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

Loann Desboulets

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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.

Keywords: non-parametric; Multivariate GARCH; dynamic correlation; PCA (search for similar items in EconPapers)
Date: 2017-10
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-02059302
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Working Paper: Co-movements in Market Prices and Fundamentals: A Semiparametric Multivariate GARCH Approach (2017)
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