Bayesian Unit-Root Testing in Stochastic Volatility Models
在随机波动率模型中使用贝叶斯方法检验不可观测波动率的单位根，基于后验几率比和马尔可夫链蒙特卡洛近似，模拟显示对中等样本量有效，并在七个市场指数中拒绝单位根假设，台湾TWSI存在非平稳证据。
This article uses a Bayesian unit-root test in stochastic volatility models. The time series of interest is the volatility that is unobservable. The unit-root testing is based on the posterior odds ratio, which is approximated by Markov-chain Monte Carlo methods. Simulations show that the testing procedure is efficient for moderate sample size. The unit-root hypothesis is rejected in seven market indexes, and some evidence of nonstationarity is observed in the TWSI of Taiwan.