Information Flow Dependence in Financial Markets

31 Pages Posted: 12 Oct 2017 Last revised: 21 Aug 2019

Date Written: June 11, 2018

Abstract

In response to empirical evidence, we propose a continuous-time model for multivariate asset returns with a two-layered dependence structure. The price process is subject to multivariate information arrivals driving the market activity modeled by non-decreasing pure-jump Lévy processes. A Lévy copula determines the jump dependence and allows for a generic multivariate information flow with a flexible structure. Conditional on the information flow, asset returns are jointly normal. Within this setup, we provide an estimation framework based on maximum simulated likelihood. We apply novel multivariate models to equity data and obtain estimates which meet an economic intuition with respect to the two-layered dependence structure.

Keywords: Lévy processes, Lévy copulas, dependence modeling, weak multivariate subordination, variance gamma, simulated likelihood

JEL Classification: C51, C58

Suggested Citation

Michaelsen, Markus, Information Flow Dependence in Financial Markets (June 11, 2018). Available at SSRN: https://ssrn.com/abstract=3051180 or http://dx.doi.org/10.2139/ssrn.3051180

Markus Michaelsen (Contact Author)

Universität Hamburg ( email )

Von-Melle-Park 5
Hamburg, 20146
Germany

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