BAYESIAN UNIT-ROOT TESTING INSTOCHASTIC VOLATILITY MODELS WITHCORRELATED ERRORS

Authors : Zeynep İ KALAYLIOĞLU, Burak BOZDEMİR, Sujit K GHOSH

Pages : 659-669

View : 22 | Download : 8

Publication Date : 2013-06-01

Article Type : Other Papers

Abstract :A series of returns are often modeled using stochastic volatility models. Many observed financial series exhibit unit-root non-stationarybehavior in the latent ARinsert ignore into journalissuearticles values(1); volatility process and tests for a unit-rootbecome necessary, especially when the error process of the returns iscorrelated with the error terms of the ARinsert ignore into journalissuearticles values(1); process. In this paper, wedevelop a class of priors that assigns positive prior probability on thenon-stationary region, employ credible interval for the test, and showthat Markov Chain Monte Carlo methods can be implemented usingstandard software. Several practical scenarios and real examples areexplored to investigate the performance of our method.
Keywords : Contemporaneous financial correlation, Markov chain Monte Carlo, Gibbssampling, unit root test, WinBUGS, financial data2000 AMS Classification 62M10, 62P20