Multivariate Lévy models: calibration and pricing
研究了多种多元Lévy模型的边际和依赖结构如何影响校准与定价，通过实证分析比较模型拟合市场数据、定价奇异衍生品的能力，为实际应用中的模型选择提供指导。
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.