Regime switching vine copula models for global equity and volatility indices

TL;DR

This paper introduces Markov-switching R-vine models to analyze the changing dependence structures between global equity and volatility indices across different continents, identifying distinct regimes of normal and abnormal market states.

Contribution

It is the first to model global dependence regimes between equity and volatility indices using regime-switching vine copulas, capturing dynamic shifts in dependence structures.

Findings

Identification of distinct normal and abnormal dependence regimes.

Detection of joint points indicating regime switches across global markets.

Validation of regime switching behavior in global equity and volatility indices.

Abstract

For nearly every major stock market there exist equity and implied volatility indices. These play important roles within finance: be it as a benchmark, a measure of general uncertainty or a way of investing or hedging. It is well known in the academic literature, that correlations and higher moments between different indices tend to vary in time. However, to the best of our knowledge, no one has yet considered a global setup including both, equity and implied volatility indices of various continents, and allowing for a changing dependence structure. We aim to close this gap by applying Markov-switching $R$-vine models to investigate the existence of different, global dependence regimes. In particular, we identify times of "normal" and "abnormal" states within a data set consisting of North-American, European and Asian indices. Our results confirm the existence of joint points in time at which global regime switching takes place.