文献详情
An Improved Bayesian Unit Root Test in Stochastic Volatility Models
文献类型：期刊
通讯作者：Li, Y (reprint author), Renmin Univ China, Hanqing Adv Inst Econ & Finance, Beijing 100872, Peoples R China.
期刊名称：ANNALS OF ECONOMICS AND FINANCE
年：2019
卷：20
期：1
页码：103-122
ISSN：1529-7373
关键词：Bayes factor; Markov chain Monte Carlo; Posterior odds ratio; Stochastic volatility models; Unit root testing
摘要：A new posterior odds analysis is developed to test for a unit root in volatility dynamics in the context of stochastic volatility models. Our analysis extends the Bayesian unit root test of So and Li (1999) in two important ways. First, a mixed informative prior distribution with a random weight is introduced for the Bayesian unit root testing in volatility. Second, a numerically more stable algorithm is introduced to compute Bayes factor, taking into account the special structure of the competi ...More
A new posterior odds analysis is developed to test for a unit root in volatility dynamics in the context of stochastic volatility models. Our analysis extends the Bayesian unit root test of So and Li (1999) in two important ways. First, a mixed informative prior distribution with a random weight is introduced for the Bayesian unit root testing in volatility. Second, a numerically more stable algorithm is introduced to compute Bayes factor, taking into account the special structure of the competing models. It can be shown that the approach introduced overcomes the problem of the diverging "size" in the marginal likelihood approach by So and Li (1999) and improves the "power" of the unit root test. A simulation study is used to investigate the finite sample performance of the improved method and an empirical study implements the proposed method and the unit root hypothesis in volatility is rejected. ...Hide

百度学术：An Improved Bayesian Unit Root Test in Stochastic Volatility Models
语言：外文
基金：Fundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central Universities; Research Funds of Renmin University of China [14XNI005]
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