Bayesian semiparametric stochastic volatility modeling
نویسندگان
چکیده
منابع مشابه
Bayesian semiparametric stochastic volatility modeling
This paper extends the existing fully parametric Bayesian literature on stochastic volatility to allow for more general return distributions. Instead of specifying a particular distribution for the return innovations, nonparametric Bayesian methods are used to flexibly model the distribution’s skewness and kurtosis while volatility dynamics follow a parametric structure. Our Bayesian approach p...
متن کاملSemiparametric Asymmetric Stochastic Volatility∗
This paper extends the stochastic volatility with leverage model, where returns are correlated with volatility, by flexibly modeling the bivariate distribution of the return and volatility innovations nonparametrically. The novelty of the paper is in modeling the unknown distribution with an infinite ordered mixture of bivariate normals with mean zero, but whose mixture probabilities and covari...
متن کاملBayesian analysis of GARCH and stochastic volatility: modeling
This paper develops a Bayesian model comparison for two broad major classes of varying volatility model, GARCH and stochastic volatility (SV) models on financial time series. The leverage effect, jumps and heavy-tailed errors are incorporated into the two models. For estimation, the efficient Markov chain Monte Carlo methods are developed and the model comparisons are examined based on the marg...
متن کاملChapter on Bayesian Inference for Stochastic Volatility Modeling
This chapter reviews the major contributions over the last two decades to the literature on the Bayesian analysis of stochastic volatility (SV) models (univariate and multivariate). Bayesian inference is performed by tailoring Markov chain Monte Carlo (MCMC) or sequential Monte Carlo (SMC) schemes that take into account the specific modeling characteristics. The popular univariate stochastic vo...
متن کاملEfficient Semiparametric Garch Modeling of Financial Volatility
We consider a class of semiparametric GARCH models with additive autoregressive components linked together by a dynamic coefficient. We propose estimators for the additive components and the dynamic coefficient based on spline smoothing. The estimation procedure involves only a small number of least squares operations, thus it is computationally efficient. Under regularity conditions, the propo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Econometrics
سال: 2010
ISSN: 0304-4076
DOI: 10.1016/j.jeconom.2010.01.014