A Hidden Markov Model (HMM) is used to model the VIX (the Cboe Volatility Index). A 4- state Gaussian mixture is fitted … Hedge Index). The results presented here show promising application in modelling and predicting volatility, as well as … identifying current volatility regimes predominating the market …

We present a self-consistent model for explosive financial bubbles, which combines a mean-reverting volatility process … started at least 4 years earlier. We confirm the validity and universality of the volatility-confined LPPL model on seven …

capturing interest rate risk. The so-called Stochastic Volatility Nelson-Siegel (SVNS) model allows for stochastic volatility in … evidence for time-varying volatility in the yield factors. This is mostly true for the level and slope volatility revealing … also the highest persistence. It turns out that the inclusion of stochastic volatility improves the model's goodness …

In this paper, I study the drop of real GDP volatility which has been observed in the United States during the postwar … disaggregated only up to 10 sectors. Blanchard and Simon (2001) come to the same result. Using a new estimation method and more … this in order to get, for each observation period, an estimation of the covariance matrix of the sectoral growth rates …

We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors …

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 …

methods. The effects ofseveral modelcharacteristics (unit roots, GARCH, stochastic volatility, heavy taileddisturbance …

The persistent nature of equity volatility is investigated by means of a multi-factor stochastic volatility model with … model a time-varying generalization of the HAR model for the realized volatility series. It emerges that during the recent … stochastic volatility model suggest that the change in the dynamic structure of the realized volatility during the financial …

We propose a novel method to estimate dynamic equilibrium models with stochastic volatility. First, we characterize the … exploits the profusion of shocks in stochastic volatility models, is versatile and computationally tractable even in large … methods to estimate a business cycle model of the U.S. economy with both stochastic volatility and parameter drifting in …

We propose a moving average stochastic volatility in mean model and a moving average stochastic volatility model with … leverage. For parameter estimation, we develop efficient Markov chain Monte Carlo algorithms and illustrate our methods, using … simulated data and a real data set. We compare the proposed specifications against several competing stochastic volatility …