ARANEDA, Axel A. and Marcelo J. VILLENA. Semiclassical Pricing of Variance Swaps in the CEV Model. Online. In Corazza, M., Perna, C., Pizzi, C., Sibillo, M. Mathematical and Statistical Methods for Actuarial Sciences and Finance. 1st ed. Cham: Springer, 2022, p. 25-30. ISBN 978-3-030-99637-6. Available from: https://dx.doi.org/10.1007/978-3-030-99638-3_5.
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Basic information
Original name Semiclassical Pricing of Variance Swaps in the CEV Model
Authors ARANEDA, Axel A. (152 Chile, belonging to the institution) and Marcelo J. VILLENA.
Edition 1. vyd. Cham, Mathematical and Statistical Methods for Actuarial Sciences and Finance. p. 25-30, 6 pp. 2022.
Publisher Springer
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 50206 Finance
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
WWW URL
RIV identification code RIV/00216224:14560/22:00125661
Organization unit Faculty of Economics and Administration
ISBN 978-3-030-99637-6
Doi http://dx.doi.org/10.1007/978-3-030-99638-3_5
Keywords in English Path Integral; CEV model; Variance swap
Tags topvydavatel
Tags International impact, Reviewed
Changed by Changed by: Axel Alejandro Araneda Barahona, Ph.D., učo 245643. Changed: 22/3/2023 02:28.
Abstract
Path integrals are a well-known tool in quantum mechanics and statistical physics. They could be used to derive the propagator or kernel of stochastic processes, analogous to solving the Fokker-Planck equation. In finance, they become an alternative tool to address the valuation of derivatives. Here, taking advantage of the hedging formula of the realized variance by means of the log contract, we use path integrals for the pricing of variance swaps under the Constant Elasticity of Variance (CEV) model, approximating analytically the propagator for the log contract by semiclassical arguments. Our results demonstrate that the semiclassical method provides an alternative and efficient computation which shows a high level of accuracy but at the same time lower execution times.
Links
EF18_053/0016952, research and development projectName: Postdoc2MUNI
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