An empirical analysis of dynamic multiscale hedging using wavelet decomposition
AbstractThis paper investigates the hedging effectiveness of a dynamic moving window OLS hedging model, formed using wavelet decomposed time-series. The wavelet transform is applied to calculate the appropriate dynamic minimum-variance hedge ratio for various hedging horizons for a number of assets. The effectiveness of the dynamic multiscale hedging strategy is then tested, both in- and out-of-sample, using standard variance reduction and expanded to include a downside risk metric, the time horizon dependent Value-at-Risk. Measured using variance reduction, the effectiveness converges to one at longer scales, while a measure of VaR reduction indicates a portion of residual risk remains at all scales. Analysis of the hedge portfolio distributions indicate that this unhedged tail risk is related to excess portfolio kurtosis found at all scales.
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Bibliographic InfoArticle provided by John Wiley & Sons, Ltd. in its journal Journal of Futures Markets.
Volume (Year): 32 (2012)
Issue (Month): 3 (03)
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Web page: http://www.interscience.wiley.com/jpages/0270-7314/
Other versions of this item:
- Thomas Conlon & John Cotter, 2011. "An Empirical Analysis of Dynamic Multiscale Hedging using Wavelet Decomposition," Working Papers 201104, Geary Institute, University College Dublin.
- Thomas Conlon & John Cotter, 2011. "An Empirical Analysis of Dynamic Multiscale Hedging using Wavelet Decomposition," Papers 1103.4943, arXiv.org.
- C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
- D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
- L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
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- Thomas Conlon & John Cotter, 2012.
"Downside risk and the energy hedger's horizon,"
201219, Geary Institute, University College Dublin.
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