Multivariate dependence between stock and commodity markets, a Vine approach

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I investigate the multivariate dependence between price returns for commodities from different sectors (energy, agriculture, precious metals and industrial metals ) with some major equities (SP500, FTSE10, DAX30, CAC40, MSCI China and MSCI India). The sample runs from January 1993 to February 2016 and I explore different sub-samples more in details. For that I use the Regular Vine Copula model as it is more flexible than GARCH-type models in the modelling of complex dependency patterns by arranging a tree structure to explore multiple correlations between the variables. The empirical results suggest that dependencies
fluctuate and change each time depending on the period considered. And this is not just related to the financial crisis but also to the effect of the 'financialization' of commodity markets. In addition, there is a low co-movements across equities and commodities in particular for precious metals and agriculture sectors which confirm their position as a safe-haven. The link between the stock market
and industrial metals and energy related commodities is stronger than with the remaining two sectors,
specially for industrial metals in the chinese case, and it remains high even after the crisis. For further
details, I use the Vector Error Correction model to study their long-run and short-run causality. The efficiency of the Vine copula model have been tested using a risk management analysis based on the Value at Risk (VaR) measure and it seems to outperform the other classical method considered (covariance-variance).

Author(s):

Manel Soury    
Aix Marseille School of economics
France