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Application of the Esscher Transform to Pricing Forward Contracts on Energy Markets in a Fuzzy Environment

The paper is dedicated to modeling electricity spot prices and pricing forward contracts on energy markets. The underlying dynamics of electricity spot prices is governed by a stochastic mean reverting diffusion with jumps having mixed-exponential distribution. Application of financial mathematics a...

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Detalles Bibliográficos
Autores principales: Nowak, Piotr, Pawłowski, Michał
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10048341/
https://www.ncbi.nlm.nih.gov/pubmed/36981415
http://dx.doi.org/10.3390/e25030527
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author Nowak, Piotr
Pawłowski, Michał
author_facet Nowak, Piotr
Pawłowski, Michał
author_sort Nowak, Piotr
collection PubMed
description The paper is dedicated to modeling electricity spot prices and pricing forward contracts on energy markets. The underlying dynamics of electricity spot prices is governed by a stochastic mean reverting diffusion with jumps having mixed-exponential distribution. Application of financial mathematics and stochastic methods enabled the derivation of the analytical formula for the forward contract’s price in a crisp case. Since the model parameters’ incertitude is considered, their fuzzy counterparts are introduced. Utilization of fuzzy arithmetic enabled deriving an analytical expression for the futures price and proposing a modified method for decision-making under uncertainty. Finally, numerical examples are analyzed to illustrate our pricing approach and the proposed financial decision-making method.
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spelling pubmed-100483412023-03-29 Application of the Esscher Transform to Pricing Forward Contracts on Energy Markets in a Fuzzy Environment Nowak, Piotr Pawłowski, Michał Entropy (Basel) Article The paper is dedicated to modeling electricity spot prices and pricing forward contracts on energy markets. The underlying dynamics of electricity spot prices is governed by a stochastic mean reverting diffusion with jumps having mixed-exponential distribution. Application of financial mathematics and stochastic methods enabled the derivation of the analytical formula for the forward contract’s price in a crisp case. Since the model parameters’ incertitude is considered, their fuzzy counterparts are introduced. Utilization of fuzzy arithmetic enabled deriving an analytical expression for the futures price and proposing a modified method for decision-making under uncertainty. Finally, numerical examples are analyzed to illustrate our pricing approach and the proposed financial decision-making method. MDPI 2023-03-18 /pmc/articles/PMC10048341/ /pubmed/36981415 http://dx.doi.org/10.3390/e25030527 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Nowak, Piotr
Pawłowski, Michał
Application of the Esscher Transform to Pricing Forward Contracts on Energy Markets in a Fuzzy Environment
title Application of the Esscher Transform to Pricing Forward Contracts on Energy Markets in a Fuzzy Environment
title_full Application of the Esscher Transform to Pricing Forward Contracts on Energy Markets in a Fuzzy Environment
title_fullStr Application of the Esscher Transform to Pricing Forward Contracts on Energy Markets in a Fuzzy Environment
title_full_unstemmed Application of the Esscher Transform to Pricing Forward Contracts on Energy Markets in a Fuzzy Environment
title_short Application of the Esscher Transform to Pricing Forward Contracts on Energy Markets in a Fuzzy Environment
title_sort application of the esscher transform to pricing forward contracts on energy markets in a fuzzy environment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10048341/
https://www.ncbi.nlm.nih.gov/pubmed/36981415
http://dx.doi.org/10.3390/e25030527
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