Forecasting International Stock Market Variances

75 Pages Posted: 17 May 2024

See all articles by Geert Bekaert

Geert Bekaert

Columbia University - Columbia Business School, Finance

Nancy R. Xu

Boston College, Carroll School of Management

Tiange Ye

University of Southern California - Marshall School of Business

Date Written: May 16, 2024

Abstract

We examine 320 different forecasting models for international monthly stock return volatilities, using high frequency realized variances and the implied option variance as the predictor variables. We evaluate linear and non-linear models, and logarithmic transformed and weighted least squares estimation approaches. A logarithmically transformed Corsi (2009) model combined with the option implied variance (“lm4 log”) is robustly, across countries and time, among the best forecasting models. It also survives tests using panel models and international variables. When alternative models (such as models including negative returns) have better performance, the forecasts they generate are extremely highly correlated with those of the “lm4 log” model.

Keywords: Realized variance, implied volatility, international stock market, volatility forecasting

JEL Classification: C58, F30, G10, G17

Suggested Citation

Bekaert, Geert and Xu, Nancy R. and Ye, Tiange, Forecasting International Stock Market Variances (May 16, 2024). Available at SSRN: https://ssrn.com/abstract=4831547 or http://dx.doi.org/10.2139/ssrn.4831547

Geert Bekaert (Contact Author)

Columbia University - Columbia Business School, Finance ( email )

NY
United States

Nancy R. Xu

Boston College, Carroll School of Management ( email )

Carroll School of Management
140 Commonwealth Avenue
Chestnut Hill, MA 02467-3808
United States

HOME PAGE: http://www.nancyxu.net

Tiange Ye

University of Southern California - Marshall School of Business ( email )

701 Exposition Blvd
Los Angeles, CA 90089
United States
90007 (Fax)

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