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Article Dans Une Revue Journal of Econometrics Année : 2023

A penalized two-pass regression to predict stock returns with time-varying risk premia

Résumé

"We develop a penalized two-pass regression with time-varying factor loadings. The penalization in the first pass enforces sparsity for the time-variation drivers while also maintaining compatibility with the no-arbitrage restrictions by regularizing appropriate groups of coefficients. The second pass delivers risk premia estimates to predict equity excess returns. Our Monte Carlo results and our empirical results on a large cross-sectional data set of US individual stocks show that penalization without grouping can yield to nearly all estimated time-varying models violating the no-arbitrage restrictions. Moreover, our results demonstrate that the proposed method reduces the prediction errors compared to a penalized approach without appropriate grouping or a time-invariant factor model."
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Dates et versions

hal-04325655 , version 1 (06-12-2023)

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Citer

Gaetan Bakalli, Stéphane Guerrier, Olivier Scaillet. A penalized two-pass regression to predict stock returns with time-varying risk premia. Journal of Econometrics, 2023, 237 (2 Part C), 27 p. ⟨10.1016/j.jeconom.2022.12.004⟩. ⟨hal-04325655⟩

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