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Wavelet multiscale analysis for Hedge Funds: Scaling and strategies

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  • Conlon, T.
  • Crane, M.
  • Ruskin, H.J.

Abstract

The wide acceptance of Hedge Funds by Institutional Investors and Pension Funds has led to an explosive growth in assets under management. These investors are drawn to Hedge Funds due to the seemingly low correlation with traditional investments and the attractive returns. The correlations and market risk (the Beta in the Capital Asset Pricing Model) of Hedge Funds are generally calculated using monthly returns data, which may produce misleading results as Hedge Funds often hold illiquid exchange-traded securities or difficult to price over-the-counter securities. In this paper, the Maximum Overlap Discrete Wavelet Transform (MODWT) is applied to measure the scaling properties of Hedge Fund correlation and market risk with respect to the S&P 500. It is found that the level of correlation and market risk varies greatly according to the strategy studied and the time scale examined. Finally, the effects of scaling properties on the risk profile of a portfolio made up of Hedge Funds is studied using correlation matrices calculated over different time horizons.

Suggested Citation

  • Conlon, T. & Crane, M. & Ruskin, H.J., 2008. "Wavelet multiscale analysis for Hedge Funds: Scaling and strategies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5197-5204.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:21:p:5197-5204
    DOI: 10.1016/j.physa.2008.05.046
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    References listed on IDEAS

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    1. Bouchaud,Jean-Philippe & Potters,Marc, 2003. "Theory of Financial Risk and Derivative Pricing," Cambridge Books, Cambridge University Press, number 9780521819169, October.
    2. Gençay, Ramazan & Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon J., 2001. "An Introduction to Wavelets and Other Filtering Methods in Finance and Economics," Elsevier Monographs, Elsevier, edition 1, number 9780122796708.
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    Cited by:

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    8. Bales, Stephan, 2022. "Sovereign and bank dependence in the eurozone: A multi-scale approach using wavelet-network analysis," International Review of Financial Analysis, Elsevier, vol. 83(C).
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    10. Chakrabarty, Anindya & De, Anupam & Gunasekaran, Angappa & Dubey, Rameshwar, 2015. "Investment horizon heterogeneity and wavelet: Overview and further research directions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 45-61.
    11. Anindya Chakrabarty & Anupam De & Gautam Bandyopadhyay, 2016. "Horizon heterogeneity, institutional constraint and managerial myopia: a multi-frequency perspective on ELSS," International Journal of Business Excellence, Inderscience Enterprises Ltd, vol. 9(1), pages 18-47.

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