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Weather derivatives are becoming prominent features in multiasset class portfolios of alternative risk. The pricing of these securities is nonetheless challenging since it requires an incomplete market framework. We discuss… Click to show full abstract
Weather derivatives are becoming prominent features in multiasset class portfolios of alternative risk. The pricing of these securities is nonetheless challenging since it requires an incomplete market framework. We discuss pricing formulas for temperature-based weather derivative options, constructing mean reverting stochastic models for describing the dynamics of daily temperature with a constant speed of mean reversion for three cities. Truncated Fourier series are used to model the volatility, and assuming a constant market price of risk, we introduce a novel approach for estimating this constant, using Monte Carlo simulations.
Journal Title: Journal of the Optical Society of America
Year Published: 2020
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