-frequency data, in line with IT developments, enables the use of more information to estimate not only the variance (volatility), but … with respect to the bandwidth selection as well as the sampling frequency selection. The main finding is that the kernel … bandwidth is strongly related to the sampling frequency at the slow-time-time scale when applying a two-scale estimator, while …

state-observation sampling (SOS) filter, for general state-space models with intractable observation densities. Second, we …

of the volatility coefficient of a stochastic differential equation. We postulate a histogram-type prior on the … volatility with piecewise constant realisations on bins forming a partition of the time interval. The values on the bins are … assigned an inverse Gamma Markov chain (IGMC) prior. Posterior inference is straightforward to implement via Gibbs sampling, as …

on high-frequency stock trading volumes and realized volatility forecasts demonstrate the usefulness of the proposed …

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 …

with the noisy rational expectations hypothesis. We find that in contrast to theory, for horizons close to two years, there … relationship becomes one-to-one, as the theory would predict …