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

38 Pages Posted: 1 Feb 2021

See all articles by Gaetan Bakalli

Gaetan Bakalli

University of Geneva - Geneva School of Economics and Management

Stéphane Guerrier

University of Geneva - Geneva School of Economics and Management

O. Scaillet

University of Geneva GSEM and GFRI; Swiss Finance Institute; University of Geneva - Research Center for Statistics

Date Written: January 31, 2021

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.

Keywords: two-pass regression, predictive modeling, large panel, factor model, LASSO penalization.

JEL Classification: C13, C23, C51, C52, C53, C55, C58, G12, G17

Suggested Citation

Bakalli, Gaetan and Guerrier, Stéphane and Scaillet, Olivier, A penalized two-pass regression to predict stock returns with time-varying risk premia (January 31, 2021). Swiss Finance Institute Research Paper No. 21-09, Available at SSRN: https://ssrn.com/abstract=3777215 or http://dx.doi.org/10.2139/ssrn.3777215

Gaetan Bakalli

University of Geneva - Geneva School of Economics and Management ( email )

Uni Mail
Bd du Pont-d'Arve 40
Geneva, 1211
Switzerland

Stéphane Guerrier

University of Geneva - Geneva School of Economics and Management ( email )

Uni Mail
Bd du Pont-d'Arve 40
Geneva, 1211
Switzerland

Olivier Scaillet (Contact Author)

University of Geneva GSEM and GFRI ( email )

40 Boulevard du Pont d'Arve
Geneva 4, Geneva 1211
Switzerland
+ 41 22 379 88 16 (Phone)
+41 22 389 81 04 (Fax)

HOME PAGE: http://www.scaillet.ch

Swiss Finance Institute

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

University of Geneva - Research Center for Statistics

Geneva
Switzerland

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
137
Abstract Views
416
rank
249,024
PlumX Metrics