We develop new procedures for maximum likelihood estimation of affine term structure models with spanned or unspanned … stochastic volatility. Our approach uses linear regression to reduce the dimension of the numerical optimization problem yet it … produces the same estimator as maximizing the likelihood. It improves the numerical behavior of estimation by eliminating …

volatility. The news component of volatility is not positively autocorrelated on these dates, since the news is released at a … these announcement dates, and (2) the persistence pattern of daily volatility is quite different around these days …

We develop a tractable and flexible stochastic volatility multi-factor model of the term structure of interest rates …

We develop and implement a new method for maximum likelihood estimation in closed-form of stochastic volatility models … unobservable volatility state, to an approximate likelihood procedure where the volatility state is replaced by the implied … volatility of a short dated at-the-money option. We find that the approximation results in a negligible loss of accuracy. We …

imposed in CIR-style models and models in which the state variables are the stochastic long-run mean and volatility of r …

We propose a novel method to estimate dynamic equilibrium models with stochastic volatility. First, we characterize the … exploits the profusion of shocks in stochastic volatility models, is versatile and computationally tractable even in large … methods to estimate a business cycle model of the U.S. economy with both stochastic volatility and parameter drifting in …