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Combination Return Forecasts and Portfolio Allocation with the Cross-Section of Book-to-Market Ratios
[Illiquidity and stock returns: cross-section and time-series effects]

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  • Andrew Detzel
  • Jack Strauss

Abstract

In this paper, we forecast industry returns out-of-sample using the cross-section of book-to-market (BM) ratios and investigate whether investors can exploit this predictability in portfolio allocation. Cash-flow and return forecasting regressions show that cross-industry BM ratios contain significant predictive information beyond aggregate and industry-specific BM ratios. Forecast combination methods based on industry BM ratios generate significant out-of-sample predictability for many industries. Real-time portfolio-rotation strategies that buy industries with high predicted returns and short industries with low predicted returns based on combination forecasts earn significant alpha with respect to standard asset pricing models net of transaction costs.

Suggested Citation

  • Andrew Detzel & Jack Strauss, 2018. "Combination Return Forecasts and Portfolio Allocation with the Cross-Section of Book-to-Market Ratios [Illiquidity and stock returns: cross-section and time-series effects]," Review of Finance, European Finance Association, vol. 22(5), pages 1949-1973.
    • Handle: RePEc:oup:revfin:v:22:y:2018:i:5:p:1949-1973.
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    File URL: http://hdl.handle.net/10.1093/rof/rfx035
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    References listed on IDEAS

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    1. Kuppenheimer, Gregory & Shelly, Stuart & Strauss, Jack, 2023. "Can machine learning identify sector-level financial ratios that predict sector returns?," Finance Research Letters, Elsevier, vol. 57(C).

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