Multivariate Fractionally Integrated APARCH Modeling of Stock Market Volatility: A multi-country study

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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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Discussion Paper Series ; No. 472

Classification and Topics

• Classification: Wirtschaft ; Estimation: General ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Model Evaluation, Validation, and Selection
• Subject: Asymmetric Power ARCH ; Fractional integration ; Stock returns ; Volatility forecast evaluation ; Kapitaleinkommen ; Börsenkurs ; Volatilität ; Korrelation ; ARCH-Modell ; Multivariate Analyse ; Theorie ; Schätzung ; Industrieländer

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Conrad, Christian ; Karanasos, Menelaos ; Zeng, Ning
• Event: Veröffentlichung
• (who): University of Heidelberg, Department of Economics
• (where): Heidelberg
• (when): 2008

Further information

• Handle: http://hdl.handle.net/10419/127293
• Last update: 10.03.2025, 11:43 AM CET