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Pricing Weather Derivatives
Author(s) -
Richards Timothy J.,
Manfredo Mark R.,
Sanders Dwight R.
Publication year - 2004
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.1111/j.0002-9092.2004.00649.x
Subject(s) - heteroscedasticity , mean reversion , autoregressive model , economics , valuation of options , econometrics , monte carlo method , black–scholes model , brownian motion , mathematics , volatility (finance) , statistics
This article presents a general method for pricing weather derivatives. Specification tests find that a temperature series for Fresno, CA follows a mean‐reverting Brownian motion process with discrete jumps and autoregressive conditional heteroscedastic errors. Based on this process, we define an equilibrium pricing model for cooling degree day weather options. Comparing option prices estimated with three methods: a traditional burn‐rate approach, a Black‐Scholes‐Merton approximation, and an equilibrium Monte Carlo simulation reveals significant differences. Equilibrium prices are preferred on theoretical grounds, so are used to demonstrate the usefulness of weather derivatives as risk management tools for California specialty crop growers.