This article approaches some of the current rainfall derivatives pricing and operational challenges through an empirical application to Comunidad Valenciana, Spain. Regarding the former, two different issues are addressed. First, we examine the rightness of suggesting the Gamma distribution to price rainfall contracts, which is the alternative chosen by previous authors applying the Index Value Simulation technique. This is done for the purpose of determining whether the consideration and comparison of other alternatives may lead to more accurate valuation results. Concretely, two different distributions, in addition to the Gamma, are proposed: the exponential and the mixed exponential, whose fits are assessed through the Kolmogorov–Smirnov/Lilliefors test and graphical analyses. The outcomes attained indicate that this selection process leads indeed to a precise generation of the rainfall index’s moments. Next, we examine the viability of using a unique distribution to model the rainfall risk of regions located nearby, since this would considerably decrease valuation complexity. Our analysis shows that the most convenient choice depends on the period and location considered, although the mixed exponential appears as a reasonable option in most cases. Finally, a relevant operational challenge related to geographical basis risk is approached. Concretely, an evaluation of this type of risk among the locations studied is conducted. The results attained indicate that, given the insufficient degree of correlation between nearby locations, rainfall risk hedging measures may rely on compound derivatives referred to several neighbor stations.

中文翻译：

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应对基于降雨的天气衍生产品定价和运营挑战

本文通过对西班牙Comunidad Valenciana的经验应用来解决当前的一些降雨衍生品定价和运营挑战。关于前者，解决了两个不同的问题。首先，我们研究了将Gamma分布建议为价格降雨合同的正确性，这是以前的作者使用“指数值模拟”技术选择的替代方法。这样做是为了确定是否考虑和比较其他备选方案可能会导致更准确的评估结果。具体而言，除了伽马值外，还提出了两种不同的分布：指数分布和混合指数分布，其拟合度通过Kolmogorov–Smirnov / Lilliefors检验和图形分析进行评估。所获得的结果表明，这种选择过程确实导致了降雨指数矩的精确生成。接下来，我们研究了使用唯一分布对附近地区降雨风险建模的可行性，因为这将大大降低估值复杂性。我们的分析表明，最方便的选择取决于所考虑的时间段和位置，尽管在大多数情况下，混合指数似乎是一个合理的选择。最后，解决了与地理基础风险相关的相关操作挑战。具体地，在所研究的位置之间进行这种类型的风险的评估。获得的结果表明，鉴于附近位置之间的相关程度不足，