Optimal Factor Timing in a High-Dimensional Setting

We develop a framework for equity factor timing in a high-dimensional setting when the number of factors and factor return predictors can be large. To ensure good out-of-sample performance, the approach is disciplined by shrinkage that effectively expresses a degree of skepticism about outsized gains from timing. In our empirical application, the predictors include macroeconomic variables and factor-specific characteristics spreads between the long and short legs of the factors. We find sizable gains from timing equity factors, including for factors constructed only from large-cap stocks.

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Publication Details

Journal
Financial Analysts Journal
Published
2025-03-27
DOI
https://doi.org/10.1080/0015198x.2025.2474385
Citations
1
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
2.21
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article

Optimal Factor Timing in a High-Dimensional Setting

Manan Mehta, Stefan Nagel, Rob Lehnherr
1 citations
Financial Analysts Journal
Stochastic processes and financial applications
2.21
article

Optimal Factor Timing in a High-Dimensional Setting

Manan Mehta, Stefan Nagel, Rob Lehnherr
article en
1 citations

Abstract

We develop a framework for equity factor timing in a high-dimensional setting when the number of factors and factor return predictors can be large. To ensure good out-of-sample performance, the approach is disciplined by shrinkage that effectively expresses a degree of skepticism about outsized gains from timing. In our empirical application, the predictors include macroeconomic variables and factor-specific characteristics spreads between the long and short legs of the factors. We find sizable gains from timing equity factors, including for factors constructed only from large-cap stocks.

Financial Analysts JournalVol. 81(2)
Russian State Agrarian Correspondence University (RU)
Openalex Percentile: Top 16%
Stochastic processes and financial applications
2.21
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