back-testing models. We conclude by comparing in-sample and out-of-sample performances of complex volatility models. …

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

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 …

-BEKK model introduced by Engle and Kroner (1995) is employed to analyze the volatility transmission structure. We identify the … is observed. Furthermore we detect unidirectional volatility transmission from the futures to the spot market at highest …

stochastic volatility. Estimation of the model delivers measures of daily variation outperforming their non …When analysing the volatility related to high frequency financial data, mostly non-parametric approaches based on …

We propose a new methodology for structural estimation of dynamic discrete choice models. We combine the Dynamic … model becomes comparable to that of a static model. Another feature of our algorithm is that even though per solution-estimation … number of estimation iterations. This is how we help ease the "Curse of Dimensionality". We simulate and estimate several …

Empirical evidence suggests a sharp volatility decline of the growth in U.S. gross domestic product (GDP) in the mid …-1980s. Using Bayesian methods, we analyze whether a volatility reduction can also be detected for the German GDP. Since … statistical inference for volatility processes critically depends on the specification of the conditional mean we assume for our …

and multivariate Stochastic Volatility (SV) models for financial return series. EIS provides a highly generic and very … out ML-estimation of SV models as well as simulation smoothing where the latent volatilities are sampled at once. Based on …