This volume deals with two complementary topics. On one hand the book deals with the problem of determining the the probability distribution of a positive compound random variable, a problem which appears in the banking and insurance industries, in many areas of operational research and in reliability problems in the engineering sciences. On the other hand, the methodology proposed to solve such problems, which is based on an application of the maximum entropy method to invert the Laplace transform of the distributions, can be applied to many other problems. The book contains applications to a large variety of problems, including the problem of dependence of the sample data used to estimate empirically the Laplace transform of the random variable. ContentsIntroductionFrequency modelsIndividual severity modelsSome detailed examplesSome traditional approaches to the aggregation problemLaplace transforms and fractional moment problemsThe standard maximum entropy methodExtensions of the method of maximum entropySuperresolution in maxentropic Laplace transform inversionSample data dependenceDisentangling frequencies and decompounding lossesComputations using the maxentropic densityReview of statistical procedures
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Henryk Gzylhas a PhD in Mathematics from UCSD. He works in Quantitatve Finance and Inverse Problems at The Center for Finance of IESA in Caracas. There he lectures on Risk and Portfolio Optimization. Silvia Mayoralis Professor of Finance in the Business Department of Carlos III University, Spain. Her academic activity is devoted to Financial Markets, with a special focus on Risk Measurement and Asset Pricing. Erika Gomes-GonçalvesPh.D. in Business and Quantitative Methods at the University Carlos III of Madrid (UC3M), Spain. Bachelor in Mathematics at Simón Bolívar University (USB), Caracas, Venezuela. Currently, she works as Independent Scholar and Data Science Consultant in Madrid.