In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and … indices and foreign exchange rates. -- Stochastic volatility ; Markov chain Monte Carlo ; Metropolis-Hastings algorithm Jump …

and the short-run or transitory components of the volatility of daily stock market returns using bivariate mixture models …. For this purpose, the Standard bivariate mixture model of Tauchen and Pitts (1983) in which volatility and volume are … each endowed with their own dynamic behavior are allowed to direct volatility and volume. Since the latent information …

forecasting horizons. Therefore, a long memory volatility model compared to a short memory GARCH model does not appear to improve …

and the short-run or transitory components of the volatility of daily stock market returns using bivariate mixture models …. For this purpose, the Standard bivariate mixture model of Tauchen and Pitts (1983) in which volatility and volume are … each endowed with their own dynamic behavior are allowed to direct volatility and volume. Since the latent information …

volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algorithms for this type of model are …

prices caused by stochastic volatility. -- option pricing ; autoregression ; heteroskedasticity ; GARCH ; leverage effect …

We examined volatility spillover effects from five prominent global stock markets to India's stock market during the … and compare the results pre-and-post COVID-19. Results show that previous period news and volatility feeds the next period …'s volatility significantly and the volatility is found to be persistent. The analysis also shows that during the pre-COVID period …

In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and …