Rainfall option impact on profits of the hospitality industry through scenario correlation and copulas
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This work introduces and empirically tests an option contract designed to manage rainfall risk of hospitality firms. It contributes to the literature on weather derivatives in tourism. We deal with a rainfall option designed to compensate for the lack of revenues caused by too much rain, which could have a negative impact on the hospitality industry business performances in the medium/long run. We concentrate on the typical question of pricing a rainfall option. We introduce a new model with the aim of improving the formulation of the price by considering the highly non-linear relationships between rain and business performances in a multidimensional framework. Such a model results from the integration of three essential elements: scenario correlation, copulas, and Monte Carlo techniques. The model is complemented by an experiment that focuses on Lake Garda, Italy, one of the most important tourist destinations in the summer period for international and Italian visitors. We consider the quantities of rainfall of Lake Garda in the years 2005–2014 and the business performances of 18 hotels operating there during the same period. Based on these data, we obtain multidimensional data. Then, the price of an option contract designed to hedge the decrease in revenues due to rainfall is assessed based on the refined and linked multidimensional data. Finally, an optimal number of contracts to be bought is suggested based on the minimization of the Earnings Before Interests and Taxes variability.
KeywordsRisk management Weather-sensitive hospitality firms Rainfall risk Rainfall options Monte Carlo techniques
JEL ClassificationG13 G32 L83 Z32 Z33
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