incorporates stochastic volatility, long-run risks in consumption and dividends, and Epstein-Zin preferences. Utilizing Bayesian …-term real risk-free interest rate, real consumption growth, and real dividend growth. Our results indicate that, over short and …

general class of discrete-time stochastic volatility (SV) models, characterized by both a leverage effect and jumps in returns … provides a feasible basis for undertaking the nontrivial task of model comparison. Furthermore, we introduce new volatility … model, namely SV-GARCH which attempts to bridge the gap between GARCH and stochastic volatility specifications. In nesting …

and has important implications for risk management, volatility forecasting and option pricing …The paper proposes a self-exciting asset pricing model that takes into account co-jumps between prices and volatility …

Aiming at financial applications, we study the problem of learning the volatility under market microstructure noise … the volatility function a priori as piecewise constant. Its prior is specified via the inverse Gamma Markov chain …. Sampling from the posterior is accomplished by incorporating the Forward Filtering Backward Simulation algorithm in the Gibbs …

. This model is applied to the time series of daily realized volatility of some indices, and is compared to similar …