Bayesian Unit-Root Testing in Stochastic Volatility Models
提出一种在随机波动率模型中进行贝叶斯单位根检验的方法，通过后验优势比和马尔可夫链蒙特卡洛近似，模拟显示中等样本量下有效，并应用于七个市场指数，发现台湾TWSI存在非平稳性。
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.