Journal of Risk

Optimal hedge ratios based on Markov-switching dynamic copula models

Jinzhi Li

  • This paper uses the Skewed-t stochastic volatility model to capture volatility patterns of the returns.
  • It captures the dynamic dependence structure by Markov-switching dynamic copula.
  • The paper also obtains the optimal futures hedge ratios and derives better hedging effectiveness via the Markov-switching Gaussian copula model.

This paper investigates optimal futures hedge ratios in stock markets. We use univariate skewed t stochastic volatility (SV) models to capture the time-varying (TV) volatility of our data and set up Markov-switching (MS) copula models to derive the dynamic dependence structure. According to the variance minimization method, we obtain optimal hedge ratios for the CSI 300 Index spot and futures in China’s stock market. We examine the hedging performance of various models and compare their effectiveness with the most common dynamic copula hedging models, including Patton’s TV copula and Engle’s dynamic conditional correlation (DCC) copula models. The empirical results show that the proposed MS dynamic copula models derive better hedging effectiveness than the corresponding dynamic copula models. The hedge ratios constructed by the MS time-varying (MSTV) Gaussian copula model demonstrate the best performance in terms of variance reduction.

Sorry, our subscription options are not loading right now

Please try again later. Get in touch with our customer services team if this issue persists.

New to View our subscription options

You need to sign in to use this feature. If you don’t have a account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here