Rainfall derivatives as a risk management tool for grain producers: daily model vs. index model.
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Uniwersytet Przyrodniczy we Wrocławiu
Submission date: 2019-12-11
Final revision date: 2020-01-11
Acceptance date: 2020-01-12
Publication date: 2020-06-06
Corresponding author
Ewa Broszkiewicz-Suwaj   

Uniwersytet Przyrodniczy we Wrocławiu
Acta Sci. Pol. Formatio Circumiectus 2020;19(1):13-20
Aim of the study:
The first weather derivatives appeared in 1996. Soon later such instruments began to be traded on the CME (Chicago Mercantile Exchange). The group of underlyings included indices related to temperature as well as the amount of precipitation. But the specificity of weather derivatives caused that the commodity exchanges stopped trading some of them. However, climate change is increasing the risk associated with adverse weather conditions. The grain producers sector is very exposed to this risk, which is why the subject of this work is to build a strategy to protect against the risk of low rainfall during the growing season of plants.

Material and methods:
The valuation of rainfall derivatives is made using Monte Carlo simulation for two types of models: a model based on daily rainfall value simulation and a model based on direct estimation of the index distribution. Then these instruments are used to build a hedging strategy against the risk of low yields in the Lower Silesian District. In the last step, the effectiveness of such a strategy is examined using percentage reduction in volatility of a secured portfolio and average squared loss.

Results and conclusions:
Based on the calculations we can conclude that the amount of precipitation is an important factor affecting the level of cereal yield. Therefore, it is reasonable for grain producers to apply hedging strategies against low rainfall. Additionally we derived that daily precipitation model used in the work underestimates the derivative instrument price while the model based on direct simulation of the index gives reasonable results.

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