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Hedging under multiple risk constraints

Author

Listed:
  • Ying Jiao

    (Université Claude Bernard – Lyon I)

  • Olivier Klopfenstein

    (EDF R&D)

  • Peter Tankov

    (Université Paris-Diderot (Paris 7))

Abstract

Motivated by the asset–liability management problems under shortfall risk constraints, we consider in a general discrete-time framework the problem of finding the least expensive portfolio whose shortfalls with respect to a given set of stochastic benchmarks are bounded by a specific shortfall risk measure. We first show how the price of this portfolio may be computed recursively by dynamic programming for different shortfall risk measures, in complete and incomplete markets. We then focus on the specific situation where the shortfall risk constraints are imposed at each period on the next-period shortfalls, and obtain explicit results. Finally, we apply our results to a realistic asset–liability management problem of an energy company, and show how the shortfall risk constraints affect the optimal hedging of liabilities.

Suggested Citation

  • Ying Jiao & Olivier Klopfenstein & Peter Tankov, 2017. "Hedging under multiple risk constraints," Finance and Stochastics, Springer, vol. 21(2), pages 361-396, April.
  • Handle: RePEc:spr:finsto:v:21:y:2017:i:2:d:10.1007_s00780-017-0326-6
    DOI: 10.1007/s00780-017-0326-6
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    References listed on IDEAS

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    Cited by:

    1. Anastasis Kratsios, 2019. "Partial Uncertainty and Applications to Risk-Averse Valuation," Papers 1909.13610, arXiv.org, revised Oct 2019.
    2. Cyril B'en'ezet & Jean-Franc{c}ois Chassagneux & Mohan Yang, 2023. "An optimal transport approach for the multiple quantile hedging problem," Papers 2308.01121, arXiv.org.
    3. Areski Cousin & Ying Jiao & Christian y Robert & Olivier David Zerbib, 2021. "Optimal asset allocation subject to withdrawal risk and solvency constraints," Working Papers hal-03244380, HAL.
    4. Balata, Alessandro & Ludkovski, Michael & Maheshwari, Aditya & Palczewski, Jan, 2021. "Statistical learning for probability-constrained stochastic optimal control," European Journal of Operational Research, Elsevier, vol. 290(2), pages 640-656.
    5. Alessandro Balata & Michael Ludkovski & Aditya Maheshwari & Jan Palczewski, 2019. "Statistical Learning for Probability-Constrained Stochastic Optimal Control," Papers 1905.00107, arXiv.org, revised Aug 2020.

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    More about this item

    Keywords

    Multiple risk constraints; Snell envelope; Dynamic programming; Shortfall risk; Asset–liability management;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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