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Minimizing volatility increases large risks

Author

Listed:
  • D. Sornette

    (CNRS-University of Nice and UCLA)

  • J. V. Andersen

    (Nordita, Copenhagen)

  • P. Simonetti

    (USC)

Abstract

We introduce a faithful representation of the heavy tail multivariate distribution of asset returns, as parsimonous as the Gaussian framework. Using calculation techniques of functional integration and Feynman diagrams borrowed from particle physics, we characterize precisely, through its cumulants of high order, the distribution of wealth variations of a portfolio composed of an arbitrary mixture of assets. The portfolio which minimizes the variance, i.e. the relatively small risks, often increases larger risks as measured by higher normalized cumulants and by the Value-at-risk.

Suggested Citation

  • D. Sornette & J. V. Andersen & P. Simonetti, 1998. "Minimizing volatility increases large risks," Papers cond-mat/9811292, arXiv.org.
    • Handle: RePEc:arx:papers:cond-mat/9811292
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    Cited by:

    1. J. V. Andersen & D. Sornette, 1999. "Have your cake and eat it too: increasing returns while lowering large risks!," Papers cond-mat/9907217, arXiv.org.

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