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Multivariate L\'evy Models: Calibration and Pricing

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Listed:
  • Giovanni Amici
  • Paolo Brandimarte
  • Francesco Messeri
  • Patrizia Semeraro

Abstract

The goal of this paper is to investigate how the marginal and dependence structures of a variety of multivariate L\'evy models affect calibration and pricing. To this aim, we study the approaches of Luciano and Semeraro (2010) and Ballotta and Bonfiglioli (2016) to construct multivariate processes. We explore several calibration methods that can be used to fine-tune the models, and that deal with the observed trade-off between marginal and correlation fit. We carry out a thorough empirical analysis to evaluate the ability of the models to fit market data, price exotic derivatives, and embed a rich dependence structure. By merging theoretical aspects with the results of the empirical test, we provide tools to make suitable decisions about the models and calibration techniques to employ in a real context.

Suggested Citation

  • Giovanni Amici & Paolo Brandimarte & Francesco Messeri & Patrizia Semeraro, 2023. "Multivariate L\'evy Models: Calibration and Pricing," Papers 2303.13346, arXiv.org, revised Jul 2023.
    • Handle: RePEc:arx:papers:2303.13346
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    References listed on IDEAS

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    2. Marina Marena & Andrea Romeo & Patrizia Semeraro, 2018. "Multivariate Factor-Based Processes With Sato Margins," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(01), pages 1-30, February.
    3. Laura Ballotta & Efrem Bonfiglioli, 2016. "Multivariate asset models using Lévy processes and applications," The European Journal of Finance, Taylor & Francis Journals, vol. 22(13), pages 1320-1350, October.
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