Multivariate Fractionally Integrated APARCH Modeling of Stock Market Volatility: A Multi-Country Study

Tse (1998) proposes a model which combines the fractionally integrated GARCH formulation of Baillie, Bollerslev and Mikkelsen (1996) with the asymmetric power ARCH specification of Ding, Granger and Engle (1993). This paper analyzes the applicability of a multivariate constant conditional correlation version of the model to national stock market returns for eight countries. We find this multivariate specification to be generally applicable once power, leverage and long-memory effects are taken into consideration. In addition, we find that both the optimal fractional differencing parameter and power transformation are remarkably similar across countries. Out-of-sample evidence for the superior forecasting ability of the multivariate FIAPARCH framework is provided in terms of forecast error statistics and tests for equal forecast accuracy of the various models.

Keywords: Asymmetric Power ARCH, Fractional integration, Stock returns, Volatility forecast evaluation

JEL Classification: C13, C22, C52

Suggested Citation: Suggested Citation

Conrad, Christian and Karanasos, Menelaos and Zeng, Ning, Multivariate Fractionally Integrated APARCH Modeling of Stock Market Volatility: A Multi-Country Study (December 2009). Journal of Empirical Finance, Forthcoming, University of Heidelberg Department of Economics Discussion Paper No. 472 , Available at SSRN: https://ssrn.com/abstract=1191942 or http://dx.doi.org/10.2139/ssrn.1191942