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 distributions
* Coxian and related distributions
* Mixed Erlang distributions
* Computational and analytical methods for aggregate claim
models
* Counting processes
* Compound distributions with time-dependent claim amounts
* Copula models
* Continuous time ruin models
* Interpolation and smoothing
The 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.
O autorze
STUART A. KLUGMAN, Ph D, is Staff Fellow (Education) at
the Society of Actuaries and Principal Financial Group
Distinguished Professor Emeritus of Actuarial Science at Drake
University. Dr. Klugman is a two-time recipient of the Society of
Actuaries’ Presidential Award.
HARRY H. PANJER, Ph D, is Distinguished Professor Emeritus
in the Department of Statistics and Actuarial Science at the
University of Waterloo, Canada. Dr. Panjer was previously president
of the Canadian Institute of Actuaries and the Society of
Actuaries.
GORDON E. WILLMOT, Ph D, is Munich Re Chair in Insurance
and Professor in the Department of Statistics and Actuarial Science
at the University of Waterloo, Canada. Dr. Willmot has authored
more than eighty-five articles in the areas of risk theory, queuing
theory, distribution theory, and stochastic modeling in
insurance.
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