An edition of Loss Models
(2009)
Loss Models
From Data to Decisions
3rd ed.
by Stuart A. Klugman
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An update of one of the most trusted books on constructing and analyzing actuarial modelsWritten by three renowned authorities in the actuarial field, Loss Models, Third Edition upholds the reputation for excellence that has made this book required reading for the Society of Actuaries (SOA) and Casualty Actuarial Society (CAS) qualification examinations. This update serves as a complete presentation of statistical methods for measuring risk and building models to measure loss in real-world events. This book maintains an approach to modeling and forecasting that utilizes tools related to risk th.
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Loss Models: From Data to Decisions
2012, John Wiley & Sons
electronic resource :
in English
- 3rd ed.
0470391332 9780470391334
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Book Details
Table of Contents
Loss Models: From Data to Decisions; Contents; Preface; PART I INTRODUCTION; 1 Modeling; 1.1 The model-based approach; 1.1.1 The modeling process; 1.1.2 The modeling advantage; 1.2 Organization of this book; 2 Random variables; 2.1 Introduction; 2.2 Key functions and four models; 2.2.1 Exercises; 3 Basic distributional quantities; 3.1 Moments; 3.1.1 Exercises; 3.2 Quantiles; 3.2.1 Exercises; 3.3 Generating functions and sums of random variables; 3.3.1 Exercises; 3.4 Tails of distributions; 3.4.1 Classification based on moments; 3.4.2 Comparison based on limiting tail behavior.
3.4.3 Classification based on the hazard rate function3.4.4 Classification based on the mean excess loss function; 3.4.5 Equilibrium distributions and tail behavior; 3.4.6 Exercises; 3.5 Measures of Risk; 3.5.1 Introduction; 3.5.2 Risk measures and coherence; 3.5.3 Value-at-Risk; 3.5.4 Tail-Value-at-Risk; 3.5.5 Exercises; PART II ACTUARIAL MODELS; 4 Characteristics of actuarial models; 4.1 Introduction; 4.2 The role of parameters; 4.2.1 Parametric and scale distributions; 4.2.2 Parametric distribution families; 4.2.3 Finite mixture distributions; 4.2.4 Data-dependent distributions.
4.2.5 Exercises5 Continuous models; 5.1 Introduction; 5.2 Creating new distributions; 5.2.1 Multiplication by a constant; 5.2.2 Raising to a power; 5.2.3 Exponentiation; 5.2.4 Mixing; 5.2.5 Frailty models; 5.2.6 Splicing; 5.2.7 Exercises; 5.3 Selected distributions and their relationships; 5.3.1 Introduction; 5.3.2 Two parametric families; 5.3.3 Limiting distributions; 5.3.4 Exercises; 5.4 The linear exponential family; 5.4.1 Exercises; 5.5 TVaR for continuous distributions; 5.5.1 Continuous elliptical distributions; 5.5.2 TVaR for the linear exponential family; 5.5.3 Exercise.
5.6 Extreme value distributions5.6.1 Introduction; 5.6.2 Distribution of the maximum; 5.6.3 Stability of the maximum of the extreme value distribution; 5.6.4 The Fisher-Tippett theorem; 5.6.5 Maximum domain of attraction; 5.6.6 Generalized Pareto distributions; 5.6.7 Stability of excesses of the generalized Pareto; 5.6.8 Limiting distributions of excesses; 5.6.9 TVaR for extreme value distributions; 5.6.10 Further reading; 5.6.11 Exercises; 6 Discrete distributions and processes; 6.1 Introduction; 6.1.1 Exercise; 6.2 The Poisson distribution; 6.3 The negative binomial distribution.
6.4 The binomial distribution6.5 The (a, b, 0) class; 6.5.1 Exercises; 6.6 Counting processes; 6.6.1 Introduction and definitions; 6.6.2 Poisson processes; 6.6.3 Processes with contagion; 6.6.4 Other processes; 6.6.5 Exercises; 6.7 Truncation and modification at zero; 6.7.1 Exercises; 6.8 Compound frequency models; 6.8.1 Exercises; 6.9 Further properties of the compound Poisson class; 6.9.1 Exercises; 6.10 Mixed frequency distributions; 6.10.1 General mixed frequency distribution; 6.10.2 Mixed Poisson distributions; 6.10.3 Exercises; 6.11 Mixed Poisson processes; 6.11.1 Exercises.
Edition Notes
6.12 Effect of exposure on frequency.
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| August 13, 2020 | Edited by ImportBot | import existing book |
| July 5, 2019 | Created by MARC Bot | import new book |