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Analysis Of Effect Of Detrending Of Time-Scale Structure Of Financial Data Using Discrete Wavelet Transform

Author

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  • BRIAN J. W. FLEMING

    (Edinburgh Multidisciplinary Consortium for Advanced Nonlinear Analysis of Complex Systems, Department of Physics, Heriot-Watt University, Riccarton, Edinburgh EH14 4AS, UK)

  • DEJIN YU

    (Edinburgh Multidisciplinary Consortium for Advanced Nonlinear Analysis of Complex Systems, Department of Physics, Heriot-Watt University, Riccarton, Edinburgh EH14 4AS, UK)

  • ROBERT G. HARRISON

    (Edinburgh Multidisciplinary Consortium for Advanced Nonlinear Analysis of Complex Systems, Department of Physics, Heriot-Watt University, Riccarton, Edinburgh EH14 4AS, UK)

  • DAVID JUBB

    (Standard Life Investments, 1 George Street, Edinburgh EH2 2LL, UK)

Abstract

One of the key features of wavelet analysis is its ability to decompose non-stationary signals according to time and scale. In this work, we use discrete wavelets to analyze the influence of detrending techniques on the time-scale information structure of daily financial data. We examine the use of log returns, a linear trend and the Hodrick–Prescott (HP) filter. Quantitative measurements of information distortion are given using the mean-squared error (MSE) and correlation of the wavelet coefficients between the detrended and original data. We find that log returns and linear detrending are most distortional. We also conclude that the HP-filter is most effective, depending on appropriate selection of the filter parameter, λ, which is${\mathcal O} (10^{11})$for the given data set.

Suggested Citation

  • Brian J. W. Fleming & Dejin Yu & Robert G. Harrison & David Jubb, 2000. "Analysis Of Effect Of Detrending Of Time-Scale Structure Of Financial Data Using Discrete Wavelet Transform," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(03), pages 375-379.
    • Handle: RePEc:wsi:ijtafx:v:03:y:2000:i:03:n:s0219024900000231
    DOI: 10.1142/S0219024900000231
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    Cited by:

    1. Francis In & Sangbae Kim, 2012. "An Introduction to Wavelet Theory in Finance:A Wavelet Multiscale Approach," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8431, January.

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