Information Flow Dependence in Financial Markets
31 Pages Posted: 12 Oct 2017 Last revised: 21 Aug 2019
Date Written: June 11, 2018
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: Suggested Citation