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Detection of arbitrage in a market with multi-asset derivatives and known risk-neutral marginals

Author

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  • Bertrand Tavin

    (EM - EMLyon Business School)

Abstract

In this paper we study the existence of arbitrage opportunities in a multi-asset market when risk-neutral marginal distributions of asset prices are known. We first propose an intuitive characterization of the absence of arbitrage opportunities in terms of copula functions. We then address the problem of detecting the presence of arbitrage by formalizing its resolution in two distinct ways that are both suitable for the use of optimization algorithms. The first method is valid in the general multivariate case and is based on Bernstein copulas that are dense in the set of all copula functions. The second one is easier to work with but is only valid in the bivariate case. It relies on results about improved Fréchet–Hoeffding bounds in presence of additional information. For both methods, details of implementation steps and empirical applications are provided.

Suggested Citation

  • Bertrand Tavin, 2015. "Detection of arbitrage in a market with multi-asset derivatives and known risk-neutral marginals," Post-Print hal-02313250, HAL.
    • Handle: RePEc:hal:journl:hal-02313250
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    Citations

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    Cited by:

    1. Papapantoleon Antonis & Yanez Sarmiento Paulo, 2021. "Detection of arbitrage opportunities in multi-asset derivatives markets," Dependence Modeling, De Gruyter, vol. 9(1), pages 439-459, January.
    2. Daniel Bartl & Michael Kupper & Thibaut Lux & Antonis Papapantoleon & Stephan Eckstein, 2017. "Marginal and dependence uncertainty: bounds, optimal transport, and sharpness," Papers 1709.00641, arXiv.org, revised Aug 2018.
    3. Antonis Papapantoleon & Paulo Yanez Sarmiento, 2020. "Detection of arbitrage opportunities in multi-asset derivatives markets," Papers 2002.06227, arXiv.org, revised Nov 2021.
    4. Ariel Neufeld & Antonis Papapantoleon & Qikun Xiang, 2023. "Model-Free Bounds for Multi-Asset Options Using Option-Implied Information and Their Exact Computation," Management Science, INFORMS, vol. 69(4), pages 2051-2068, April.
    5. Guo, Nan & Wang, Fang & Yang, Jingping, 2017. "Remarks on composite Bernstein copula and its application to credit risk analysis," Insurance: Mathematics and Economics, Elsevier, vol. 77(C), pages 38-48.
    6. Luca De Gennaro Aquino & Carole Bernard, 2019. "Bounds on Multi-asset Derivatives via Neural Networks," Papers 1911.05523, arXiv.org, revised Nov 2020.

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