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Financial weather derivatives for corn production in Northern China: A comparison of pricing methods

Baojing Sun and Gerrit van Kooten

Journal of Empirical Finance, 2015, vol. 32, issue C, 201-209

Abstract: The focus in this study is on the pricing of financial derivatives for hedging weather risks in crop production. Employing data from an earlier study, we compare different methods for pricing weather derivative options based on growing degree days (GDDs). We employ average daily temperatures to derive GDDs using three approaches: (1) An econometric approach with a sine function; (2) Monte Carlo simulation with a sine function and three methods to estimate the mean-reversion parameter; and (3) a historic approach (burn analysis) based on a 10-year moving average of GDDs. Results indicate that the historical average method provides the best fit, followed by the stochastic process with a high mean reversion speed, and, finally, the approach using the econometrically estimated sine function. Depending on the method used, premiums for weather derivative options vary from $21.27 to $24.39 per GDD index contract.

Keywords: Agricultural finance; Stochastic processes; Pricing weather options; Growing degree days for corn production (search for similar items in EconPapers)
JEL-codes: G11 G12 Q14 (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:32:y:2015:i:c:p:201-209

DOI: 10.1016/j.jempfin.2015.03.014

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Journal of Empirical Finance is currently edited by R. T. Baillie, F. C. Palm, Th. J. Vermaelen and C. C. P. Wolff

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