Journal Articles Journal of Econometrics Year : 2023

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

Abstract

"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."

Fichier principal
Vignette du fichier
728765-A penalized two-pass regression to predict stock returns with time-varying risk premia.pdf (692.26 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Licence

Dates and versions

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

Licence

Identifiers

Cite

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⟩

Collections

51 View
183 Download

Altmetric

Share

  • More