JSM 2005 - Toronto

Abstract #302318

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 462
Type: Invited
Date/Time: Thursday, August 11, 2005 : 8:30 AM to 10:20 AM
Sponsor: IMS
Abstract - #302318
Title: Wavelet-based Volatility Estimation for High-frequency Financial Data
Author(s): Yazhen Wang*+
Companies: University of Connecticut
Address: 215 Glenbrook Road, Storrs, CT, 06269,
Keywords: High-Frequency ; Jump ; Multiscale ; microstructure ; Volatility ; Wavelets
Abstract:

Volatilities of asset returns are pivotal for many issues in financial economics. The availability of high frequency intraday data allows us to accurately estimate stock volatility. Because asset prices often have jumps, and high-frequency data are contaminated with market microstructure noise, the common approach to estimating integrated volatility is to sample from available data and use the obtained subsample (a fraction of the original data) to compute realized volatility and realized bipower variation. In this paper, we propose wavelet-based multiscale methods to perform jump analysis in price processes and estimate integrated volatility and, if jump(s) occurs, recover jump variation. We establish asymptotic theory for the methods and study their efficiency for finite sample.

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Revised March 2005