Multivariate Lévy models: calibration and pricing

Giovanni Amici (), Paolo Brandimarte, Francesco Messeri and Patrizia Semeraro
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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

OR Spectrum: Quantitative Approaches in Management, 2025, vol. 47, issue 4, No 8, 1379-1420

Abstract: 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.

Keywords: Multivariate Lévy processes; Calibration; Pricing; Dependence; Exotic derivatives (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s00291-025-00815-0

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