This paper proposes a range-based dynamic conditional correlation (DCC) model combined by the return-based DCC model and the conditional autoregressive range (CARR) model. The substantial gain in efficiency of volatility estimation can boost the accuracy for estimating time-varying covariances....

This study examines latent shifts in the conditional volatility and correlation for the U.S. stock and T-bond data using the two-state Markov-switching range-based volatility and correlation models. This paper comes up with clear evidence of volatility regime-switching in stock indices and...

We propose a more flexible range-based volatility model which can capture volatility process better than conventional GARCH approach. Considering the regime switching process is appropriate for dealing the structure change embedded in the time series data. Range-based volatility CARR model with...