Derivatives, especially equity and volatility options, contain valuable and oftentimes essential information for … estimating stochastic volatility models. Absent strong assumptions, their typically highly nonlinear pricing dependence on the … jointly accounts for stock returns as well as prices of equity and volatility options. Finally, we provide numerical results …

We propose a new variational approximation of the joint posterior distribution of the log-volatility in the context of … proposed methodology with an application of a 96-variable VAR with stochastic volatility to measure global bank network …

In an affine term structure framework with stochastic volatility, we derive the characteristic function of the log swap … swap rates and swaption premiums, model parameters are estimated using square-root unscented Kalman filter. We investigate …

regressions. Asymmetry and tail expectations are found to be subsumed in volatility expectations and significant co …

for the implied volatility surface of S&P500 index options data. …

-varying parameter vector autoregression with stochastic volatility developed by Cogley and Sargent (2005) and Primiceri (2005), CSP …

This work deals with multivariate stochastic volatility models, which account for a time-varying variance … the volatility level. We apply a full Bayesian inference approach, which relies upon Sequential Monte Carlo (SMC) for …

gap inflation persistence to a UC model that already has stochastic volatility (SV) afflicting trend and gap inflation …