IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1103.4943.html
   My bibliography  Save this paper

An Empirical Analysis of Dynamic Multiscale Hedging using Wavelet Decomposition

Author

Listed:
  • Thomas Conlon
  • John Cotter

Abstract

This 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.

Suggested Citation

  • Thomas Conlon & John Cotter, 2011. "An Empirical Analysis of Dynamic Multiscale Hedging using Wavelet Decomposition," Papers 1103.4943, arXiv.org.
  • Handle: RePEc:arx:papers:1103.4943
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1103.4943
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Christie-David, Rohan & Chaudhry, Mukesh, 2001. "Coskewness and cokurtosis in futures markets," Journal of Empirical Finance, Elsevier, vol. 8(1), pages 55-81, March.
    2. Kim, Sangbae & In, Francis, 2005. "The relationship between stock returns and inflation: new evidence from wavelet analysis," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 435-444, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mara Madaleno & Carlos Pinho, 2010. "Hedging Performance and Multiscale Relationships in the German Electricity Spot and Futures Markets," JRFM, MDPI, vol. 3(1), pages 1-37, December.
    2. Zied Ftiti & Aviral Tiwari & Amél Belanès & Khaled Guesmi, 2015. "Tests of Financial Market Contagion: Evolutionary Cospectral Analysis Versus Wavelet Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 46(4), pages 575-611, December.
    3. Refk Selmi & Christos Kollias & Stephanos Papadamou & Rangan Gupta, 2017. "A Copula-Based Quantile-on-Quantile Regression Approach to Modeling Dependence Structure between Stock and Bond Returns: Evidence from Historical Data of India, South Africa, UK and US," Working Papers 201747, University of Pretoria, Department of Economics.
    4. Michis, Antonis A., 2014. "Investing in gold: Individual asset risk in the long run," Finance Research Letters, Elsevier, vol. 11(4), pages 369-374.
    5. Alexander Eastman & Brian Lucey, 2008. "Skewness and asymmetry in futures returns and volumes," Applied Financial Economics, Taylor & Francis Journals, vol. 18(10), pages 777-800.
    6. Marcos Albuquerque Junior & José António Filipe & Paulo de Melo Jorge Neto & Cristiano da Costa da Silva, 2021. "Assessing the Time-Frequency Co-Movements among the Five Largest Engineering Consulting Companies: A Wavelet-Base Metrics of Contagion and VaR Ratio," Mathematics, MDPI, vol. 9(5), pages 1-16, March.
    7. In, Francis & Kim, Sangbae & Gençay, Ramazan, 2011. "Investment horizon effect on asset allocation between value and growth strategies," Economic Modelling, Elsevier, vol. 28(4), pages 1489-1497, July.
    8. repec:ipg:wpaper:2014-108 is not listed on IDEAS
    9. Lin, Fu-Lai & Chen, Yu-Fen & Yang, Sheng-Yung, 2016. "Does the value of US dollar matter with the price of oil and gold? A dynamic analysis from time–frequency space," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 59-71.
    10. Kilponen, Juha & Verona, Fabio, 2016. "Testing the Q theory of investment in the frequency domain," Research Discussion Papers 32/2016, Bank of Finland.
    11. Kregždė Arvydas & Kišonaitė Karolina, 2018. "Co-movements of Lithuanian and Central European Stock Markets Across Different Time Horizons: A Wavelet Approach," Ekonomika (Economics), Sciendo, vol. 97(2), pages 55-69, December.
    12. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    13. Hassan Farazmand & Amin Mansouri & Morteza Afghah, 2014. "Choosing the best type of wavelet: Case study-business cycle in Iran," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 4(5), pages 293-314, May.
    14. Aloui, Chaker & Jammazi, Rania, 2015. "Dependence and risk assessment for oil prices and exchange rate portfolios: A wavelet based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 62-86.
    15. repec:zbw:bofrdp:2018_007 is not listed on IDEAS
    16. Dash, Saumya Ranjan & Maitra, Debasish, 2019. "The relationship between emerging and developed market sentiment: A wavelet-based time-frequency analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 135-150.
    17. Ayadi, Mohamed A. & Cao, Xu & Lazrak, Skander & Wang, Yan, 2019. "Do idiosyncratic skewness and kurtosis really matter?," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    18. Gazi Salah Uddin & Aviral Kumar Tiwari, 2013. "Measuring co-movement of oil price and exchange rate differential in Bangladesh," Economics Bulletin, AccessEcon, vol. 33(3), pages 1922-1930.
    19. Saumitra Bhaduri, 2016. "Revisiting the Growth–Inflation Nexus: A Wavelet Analysis," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 45(1), pages 79-89, February.
    20. He, Kaijian & Lai, Kin Keung & Yen, Jerome, 2011. "Value-at-risk estimation of crude oil price using MCA based transient risk modeling approach," Energy Economics, Elsevier, vol. 33(5), pages 903-911, September.
    21. Chi‐Hsiou Hung, 2008. "Return Predictability of Higher‐Moment CAPM Market Models," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 35(7‐8), pages 998-1022, September.
    22. Farouk, Faizal & Masih, Mansur, 2016. "Are there profit (returns) in Shariah-compliant exchange traded funds? The multiscale propensity," Research in International Business and Finance, Elsevier, vol. 38(C), pages 360-375.

    More about this item

    JEL classification:

    • 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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1103.4943. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.