Summary and Info
An essential resource for constructing and analyzing advanced actuarial models Loss Models: Further Topics presents extended coverage of modeling through the use of tools related to risk theory, loss distributions, and survival models. The book uses these methods to construct and evaluate actuarial models in the fields of insurance and business. Providing an advanced study of actuarial methods, the book features extended discussions of risk modeling and risk measures, including Tail-Value-at-Risk. Loss Models: Further Topics contains additional material to accompany the Fourth Edition of Loss Models: From Data to Decisions, such as:Extreme value distributionsCoxian and related distributionsMixed Erlang distributionsComputational and analytical methods for aggregate claim modelsCounting processesCompound distributions with time-dependent claim amountsCopula modelsContinuous time ruin modelsInterpolation and smoothingThe book is an essential reference for practicing actuaries and actuarial researchers who want to go beyond the material required for actuarial qualification. Loss Models: Further Topics is also an excellent resource for graduate students in the actuarial field.Content: Chapter 1 Introduction (pages 1–2): Chapter 2 Coxian and Related Distributions (pages 3–10): Chapter 3 Mixed Erlang Distributions (pages 11–22): Chapter 4 Extreme Value Distributions (pages 23–50): Chapter 5 Analytic and Related Methods for Aggregate Claim Models (pages 51–71): Chapter 6 Computational Methods for Aggregate Models (pages 73–96): Chapter 7 Counting Processes (pages 97–118): Chapter 8 Discrete Claim Count Models (pages 119–157): Chapter 9 Compound Distributions with Time Dependent Claim Amounts (pages 159–186): Chapter 10 Copula Models (pages 187–213): Chapter 11 Continuous‐Time Ruin Models (pages 215–254): Chapter 12 Interpolation and Smoothing (pages 255–272):
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