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 …

accounts for time variation in macroeconomic volatility, known as the great moderation. In particular, we consider an … volatility processes and mixture distributions for the irregular components and the common cycle disturbances enable us to … that time-varying volatility is only present in the a selection of idiosyncratic components while the coefficients driving …

contribution to overall realized variation and their contribution to predictive regressions of realized volatility. We find … individual stocks. -- Itô semi-martingale ; realized volatility ; jumps ; quadratic volatility ; multipower variation ; tripower …

volatility clustering in clock-time returns, even when trade- time returns are Gaussian. Finally, we highlight conditions on the … directing process which are required in order to generate proper volatility dynamics while simultaneously matching the … unconditional distribution of returns. In-sample fitting and out-of-sample realized volatility forecasting demonstrate the strength …

relating the growing importance of ETFs to increased market volatility and rising equity valuations. We estimate quantile … cointegration models using Standard & Poor's 500 Index (S&P 500) and Chicago Board Options Exchange volatility Index (VIX) data for …

volatility equation and corresponding value-at-risk predictions. We find that most GARCH coefficients and associated predictions …

Heteroscedasticity) volatility dynamics. DCS models are robust to extreme observations, whereas standard financial time series models are … observations, stochastic seasonality with dynamic amplitude, and volatility dynamics. These seasonality dynamics of the GTQ/USD are …

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