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Risk Evaluating for Subdiffusive Option Price Model with Gamma Subordinator
Örebro University, Örebro University School of Business. Department of Mathematics, National University of Kyiv-Mohyla Academy, Kyiv, Ukraine.ORCID iD: 0000-0002-7652-8157
Örebro University, Örebro University School of Business. Department of Mathematics, National University of Kyiv-Mohyla Academy, Kyiv, Ukraine.ORCID iD: 0000-0002-5576-3756
Department of Mathematics, National University of Kyiv-Mohyla Academy, Kyiv, Ukraine.
2024 (English)In: Mathematical and Statistical Methods for Actuarial Sciences and Finance, MAF2024: Conference proceedings / [ed] Marco Corazza; Frédéric Gannon; Florence Legros; Claudio Pizzi; Vincent Touzé, Springer, 2024, p. 286-291Conference paper, Published paper (Refereed)
Abstract [en]

The article focuses on Value-at-risk measuring for options in situations characterized by the lack of liquidity when the underlying stock price has motionless periods. A similar behavior can be observed in physical systems exhibiting sub-diffusion. In the considered sub-diffusive model, the bond movement and stock process are time-changed by the stochastic clock with gamma subordinator. In the model, the two techniques for option pricing were considered. The first very common approach for the time-changed model is to find option prices as the discounted expected payoff under the risk-neutral measure. The second technique for option pricing is based on a fractional version of what is called Dupire's equation. The Value-at-Risk evaluating procedure for the proposed model was discussed and we show that this procedure is based on the Fractional Fokker-Planck equation (FFPE).

Place, publisher, year, edition, pages
Springer, 2024. p. 286-291
Keywords [en]
Option pricing, subdiffusion, Value-at-risk, Gamma subordinator
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:oru:diva-116497DOI: 10.1007/978-3-031-64273-9_47ISI: 001299654100047ISBN: 9783031642753 (print)ISBN: 9783031642739 (electronic)ISBN: 9783031642722 (print)OAI: oai:DiVA.org:oru-116497DiVA, id: diva2:1904442
Conference
International Conference of the Mathematical and Statistical Methods for Actuarial Sciences and Finance (MAF 2024), Le Havre, France, April 4-6, 2024
Funder
Knowledge Foundation, 20220099; 20220115
Note

Nataliya Shchestyuk acknowledges financial support from the project "Portfolio management for illiquid markets" (Dnr: 20220099) funded by the Knowledge Foundation. Svitlana Drin acknowledges financial support from the Knowledge Foundation Grant (Dnr: 20220115).

Available from: 2024-10-09 Created: 2024-10-09 Last updated: 2024-10-09Bibliographically approved

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Shchestyuk, NataliyaDrin, Svitlana

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