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De-noising option prices with the wavelet method

Haven, E and Liu, X and Shen, L (2012) 'De-noising option prices with the wavelet method.' European Journal of Operational Research, 222 (1). 104 - 112. ISSN 0377-2217

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Abstract

Financial time series are known to carry noise. Hence, techniques to de-noise such data deserve great attention. Wavelet analysis is widely used in science and engineering to de-noise data. In this paper we show, through the use of Monte Carlo simulations, the power of the wavelet method in the de-noising of option price data. We also find that the estimation of risk-neutral density functions and out-of-sample price forecasting is significantly improved after noise is removed using the wavelet method. © 2012 Elsevier B.V. All rights reserved.

Item Type: Article
Subjects: H Social Sciences > HG Finance
Divisions: Faculty of Social Sciences > Essex Business School
Faculty of Social Sciences > Essex Business School > Essex Finance Centre
Depositing User: Jim Jamieson
Date Deposited: 18 Dec 2012 14:30
Last Modified: 30 Jan 2019 16:17
URI: http://repository.essex.ac.uk/id/eprint/4781

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