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Co-movements in Market Prices and Fundamentals: A Semiparametric Multivariate GARCH Approach

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  • Loann David Denis Desboulets

    (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

Abstract

In this paper we investigate on Multivariate GARCH models to assess the co-movements between stock prices of american firms listed on main markets and fundamentals. Co-movements can be seen as correlations. The latter are usually estimated via standard GARCH models such as the Dynamic Conditional Correlation (Engle, 2002) or the Baba-Engle-Kraft-Kroner (Baba et al., 1990). Nevertheless more flexible models such as the Orthogonal GARCH of Alexander (2001) can be used as well. We also introduce a new Semi-parametric Orthogonal GARCH as a natural non-linear extension of the Orthogonal GARCH. A Montecarlo simulation is conducted to evaluate finite sample performance of each model before applying them to the data. Empirical results show evidence that during crises, prices are less correlated with fundamentals that in normal periods.

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  • Loann David Denis Desboulets, 2017. "Co-movements in Market Prices and Fundamentals: A Semiparametric Multivariate GARCH Approach," Working Papers halshs-02059302, HAL.
    • Handle: RePEc:hal:wpaper:halshs-02059302
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-02059302
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