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Volatility exposure for strategic asset allocation

Author

Listed:
  • Marie Briere
  • Alexandre Burgues
  • Ombretta Signori
Abstract
Brière, Burgues, and Signori examine the advantages of incorporating strategic exposure to equity volatility into the investment opportunity set of a long-term equity investor. They consider two standard volatility investments: implied volatility and volatility risk premium strategies. An analytical framework, which offers pragmatic solutions for longterm investors who seek exposure to volatility, is used to calibrate and assess the risk - return profiles of portfolios.The benefit of volatility exposure for a conventional portfolio is shown through a mean-modified Value at Risk portfolio optimization. A pure volatility investment makes it possible to partially hedge downside equity risk and thus reduce the risk profile of a portfolio, while an investment in the volatility risk premium substantially increases returns for a given level of risk. A well-calibrated combination of the two strategies enhances both the absolute and risk-adjusted returns of a portfolio.

Suggested Citation

  • Marie Briere & Alexandre Burgues & Ombretta Signori, 2010. "Volatility exposure for strategic asset allocation," ULB Institutional Repository 2013/169642, ULB -- Universite Libre de Bruxelles.
    • Handle: RePEc:ulb:ulbeco:2013/169642
    Note: SCOPUS: ar.j
    as

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    References listed on IDEAS

    as
    1. Eric Jondeau & Michael Rockinger, 2006. "Optimal Portfolio Allocation under Higher Moments," European Financial Management, European Financial Management Association, vol. 12(1), pages 29-55, January.
    2. Gurdip Bakshi & Nikunj Kapadia, 2003. "Delta-Hedged Gains and the Negative Market Volatility Risk Premium," The Review of Financial Studies, Society for Financial Studies, vol. 16(2), pages 527-566.
    3. repec:bla:jfinan:v:59:y:2004:i:2:p:711-753 is not listed on IDEAS
    4. Eric Jondeau & Michael Rockinger, 2006. "The Economic Value of Distributional Timing," Swiss Finance Institute Research Paper Series 06-35, Swiss Finance Institute.
    5. Campbell Harvey & John Liechty & Merrill Liechty & Peter Muller, 2010. "Portfolio selection with higher moments," Quantitative Finance, Taylor & Francis Journals, vol. 10(5), pages 469-485.
    6. Massimo Guidolin & Allan Timmerman, 2005. "Optimal portfolio choice under regime switching, skew and kurtosis preferences," Working Papers 2005-006, Federal Reserve Bank of St. Louis.
    7. Vikas Agarwal, 2004. "Risks and Portfolio Decisions Involving Hedge Funds," The Review of Financial Studies, Society for Financial Studies, vol. 17(1), pages 63-98.
    8. Reinhold Hafner & Martin Wallmeier, 2007. "Volatility as an Asset Class: European Evidence," The European Journal of Finance, Taylor & Francis Journals, vol. 13(7), pages 621-644.
    9. Chunhachinda, Pornchai & Dandapani, Krishnan & Hamid, Shahid & Prakash, Arun J., 1997. "Portfolio selection and skewness: Evidence from international stock markets," Journal of Banking & Finance, Elsevier, vol. 21(2), pages 143-167, February.
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    More about this item

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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