Subsampled Factor Models for Asset Pricing: The Rise of Vasa

64 Pages Posted: 14 Apr 2020 Last revised: 2 Nov 2020

See all articles by Gianluca De Nard

Gianluca De Nard

University of Zurich - Department of Banking and Finance; New York University

Simon Hediger

University of Zurich - Department of Banking and Finance

Markus Leippold

University of Zurich - Department of Banking and Finance; University of Zurich - Faculty of Economics, Business Administration and Information Technology

Date Written: November 01, 2020

Abstract

We propose a new method, VASA, based on variable subsample aggregation of model predictions for equity returns using a large-dimensional set of factors. To demonstrate the effectiveness, robustness, and dimension reduction power of VASA, we perform a comparative analysis between state-of-the-art machine learning algorithms. As a performance measure, we explore not only the global predictive but also the stock-specific R2's and their distribution. While the global R2 indicates the average forecasting accuracy, we find that high variability in the stock-specific R2's can be detrimental for the portfolio performance, due to the higher prediction risk. Since VASA shows minimal variability, portfolios formed on this method outperform the portfolios based on more complicated methods like random forests and neural nets.

Keywords: Large-dimensional factor models, machine learning, return prediction, subagging, subsampling.

JEL Classification: C13, C30, C53, C58, G12, G17

Suggested Citation

De Nard, Gianluca and Hediger, Simon and Leippold, Markus, Subsampled Factor Models for Asset Pricing: The Rise of Vasa (November 01, 2020). Available at SSRN: https://ssrn.com/abstract=3557957 or http://dx.doi.org/10.2139/ssrn.3557957

Gianluca De Nard (Contact Author)

University of Zurich - Department of Banking and Finance ( email )

Zürichbergstrasse 14
Zürich, Zürich CH-8032
Switzerland

HOME PAGE: http://denard.ch

New York University ( email )

Department of Finance
NYU Stern Volatility and Risk Institute
New York, NY
United States

HOME PAGE: http://https://vlab.stern.nyu.edu

Simon Hediger

University of Zurich - Department of Banking and Finance ( email )

Plattenstrasse 14
Zurich
Switzerland

Markus Leippold

University of Zurich - Department of Banking and Finance ( email )

Plattenstrasse 14
Zürich, 8032
Switzerland

University of Zurich - Faculty of Economics, Business Administration and Information Technology ( email )

Plattenstrasse 14
Zürich, 8032
Switzerland

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

Paper statistics

Downloads
317
Abstract Views
1,121
rank
117,954
PlumX Metrics