drivers, similar results accrue from consideration of only a subgroup of anomalies. Increasing the number of anomalies considered steadily boosts average realized excess returns.
• Results are robust to different levels of transaction costs.

The following chart, taken from the paper, depicts the cumulative wealth from a $1 initial investments in a broad market index and in the best performing anomaly over past one, two, five, and ten years, retested/reselected annually. It shows that a five-year past performance (training) period generates the greatest excess returns. All results include transaction costs derived from crude assumptions (1% of assets annually for cross-sectional anomalies, 2% of assets annually for the January effect and 5% of assets annually for the Monday effect).

In summary, a trader who periodically switches to the hottest known anomaly based on a rolling window of past performance may be able to beat the market. Anomalies appear to have their own kind of momentum.

Perhaps the very best trading strategies are those that rotate (but not too often, based on trading costs) to the hottest anomalies in the hottest asset classes. See our blog entries of 1/7/08, 7/27/07 and 2/27/07 for strategies that use one or two anomalies to rotate through asset classes. See also our blog entry of 2/7/08 for evidence that inflexible strategies work only for limited periods.

For other big-picture research, see Blog Synthesis: Big Ideas for Investing/Trading.