Weather is an important factor for the economy and has a growing impact on businesses of many kinds. Companies that suffer serious losses in case of unfavorable weather are interested in hedging the weather risks. In this thesis weather derivatives are introduced which are a very useful instrument for hedging. Temperature based derivative contracts usually pay a compensation to the buyer if the temperature is unusually high or low on many days. This thesis focuses on such weather derivative contracts for agricultural enterprises in important regions of crop cultivating in the United States. The main aim is the pricing of these contracts. Since temperature does not follow a simple stochastic process, several complex Monte Carlo models for simulating temperature are calculated and discussed. Especially, the impacts of mean-reverting, autoregressive, variability, and jump component elements will be investigated. The simulation results will be compared with historical data and with recent reference data for analyzing how the contracts would have performed in later years. It will be shown how important it is to choose an appropriate model. Thereafter, methods for finding fair prices and the importance of the market price of risk are considered.
