Understand Up-to-Date Statistical Techniques for Financial and
Actuarial Applications
Since the first edition was published, statistical techniques,
such as reliability measurement, simulation, regression, and Markov
chain modeling, have become more prominent in the financial and
actuarial industries. Consequently, practitioners and students must
acquire strong mathematical and statistical backgrounds in order to
have successful careers.
Financial and Actuarial Statistics: An Introduction, Second
Edition enables readers to obtain the necessary mathematical and
statistical background. It also advances the application and theory
of statistics in modern financial and actuarial modeling. Like its
predecessor, this second edition considers financial and actuarial
modeling from a statistical point of view while adding a
substantial amount of new material.
New to the Second Edition
- Nomenclature and notations standard to the actuarial field
- Excel exercises with solutions, which demonstrate how to use
Excel functions for statistical and actuarial computations
- Problems dealing with standard probability and statistics
theory, along with detailed equation links
- A chapter on Markov chains and actuarial applications
- Expanded discussions of simulation techniques and applications,
such as investment pricing
- Sections on the maximum likelihood approach to parameter
estimation as well as asymptotic applications
- Discussions of diagnostic procedures for nonnegative random
variables and Pareto, lognormal, Weibull, and left truncated
distributions
- Expanded material on surplus models and ruin computations
- Discussions of nonparametric prediction intervals, option
pricing diagnostics, variance of the loss function associated with
standard actuarial models, and Gompertz and Makeham
distributions
- Sections on the concept of actuarial statistics for a
collection of stochastic status models
The book presents a unified approach to both financial and
actuarial modeling through the use of general status structures.
The authors define future time-dependent financial actions in terms
of a status structure that may be either deterministic or
stochastic. They show how deterministic status structures lead to
classical interest and annuity models, investment pricing models,
and aggregate claim models. They also employ stochastic status
structures to develop financial and actuarial models, such as
surplus models, life insurance, and life annuity models.
General
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