Investigating the Intertemporal Risk-Return Relation in International Stock Markets with the Component GARCH Model

Federal Reserve Bank St. Louis Working Paper No. 2006-006

24 Pages Posted: 31 Jan 2006

See all articles by Hui Guo

Hui Guo

University of Cincinnati - Department of Finance - Real Estate

Christopher J. Neely

Federal Reserve Bank of St. Louis - Research Division

Date Written: January 2006

Abstract

We revisit the risk-return relation using the component GARCH model and international daily MSCI stock market data. In contrast with the previous evidence obtained from weekly and monthly data, daily data show that the relation is positive in almost all markets and often statistically significant. Likelihood ratio tests reject the standard GARCH model in favor of the component GARCH model, which strengthens the evidence for a positive risk-return tradeoff. Consistent with U.S. evidence, the long-run component of volatility is a more important determinant of the conditional equity premium than the short-run component for most international markets.

Keywords: GARCH-in-mean, Component GARCH, Risk-return relation, International stock market returns

JEL Classification: G10, G12

Suggested Citation

Guo, Hui and Neely, Christopher J., Investigating the Intertemporal Risk-Return Relation in International Stock Markets with the Component GARCH Model (January 2006). Federal Reserve Bank St. Louis Working Paper No. 2006-006, Available at SSRN: https://ssrn.com/abstract=878685 or http://dx.doi.org/10.2139/ssrn.878685

Hui Guo (Contact Author)

University of Cincinnati - Department of Finance - Real Estate ( email )

College of Business
418 Carl H. Lindner Hall
Cincinnati, OH 45221
United States
513.556.7077 (Phone)
513.556.0979 (Fax)

HOME PAGE: http://homepages.uc.edu/~guohu/

Christopher J. Neely

Federal Reserve Bank of St. Louis - Research Division ( email )

411 Locust St
Saint Louis, MO 63011
United States
314-444-8568 (Phone)
314-444-8731 (Fax)

HOME PAGE: http://www.stls.frb.org/research/econ/cneely/

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

Paper statistics

Downloads
185
Abstract Views
1,185
rank
202,503
PlumX Metrics