Forecasting and Managing Correlation Risks

64 Pages Posted: 21 Nov 2022 Last revised: 1 Sep 2023

See all articles by Tim Bollerslev

Tim Bollerslev

Duke University - Finance; Duke University - Department of Economics; National Bureau of Economic Research (NBER)

Sophia Zhengzi Li

Rutgers, The State University of New Jersey - Rutgers Business School at Newark & New Brunswick

Yushan Tang

Nankai Business School, Nankai University

Date Written: September 1, 2023

Abstract

We propose a novel and easy-to-implement framework for forecasting correlation risks based on a large set of salient realized correlation features and the sparsity-encouraging LASSO technique. Considering the universe of S&P 500 stocks, we find that the new approach manifests in statistically superior out-of-sample forecasts compared to commonly used procedures. We further demonstrate how the forecasts translate into significant economic gains in the form of higher pairs trading profits, better equity premium predictions, more accurate portfolio risk targeting, and superior overall risk control and minimization.

Keywords: Correlation forecasting, high-frequency data, LASSO, risk targeting and control, pairs trading, equity premium prediction

JEL Classification: C13, C14, C52, C53, C55, C58

Suggested Citation

Bollerslev, Tim and Li, Sophia Zhengzi and Tang, Yushan, Forecasting and Managing Correlation Risks (September 1, 2023). Available at SSRN: https://ssrn.com/abstract=4281900 or http://dx.doi.org/10.2139/ssrn.4281900

Tim Bollerslev

Duke University - Finance ( email )

Durham, NC 27708-0120
United States
919-660-1846 (Phone)
919-684-8974 (Fax)

Duke University - Department of Economics

213 Social Sciences Building
Box 90097
Durham, NC 27708-0204
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Sophia Zhengzi Li (Contact Author)

Rutgers, The State University of New Jersey - Rutgers Business School at Newark & New Brunswick ( email )

100 Rockafeller Rd
Piscataway, NJ 08854
United States

HOME PAGE: http://https://sites.google.com/site/szlwebpage/

Yushan Tang

Nankai Business School, Nankai University ( email )

Balitai, 94 weijing Rd
Tianjin, 300071
China

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