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Weather derivatives pricing using regim switching models
Linköping University, Department of Mathematics, Mathematical Statistics . Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Mathematics, Computational Mathematics. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-2681-8965
Linköping University, Department of Mathematics, Mathematical Statistics . Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-9896-4438
Linköping University, Department of Mathematics, Mathematical Statistics . Linköping University, Faculty of Science & Engineering.
2017 (English)Report (Other academic)
Abstract [en]

In this study we discuss the pricing of weather derivatives whose underlying weather variable is temperature. The dynamics of temperature in this study follows a two state regime switching model with a heteroskedastic mean reverting process as the base regime and a shifted regime defined by Brownian motion with mean different from zero. We develop the mathematical formulas for pricing futures contract on heating degree days (HDDs), cooling degree days (CDDs) and cumulative average temperature (CAT) indices. We also present the mathematical expressions for pricing the corresponding options on futures contracts for the same temperature indices. The local volatility nature of the model in the base regime captures very well the dynamics of the underlying process, thus leading to a better pricing processes for temperature derivatives contracts written on various index variables. We provide the description of Montecarlo simulation method for pricing weather derivatives under this model and use it to price a few weather derivatives call option contracts.

Place, publisher, year, edition, pages
2017. , p. 19
Series
LiTH-MAT-R, ISSN 0348-2960 ; 2017/04
Keywords [en]
Weather derivatives, Arbitrage-free pricing, Regime switching, Monte Carlo Simulation, Option Pricing
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:liu:diva-135484ISRN: LiTH-MAT-R--2017/04--SELibris ID: 20167257OAI: oai:DiVA.org:liu-135484DiVA, id: diva2:1082101
Available from: 2017-03-15 Created: 2017-03-15 Last updated: 2017-04-12Bibliographically approved

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