We use a multivariate generalized autoregressive heteroskedasticity model (M-GARCH) to examine three stock indexes and their associated futures prices: the New York Stock Exchange Composite, Standard and Poor's 500, and Toronto 35. The North American context is significant because markets in Canada and the United States share similar structures and regulatory environments. Our model allows examination of dependence in volatility as it captures time variation in volatility and cross-market influences. Estimated time-variation in volatility is significant, and the volatilities are highly positively correlated. Yet, we find that the correlation in North American index and futures markets has declined over time.
JEL classification: G10, G15
Key words: volatility dependence, M-GARCH
The authors acknowledge the financial support of the Social Sciences and Humanities Research Council of Canada. They also thank Ken Gilbert and Darren McIlwraith for research assistance and Zhuaxin Ding and an anonymous referee for helpful comments. The views expressed here are those of the authors and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. Any remaining errors are the authors' responsibility.
Please address questions regarding content to Marie D. Racine, School of Business and Economics, Wilfrid Laurier University, Waterloo, Ontario N2L 3C5, Canada, 519/884-0710 ext. 2776, firstname.lastname@example.org; or Lucy F. Ackert, Research Department, Federal Reserve Bank of Atlanta, 104 Marietta Street, NW, Atlanta, Georgia 30303-2713, 404/498-8783, email@example.com.
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