Industry Momentum and Trend Factors Using Risk-Adjusted Returns

Summary

This research summary compares industry-level signals built from risk-adjusted returns and moving averages. It reports tests of Jensen’s alpha, Sharpe, Treynor, and Calmar measures across different lookback periods. The six-month Jensen measure behaved as a reversal signal, while selected one- and three-month measures from the other metrics showed momentum effects. A separate cross-sectional regression analysis formed short-, medium-, and long-horizon trend factors from moving-average signals; the summary reports that the short-term factor was predictive, while the longer-horizon factors offered little forecasting power in that study.

The authors also combined selected factors after examining their information-coefficient relationships. The three-factor combination had the strongest reported average IC and long-short annual return, while a two-factor combination had a higher IC hit rate, suggesting greater consistency by that measure. These are reported historical research results, not guarantees. The summary flags liquidity, model failure, and factor decay as risks, and it does not include the underlying sample details or full methodology needed to independently assess robustness.

Key ideas

• The study tests industry signals based on several risk-adjusted return measures over different lookback periods.
• The six-month Jensen measure is reported as a reversal factor, while selected other measures show momentum effects.
• Among moving-average trend signals, only the short-term factor is reported as strongly predictive.
• A three-factor blend has the strongest reported average IC, while a two-factor blend has a higher IC hit rate.
• The summary cautions about liquidity, model failure, and factor decay.

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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.