more than a single regime, have performed substantially better than standard methods in terms of volatility and Value …

. Applying our model to high-frequency transaction data, we detect two distinct regimes in the intraday volatility process: a … dominant volatility regime that is observable throughout the trading day representing the risk-transferring trading activity of … investors, and a minor volatility regime that concentrates around market liquidity shocks which mainly capture impacts of firm …

A new model - the factorial hidden Markov volatility (FHMV) model - is proposed for financial returns and their latent … variances. It is also applicable to model directly realized variances. Volatility is modeled as a product of three components: a … Markov chain driving volatility persistence, an independent discrete process capable of generating jumps in the volatility …

The transmission mechanisms of volatility between markets can be characterized within a new Markov Switching bivariate …

This paper investigates inference and volatility forecasting using a Markov switching heteroscedastic model with a fat …-tailed error distribution to analyze asymmetric effects on both the conditional mean and conditional volatility of financial time … work to incorporate Markov switching in the mean and variance simultaneously. Parameter estimation and inference are …

the weighting of lagged squared innovations for the estimation of future correlations and volatilities. When we account …

ARCH and stochastic volatility models. We consider two major dollar exchange rates, and we show that returns standardized …