Information Flow Dependence in Return and Trading Volume Across Different Stocks

24 Pages Posted: 10 Apr 2019

Date Written: March 21, 2019

Abstract

We develop a multivariate return and trading volume model, where each stock’s system is driven by latent information arrivals in continuous time. The arrivals contain idiosyncratic and cross-relevant information, which provides both return and trading volume dependence. Conditional on the accumulated information, returns are jointly normal and correlated, which implies a second layer of dependence in the return dimension. Using a sample of nine common stocks, we show that trading volume significantly adds to the operationalization of the latent information flow process driving the contemporaneous return distribution. The dependence parameter estimates provide significant and interpretable degrees of information flow dependence across all results. Portfolio risk measurement applications are extended by conditioning on the level of trading volume, e.g. reflecting stress, leading to an accurate risk quantification.

Keywords: information flow, trading volume, dependence modeling, risk measurement, Lévy copulas, weak multivariate subordination

Suggested Citation

Michaelsen, Markus, Information Flow Dependence in Return and Trading Volume Across Different Stocks (March 21, 2019). Available at SSRN: https://ssrn.com/abstract=3357537 or http://dx.doi.org/10.2139/ssrn.3357537

Markus Michaelsen (Contact Author)

Universität Hamburg ( email )

Von-Melle-Park 5
Hamburg, 20146
Germany

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