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Multivariate Lévy models: calibration and pricing

Author

Listed:
  • Giovanni Amici

    (Politecnico di Torino, Department of Mathematical Sciences)

  • Paolo Brandimarte

    (Politecnico di Torino, Department of Mathematical Sciences)

  • Francesco Messeri

    (Intesa Sanpaolo Risk Management IMI CIB, Model Development and Integration Senior Specialist)

  • Patrizia Semeraro

    (Politecnico di Torino, Department of Mathematical Sciences)

Abstract

The goal of this paper is to investigate how the marginal and dependence structures of a variety of multivariate Lévy models affect calibration and pricing. To this aim, we study the approaches of Luciano and Semeraro (J Comput Appl Math 233:1937–1953, 2010) and Ballotta and Bonfiglioli (Eur J Financ 22:1320–1350, 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, 2025. "Multivariate Lévy models: calibration and pricing," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 47(4), pages 1379-1420, December.
    • Handle: RePEc:spr:orspec:v:47:y:2025:i:4:d:10.1007_s00291-025-00815-0
    DOI: 10.1007/s00291-025-00815-0
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