Revisiting semidefinite programming approaches to options pricing: complexity and computational perspectives - Archive ouverte HAL
Article Dans Une Revue INFORMS Journal on Computing Année : 2023

Revisiting semidefinite programming approaches to options pricing: complexity and computational perspectives

Etienne de Klerk
  • Fonction : Auteur
  • PersonId : 1092851
Milan Korda
Jean-Bernard Lasserre
Victor Magron

Résumé

In this paper we consider the problem of finding bounds on the prices of options depending on multiple assets without assuming any underlying model on the price dynamics, but only the absence of arbitrage opportunities. We formulate this as a generalized moment problem and utilize the well-known Moment-Sum-of-Squares (SOS) hierarchy of Lasserre to obtain bounds on the range of the possible prices. A complementary approach (also due to Lasserre) is employed for comparison. We present several numerical examples to demonstrate the viability of our approach. The framework we consider makes it possible to incorporate different kinds of observable data, such as moment information, as well as observable prices of options on the assets of interest.
Fichier principal
Vignette du fichier
options_rev_arxiv_submission.pdf (233.6 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03429272 , version 1 (15-11-2021)
hal-03429272 , version 2 (11-03-2022)

Identifiants

Citer

Didier Henrion, Felix Kirschner, Etienne de Klerk, Milan Korda, Jean-Bernard Lasserre, et al.. Revisiting semidefinite programming approaches to options pricing: complexity and computational perspectives. INFORMS Journal on Computing, 2023, 35 (2), pp.265-517. ⟨10.1287/ijoc.2022.1220⟩. ⟨hal-03429272v2⟩
215 Consultations
159 Téléchargements

Altmetric

Partager

More