Are there Structural Breaks in Realized Volatility?

摘要：

Constructed from high-frequency data,realized volatility (RV) provides an efficient estimate of the unobserved volatility of financial markets. This paper uses a Bayesian approach to investigate the evidence for structural breaks in reduced form time-series models of RV. We focus on the popular heterogeneous autoregressive (HAR) models of the logarithm of realized volatility. Using Monte Carlo simulations we demonstrate that our estimation approach is e?ective in identifying and dating structural breaks. Applied to daily S&P 500 data,we find strong evidence of a single structural break in log(RV ). The main e?ect of the break is on the long-run mean and variance of log-volatility.

关键词： change point marginal likelihood gibbs sampling

作者: Chun Liu John M.Maheu

作者单位: Dept.of Economics University of Toronto

会议类型: 国际会议

会议名称: 2007年中国国际金融年会

会议地点: 成都

会议语种:英文

在线出版日期: 2007-07-09（万方平台首次上网日期，不代表论文的发表时间）