Bayesian Analysis of Moving Average Stochastic Volatility Models

Bayesian Analysis of Moving Average Stochastic Volatility Models
Author :
Publisher :
Total Pages : 28
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ISBN-10 : OCLC:1305293202
ISBN-13 :
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Book Synopsis Bayesian Analysis of Moving Average Stochastic Volatility Models by : Stefanos Dimitrakopoulos

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.


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