A Haar-Fisz technique for locally stationary volatility estimation

Fryzlewicz, Piotr ORCID: 0000-0002-9676-902X, Sapatinas, Theofanis and Subba Rao, Suhasini (2006) A Haar-Fisz technique for locally stationary volatility estimation. Biometrika, 93 (3). pp. 687-704. ISSN 0006-3444

Preview

PDF Download (350kB) | Preview

Abstract

We consider a locally stationary model for financial log-returns whereby the returns are independent and the volatility is a piecewise-constant function with jumps of an unknown number and locations, defined on a compact interval to enable a meaningful estimation theory. We demonstrate that the model explains well the common characteristics of log-returns. We propose a new wavelet thresholding algorithm for volatility estimation in this model, in which Haar wavelets are combined with the variance-stabilising Fisz transform. The resulting volatility estimator is mean-square consistent with a near-parametric rate, does not require any pre-estimates, is rapidly computable and is easily implemented. We also discuss important variations on the choice of estimation parameters. We show that our approach both gives a very good fit to selected currency exchange datasets, and achieves accurate long- and short-term volatility forecasts in comparison to the GARCH(1, 1) and moving window techniques.

Item Type:	Article
Official URL:	http://biomet.oxfordjournals.org/
Additional Information:	© 2006 The Authors
Divisions:	Statistics
Subjects:	H Social Sciences > HA Statistics
Date Deposited:	18 Sep 2009 11:41
Last Modified:	11 Apr 2024 22:21
URI:	http://eprints.lse.ac.uk/id/eprint/25225

Actions (login required)

View Item