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Stochastic Model Genetic Programming: Deriving Pricing Equations for Rainfall Weather Derivatives

Cramer, Sam, Kampouridis, Michael, Freitas, Alex A., Alexandridis, Antonis (2019) Stochastic Model Genetic Programming: Deriving Pricing Equations for Rainfall Weather Derivatives. Swarm and Evolutionary Computation, 46 . pp. 184-200. ISSN 2210-6502. E-ISSN 2210-6510. (doi:10.1016/j.swevo.2019.01.008)

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Abstract

Rainfall derivatives are in their infancy since starting trading on the Chicago Mercantile Exchange (CME) in 2011.

the literature. In this paper, we propose a novel Genetic Programming (GP) algorithm for pricing contracts. Our

of rainfall, which allows us to probabilistically transform rainfall predictions from the risky world to the risk-neutral

namely a seasonal component and an autoregressive component. To create the stochastic nature of an equation for

by SMGP in terms of rainfall predictive accuracy and in terms of pricing performance on 42 cities from Europe and the

Model trees, k-Nearest Neighbors, Support Vector Regression, Radial Basis Function), and two statistical methods,

show that the proposed algorithm is able to statistically outperform all other algorithms.

Item Type: Article
DOI/Identification number: 10.1016/j.swevo.2019.01.008
Uncontrolled keywords: Weather derivatives, rainfall, pricing, stochastic model genetic programming
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Divisions: Faculties > Sciences > School of Computing
Faculties > Social Sciences > Kent Business School
Depositing User: Michael Kampouridis
Date Deposited: 30 Jan 2019 09:43 UTC
Last Modified: 07 Feb 2020 00:00 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/72082 (The current URI for this page, for reference purposes)
Kampouridis, Michael: https://orcid.org/0000-0003-0047-7565
Freitas, Alex A.: https://orcid.org/0000-0001-9825-4700
Alexandridis, Antonis: https://orcid.org/0000-0001-6448-1593
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