Bayesian Analysis of Moving Average Stochastic Volatility Models
Author | : Stefanos Dimitrakopoulos |
Publisher | : |
Total Pages | : 28 |
Release | : 2017 |
ISBN-10 | : OCLC:1305293202 |
ISBN-13 | : |
Rating | : 4/5 ( Downloads) |
Download or read book Bayesian Analysis of Moving Average Stochastic Volatility Models written by Stefanos Dimitrakopoulos and published by . This book was released on 2017 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a moving average stochastic volatility in mean model and a moving average stochastic volatility model with leverage. For parameter estimation, we develop efficient Markov chain Monte Carlo algorithms and illustrate our methods, using simulated data and a real data set. We compare the proposed specifications against several competing stochastic volatility models, using marginal likelihoods and the observed-data Deviance information criterion. We find that the moving average stochastic volatility model with leverage has better fit to our daily return series than various standard benchmarks.