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Multiscale Analysis of Stock Index Return Volatility

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  • Enrico Capobianco

    () (CWI, Kruislaan 413, 1098 SJ Amsterdam, the Netherlands)

Abstract

We present a study where wavelet approximation techniques and some related computational algorithms are applied to non-stationary high frequency financial times series. Wavelets represent a novel instrument as far as concerned applications in the finance setting, but have a great relevance in many domains, from physics to statistics. Thus, while one goal of the paper is to compare the numerical performance of global and local function optimizers, another goal is to try to show that ad hoc wavelet-based function dictionaries are very useful for financial modeling through signal decomposition and approximation. Detecting the latent dependence features which are typically found in high frequency financial returns is particularly important for the scope of proposing models which are able to achieve reliable results in parameter estimation and pointwise function prediction. We show that by pre-processing data with wavelet dictionaries we effectively account for hidden periodic components, whose discovery allows to attain and improve the feature extraction power. We refer to sparse approximation through the Matching Pursuit algorithm, thus handling the negative effects of covariance non-stationarity at very high frequencies.

Suggested Citation

  • Enrico Capobianco, 2004. "Multiscale Analysis of Stock Index Return Volatility," Computational Economics, Springer;Society for Computational Economics, vol. 23(3), pages 219-237, April.
  • Handle: RePEc:kap:compec:v:23:y:2004:i:3:p:219-237
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    Citations

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    Cited by:

    1. Viviana Fernandez & Brian M Lucey, 2006. "Portfolio management implications of volatility shifts: Evidence from simulated data," Documentos de Trabajo 219, Centro de Economía Aplicada, Universidad de Chile.
    2. Crowley, Patrick M., 2005. "An intuitive guide to wavelets for economists," Research Discussion Papers 1/2005, Bank of Finland.
    3. repec:hal:journl:halshs-00261514 is not listed on IDEAS
    4. Fernandez, Viviana & Lucey, Brian M., 2007. "Portfolio management under sudden changes in volatility and heterogeneous investment horizons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 612-624.
    5. Bai, Limiao & Yan, Sen & Zheng, Xiaolian & Chen, Ben M., 2015. "Market turning points forecasting using wavelet analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 184-197.
    6. Kravets Tatiana V., 2013. "Modelling Profitabilities of Stock Indices Using Methods of Wavelet Analysis," Business Inform, RESEARCH CENTRE FOR INDUSTRIAL DEVELOPMENT PROBLEMS of NAS (KHARKIV, UKRAINE), Kharkiv National University of Economics, issue 7, pages 104-109.
    7. Roger Bowden & Jennifer Zhu, 2010. "Multi-scale variation, path risk and long-term portfolio management," Quantitative Finance, Taylor & Francis Journals, vol. 10(7), pages 783-796.
    8. George Tzagkarakis & Juliana Caicedo-Llano & Thomas Dionysopoulos, 2016. "Time-Frequency Adapted Market Integration Measure Based on Hough Transformed Multiscale Decompositions," Computational Economics, Springer;Society for Computational Economics, vol. 48(1), pages 1-27, June.

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