Momentum is the tendency for assets that have performed well (poorly) in the recent past to continue to perform well (poorly) in the future, at least for a short period of time. The momentum effect is one of the most pervasive asset pricing anomalies documented in the ?nancial literature: Stocks with highest returns over the past six to 12 months continue to deliver above-average returns in the subsequent period.

In 1997, Mark Carhart, in his study “On Persistence in Mutual Fund Performance,” was the first to use cross-sectional (or relative) momentum, together with the three Fama–French factors (market beta, size, and value), to explain mutual fund returns. Initial research on cross-sectional momentum was published by Narasimhan Jegadeesh and Sheridan Titman, authors of the 1993 study “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency.”

As my co-author, Andrew Berkin, and I show in “Your Complete Guide to Factor-Based Investing,” the evidence supporting the momentum factor (both cross-sectional and time-series, or absolute momentum) and premium is persistent across time, pervasive around the globe and across asset classes, robust to various definitions, and implementable. We also provide the well-documented behavioral explanations for the factor’s existence.

Source: Quantitative Momentum (2016). The chart shows the invested growth of intermediate term momentum (2-12 month lookback) from 1927 to 2015 using data from Ken French’s website. The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

One of the critiques of cross-sectional momentum is that it has a dark side, being subject to crashes (though this is only true for long-short portfolios, not long-only portfolios), such as the one that occurred in 2009 when the Fama-French French momentum factor (UMD, or up minus down) returned -83 percent. (See for example, “Momentum Crashes,” by Kent Daniel and Toby Moskowitz.)

Crashes to cross-sectional momentum occur because the long leg of momentum has positive exposures to the styles that performed well in the recent past, while the short leg is exposed to those that underperformed. For example, in bear markets, high beta stocks tend to underperform while low beta stocks outperform. As a result, momentum can exhibit negative returns if the market experiences a sharp turn. Below is Table 2 from the Momentum Crashes paper, which highlights some of the horrible monthly returns associated with the long/short momentum factor.

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