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Are there Structural Breaks in Realized Volatility?

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Author Info
Chun Liu
John M Maheu

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Abstract

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 effective in identifying and dating structural breaks. Applied to daily S&P 500 data from 1993-2004, we find strong evidence of a structural break in early 1997. The main effect of the break is a reduction in the variance of log-volatility. The evidence of a break is robust to different models including a GARCH specification for the conditional variance of log(RV).

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Paper provided by University of Toronto, Department of Economics in its series Working Papers with number tecipa-304.

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Length: 41 pages
Date of creation: 18 Dec 2007
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Handle: RePEc:tor:tecipa:tecipa-304

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Related research
Keywords: realized volatility change point marginal likelihood Gibbs sampling GARCH

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Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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