In constructing TS strategies for their paper, Moskowitz, Ooi and Pedersen scale positions using an inverse volatility scaling approach that scales positions in each asset class by a factor equal to 40% divided by the lagged volatility of the asset. Using this scaling approach leads to larger cumulative positions across both long and short positions in dollar terms. This, then, ultimately magnifies the size of profits for the TS strategies.
To account for this, Goyal and Jegadeesh construct similarly scaled CS strategies to compare to TS strategies constructed using this inverse volatility-scaling approach. The authors’ main takeaways include:
- Both volatility-scaled TS and CS strategies earn positive excess returns for all ranking periods. However, the differences in returns between the similarly scaled TS and CS strategies are quite different.
- Volatility-scaled CS strategies earn bigger returns than the corresponding volatility-scaled TS strategies for all ranking periods except the longest one that looks back 60 months.
- As an example, when using 12-month ranking and one-month holding periods (12 x 1), the CS strategy earned 21.55%, while the TS strategy earned 14.75%.
- Net long positions of the volatility-scaled TS strategy are much higher than those for TS strategies that are not scaled inversely by volatility.
As with the other TS strategies analyzed, volatility-scaled TS strategies also tend to have time-varying net long positions in risky assets.
To account for this, the authors again add a time-varying investment in a market index to CS strategies. When comparing volatility-scaled TS and CS strategies with similar volatility-scaled CS strategies that have a time-varying investment in the market, the authors found that the latter outperform both the volatility scaled TS and CS strategies across all ranking periods.
Goyal and Jegadeesh refute Moskowitz, Ooi and Pedersen’s claims that TS and CS momentum are distinct sources of returns. They show that differences in returns between TS and CS strategies shown in prior research are primarily driven by differences in factor construction and not necessarily by differences in return phenomena.
The main difference in returns between previously studied TS and CS strategies relates to both a time-varying net long investment in risky assets of TS strategies and differences in position scaling. When controlling for scaling differences and the time-varying net long exposure that TS strategies take on, CS strategies actually outperform.
Managed futures strategies have typically implemented some form of time-series momentum strategy, also commonly referred to as “trend-following.” Even though the authors show that TS momentum is not a distinct return phenomenon from CS momentum, this doesn’t mean that having an allocation to trend-following in a portfolio isn’t advised; investors just need to understand what exposure they are actually receiving.
Goyal and Jegadeesh suggest that trend-following strategies really just provide exposure to CS momentum with an additional time-varying net long investment in risky assets. While net long over the longer term, managed futures will be net short at certain periods—for example, trend-following strategies generally tend to be net short when markets are in crisis.
This is an attractive property, since trend-following has historically provided a left-tail (the risk of large losses) hedging property during poor market periods. For some investors, my firm, Buckingham Strategic Wealth, recommends a modest allocation to managed futures strategies because of this left-tail hedging property in addition to the robust momentum premium and its lack of correlation to traditional asset classes like stocks and bonds, along with other factors or return phenomena over the long term.
Larry Swedroe is the director of research for The BAM Alliance, a community of more than 140 independent registered investment advisors throughout the country.