​Oliver Scaillet (Université de Genève and SFI)

Oliver Scaillet (Université de Genève and SFI)

Discussant: Marcelo C. Medeiros (Pontifical Catholic University of Rio de Janeiro)

Title: A Penalized Two-Pass Regression to Predict Stock Returns with Time-Varying Risk Premia

Authors: Gaetan Bakalli, Stephane Guerrier and Olivier Scaillet

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.

Bio of speaker:
Olivier Scaillet is professor of finance and statistics at the Geneva Finance Research Institute of the University of Geneva and has a senior chair at the Swiss Finance Institute. He holds both a master and Ph.D. from University Paris IX Dauphine in applied mathematics. Fellow of the Society of Financial Econometrics, Professor Scaillet research expertise is in the area of derivatives pricing, econometric theory and econometrics applied to finance and insurance. He has published several papers in top journals in econometrics and finance, and co-authored a book on financial econometrics. He has been one of the winners of the bi-annual award for the best paper published in the Journal of Empirical Finance on the topic of quantitative risk management and of the Banque Privee Espirito Santo award prize on the topic of mutual fund performance. He is an elected fellow of the Society of Financial Econometrics, and associate editor of several leading academic journals in econometrics, statistics, banking and finance. He is a long-term advisor for the research teams of BNP Paribas located in Paris and London.

Bio of discussant:
Marcelo C. Medeiros is Professor of Economics at the Pontifical Catholic University of Rio de Janeiro (PUC-Rio). Marcelo has a BA, MSc. and PhD degrees in Electrical Engineering from PUC-Rio, with an emphasis in Statistics, Optimization and Control Theory. His area of research is econometrics and data science, and he is particularly interested in the intersection between econometric/statistical theory and cutting-edge machine learning tools. He focuses his research both on theoretical developments as well as empirical applications in finance, macroeconomics, forecasting, and the evaluation of public policies, among other areas. Marcelo was elected Fellow of the Society of Financial Econometrics (SoFiE) in 2022 and serves as Associate Editor for the Journal of Business and Economic Statistics and the Journal of Financial Econometrics. Marcelo has published more than 50 papers in international peer-reviewed journals such as, for example, the Journal of the American Statistical Association, the Journal of Econometrics, the Journal of Business and Economic Statistics, Econometric Theory, the International Journal of Forecasting, and the Journal of Banking and Finance. Finally, Marcelo also serves as an external consultant for firms in Brazil and abroad.

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