We are comparing two approaches for stochastic volatility and jumps estimation in the EUR/USD time series - the non …) using daily returns. We find that both of the methods do identify continuous stochastic volatility similarly, but they do … the continuous volatility) on the daily frequency. As an additional result we find strong evidence for jump size …

This paper proposes a parsimonious threshold stochastic volatility (SV) model for financial asset returns. Instead of … imposing a threshold value on the dynamics of the latent volatility process of the SV model, we assume that the innovation of … time-varying volatility of returns, but also can accommodate the asymmetric shape of conditional distribution of the …

evidence for stochastic intensity and stochastic volatility models based on Ornstein-Uhlenbeck processes. For our empirical …

-memory stochastic volatility model. We develop a new Bayesian estimator based on the Markov chain Monte Carlo sampler and the wavelet … joint posterior distribution. Unlike short-memory stochastic volatility models, long-memory stochastic volatility models do … quickly and efficiently from the near independent multivariate distribution of the long-memory volatility's wavelet …

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 …

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

section compares stochastic volatility models with GARCH. …