Macroeconomic Factors for Equity Industry Rotation

Summary

This report summary describes three methods for rotating among equity industries using macroeconomic information. The first models industry excess returns from cyclical components of leading indicators spanning growth, inflation, trade, and liquidity. The second estimates each industry's sensitivity to economic policy uncertainty by adding an uncertainty index to a Fama-French three-factor regression. The third normalizes and equally weights those two signals; their reported monthly excess returns have a correlation of 0.21.

Against an equal-weighted industry benchmark, the summary reports annualized long-only excess returns of 7.33% for the predictive method, 5.33% for the uncertainty-beta method, and 9.66% for the combined factor. It also gives long-short figures and turnover for the first two approaches, plus relative drawdowns for two strategies, but some reported fields are blank, including a combined long-short result. These figures are presented without the underlying report, sample period, detailed portfolio rules, or validation information. The source flags market-wide, model specification, and factor failure risks, so the reported historical returns should not be treated as evidence of future performance.

Key ideas

• The predictive rotation method relates industry excess returns to cyclical components of leading macroeconomic indicators.
• An economic uncertainty beta is estimated by regressing industry returns on Fama-French factors and an uncertainty index.
• The report combines normalized versions of the return forecast and uncertainty beta signals with equal weights.
• The two component strategies have reported monthly excess-return correlation of 0.21.
• Historical results are incomplete in places and carry market, model, and factor failure risks.

Tags

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