The relationship between risk and return is one of the most studied topics in finance. The majority of the literature … is based on a linear, parametric relationship between expected returns and conditional volatility. This paper models the …-realized variance. We find strong robust evidence of volatility feedback in monthly data. Once volatility feedback is accounted for …

The volatility implied by observed market prices as a function of the strike and time to maturity form an Implied … Volatility Surface (IV S). Practical applications require reducing the dimension and characterize its dynamics through a small … investigating long range dependence in the factor loadings series. Our result reveals that shocks to volatility persist for a very …

The volatility implied by observed market prices as a function of the strike and time to maturity form an Implied … Volatility Surface (IVS). Practical applications require reducing the dimension and characterize its dynamics through a small … investigating long range dependence in the factor loadings series. Our result reveals that shocks to volatility persist for a very …

parametric approach utilizing a Stochastic-Volatility-Jump-Diffusion (SVJD) model, estimated with MCMC and extended with Particle … method may be biased in the case when large outlier jumps occur in the time series as well as when the stochastic volatility …

This paper presents a method for Bayesian nonparametric analysis of the return distribution in a stochastic volatility … series and two stock index return series. We find that estimates of volatility using the model can differ dramatically from …

A Bayesian semiparametric stochastic volatility model for financial data is developed. This estimates the return … between the returns and changes in volatility, the leverage effect. An efficient MCMC algorithm for inference is described …

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

suggested by new growth theory, while addressing the variable selection problem by means of Bayesian model averaging …. Controlling for variable selection uncertainty, we confirm the evidence in favor of new growth theory presented in several earlier …