Andrea Martínez Salgueiro, Maria-Antonia Tarrazon-Rodon
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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.","PeriodicalId":45022,"journal":{"name":"Review of Derivatives Research","volume":"348 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2019-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Approaching rainfall-based weather derivatives pricing and operational challenges\",\"authors\":\"Andrea Martínez Salgueiro, Maria-Antonia Tarrazon-Rodon\",\"doi\":\"10.1007/s11147-019-09161-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":45022,\"journal\":{\"name\":\"Review of Derivatives Research\",\"volume\":\"348 1\",\"pages\":\"\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2019-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Review of Derivatives Research\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1007/s11147-019-09161-0\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Review of Derivatives Research","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1007/s11147-019-09161-0","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Approaching rainfall-based weather derivatives pricing and operational challenges
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.
期刊介绍:
The proliferation of derivative assets during the past two decades is unprecedented. With this growth in derivatives comes the need for financial institutions, institutional investors, and corporations to use sophisticated quantitative techniques to take full advantage of the spectrum of these new financial instruments. Academic research has significantly contributed to our understanding of derivative assets and markets. The growth of derivative asset markets has been accompanied by a commensurate growth in the volume of scientific research. The Review of Derivatives Research provides an international forum for researchers involved in the general areas of derivative assets. The Review publishes high-quality articles dealing with the pricing and hedging of derivative assets on any underlying asset (commodity, interest rate, currency, equity, real estate, traded or non-traded, etc.). Specific topics include but are not limited to: econometric analyses of derivative markets (efficiency, anomalies, performance, etc.) analysis of swap markets market microstructure and volatility issues regulatory and taxation issues credit risk new areas of applications such as corporate finance (capital budgeting, debt innovations), international trade (tariffs and quotas), banking and insurance (embedded options, asset-liability management) risk-sharing issues and the design of optimal derivative securities risk management, management and control valuation and analysis of the options embedded in capital projects valuation and hedging of exotic options new areas for further development (i.e. natural resources, environmental economics. The Review has a double-blind refereeing process. In contrast to the delays in the decision making and publication processes of many current journals, the Review will provide authors with an initial decision within nine weeks of receipt of the manuscript and a goal of publication within six months after acceptance. Finally, a section of the journal is available for rapid publication on `hot'' issues in the market, small technical pieces, and timely essays related to pending legislation and policy. Officially cited as: Rev Deriv Res