An Efficient Stochastic Simulation Algorithm for Bayesian Unit Root Testing in Stochastic Volatility Models

被引：2
|
作者：
Li, Yong [2 ]
Ni, Zhongxin [1 ]
Zhang, Jie [3 ]
机构：
[1] Shanghai Univ, Sch Econ, Shanghai 200444, Peoples R China
[2] Sun Yat Sen Univ, Sch Business, Guangzhou 510275, Guangdong, Peoples R China
[3] Renmin Univ China, Inst Chinas Econ Reform Dev, Beijing 100872, Peoples R China
来源：
COMPUTATIONAL ECONOMICS | 2011年 / 37卷 / 03期
关键词：
Financial times series; Stochastic volatility models; Unit root testing; Bayes factor; Path sampling; MARGINAL LIKELIHOOD;
D O I：
10.1007/s10614-011-9252-4
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
In financial times series analysis, unit root test is one of the most important research issues. This paper is aimed to propose a new simple and efficient stochastic simulation algorithm for computing Bayes factor to detect the unit root of stochastic volatility models. The proposed algorithm is based on a classical thermodynamic integration technique named path sampling. Simulation studies show that the test procedure is efficient under moderate sample size. In the end, the performance of the proposed approach is investigated with a Monte Carlo simulation study and illustrated with a time series of S&P500 return data.
引用
收藏
页码：237 / 248
页数：12
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