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Gaetan BAKALLI (GSEM, Switzerland) “A Penalized two Pass Regression to Predict Stock Returns with Time-Varying Risk Premia”
Time: 10:30 pm
Date: 16th of December 2021
Room : 3001
Gaetan BAKALLI (GSEM, Switzerland) “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.
Organizers:
Jean-Michel ZAKOIAN (CREST)
Sponsors:
CREST