A closed-form approximation for pricing temperature-based weather derivatives
This paper develops analytical distributions of temperature indices on which temperature derivatives are written. If the deviations of daily temperatures from their expected values are modelled as an Ornstein-Uhlenbeck process with timevarying variance, then the distributions of the temperature index on which the derivative is written is the sum of truncated, correlated Gaussian deviates. The key result of this paper is to provide an analytical approximation to the distribution of this sum, thus allowing the accurate computation of payoffs without the need for any simulation. A data set comprising average daily temperature spanning over a hundred years for four Australian cities is used to demonstrate the efficacy of this approach for estimating the payoffs to temperature derivatives. It is demonstrated that expected payoffs computed directly from historical records are a particularly poor approach to the problem when there are trends in underlying average daily temperature. It is shown that the proposed analytical approach is superior to historical pricing.
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|Item Type:||Journal Article|
|Keywords:||Weather Derivatives, Temperature Models, Cooling-Degree Days, Distributions for Correlated Variables|
|Divisions:||Current > QUT Faculties and Divisions > QUT Business School
Current > Schools > School of Economics & Finance
|Copyright Owner:||Copyright © 2013 A. E. Clements et al|
|Copyright Statement:||This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.|
|Deposited On:||23 Sep 2013 22:30|
|Last Modified:||10 Dec 2013 15:15|
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