Are There Structural Breaks in Realized Volatility?
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Constructed from high-frequency data, realized volatility (RV) provides an
accurate 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, and 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). Copyright The Author 2008. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: email@example.com., Oxford University Press.
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