Journal of Statistical and Econometric Methods

Empirical analysis of asymmetries and long memory among international stock market returns: A Multivariate FIAPARCH-DCC approach

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  •  Abstract

    This study examines the interdependence of four stock prices namely (KOSPI, NIKKEI225, SSE and MSCI). The aim of this paper is to examine how the dynamics of correlations between the major stock prices evolved from January 01, 2000 to December10, 2013. To this end, we adopt a dynamic conditional correlation (DCC) model into a multivariate Fractionally Integrated Asymmetric Power ARCH (FIAPARCH) framework, which accounts for long memory, power effects, leverage terms and time varying correlations. The empirical findings indicate the evidence of time-varying comovement, a high persistence of the conditional correlation and the dynamic correlations revolve around a constant level and the dynamic process appears to be mean reverting. Moreover, the univariate FIAPARCH models are particularly useful in forecasting market risk exposure for synthetic portfolios of stocks and currencies.