From Data to Decisions
Buch, Englisch, 560 Seiten, Format (B × H): 183 mm x 257 mm, Gewicht: 1021 g
ISBN: 978-1-119-52378-9
Verlag: Wiley
A guide that provides in-depth coverage of modeling techniques used throughout many branches of actuarial science, revised and updated
Now in its fifth edition, Loss Models: From Data to Decisions puts the focus on material tested in the Society of Actuaries (SOA) newly revised Exams STAM (Short-Term Actuarial Mathematics) and LTAM (Long-Term Actuarial Mathematics). Updated to reflect these exam changes, this vital resource offers actuaries, and those aspiring to the profession, a practical approach to the concepts and techniques needed to succeed in the profession. The techniques are also valuable for anyone who uses loss data to build models for assessing risks of any kind.
Loss Models contains a wealth of examples that highlight the real-world applications of the concepts presented, and puts the emphasis on calculations and spreadsheet implementation. With a focus on the loss process, the book reviews the essential quantitative techniques such as random variables, basic distributional quantities, and the recursive method, and discusses techniques for classifying and creating distributions. Parametric, non-parametric, and Bayesian estimation methods are thoroughly covered. In addition, the authors offer practical advice for choosing an appropriate model. This important text:
• Presents a revised and updated edition of the classic guide for actuaries that aligns with newly introduced Exams STAM and LTAM
• Contains a wealth of exercises taken from previous exams
• Includes fresh and additional content related to the material required by the Society of Actuaries (SOA) and the Canadian Institute of Actuaries (CIA)
• Offers a solutions manual available for further insight, and all the data sets and supplemental material are posted on a companion site
Written for students and aspiring actuaries who are preparing to take the SOA examinations, Loss Models offers an essential guide to the concepts and techniques of actuarial science.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Preface xiii
About the Companion Website xv
Part I Introduction
1 Modeling 3
1.1 The Model-Based Approach 3
1.1.1 The Modeling Process 3
1.1.2 The Modeling Advantage 5
1.2 The Organization of This Book 6
2 Random Variables 9
2.1 Introduction 9
2.2 Key Functions and Four Models 11
2.2.1 Exercises 19
3 Basic Distributional Quantities 21
3.1 Moments 21
3.1.1 Exercises 28
3.2 Percentiles 29
3.2.1 Exercises 31
3.3 Generating Functions and Sums of Random Variables 31
3.3.1 Exercises 33
3.4 Tails of Distributions 33
3.4.1 Classification Based on Moments 33
3.4.2 Comparison Based on Limiting Tail Behavior 34
3.4.3 Classification Based on the Hazard Rate Function 35
3.4.4 Classification Based on the Mean Excess Loss Function 36
3.4.5 Equilibrium Distributions and Tail Behavior 38
3.4.6 Exercises 39
3.5 Measures of Risk 41
3.5.1 Introduction 41
3.5.2 Risk Measures and Coherence 41
3.5.3 Value at Risk 43
3.5.4 Tail Value at Risk 44
3.5.5 Exercises 48
Part II Actuarial Models
4 Characteristics of Actuarial Models 51
4.1 Introduction 51
4.2 The Role of Parameters 51
4.2.1 Parametric and Scale Distributions 52
4.2.2 Parametric Distribution Families 54
4.2.3 Finite Mixture Distributions 54
4.2.4 Data-Dependent Distributions 56
4.2.5 Exercises 59
5 Continuous Models 61
5.1 Introduction 61
5.2 Creating New Distributions 61
5.2.1 Multiplication by a Constant 62
5.2.2 Raising to a Power 62
5.2.3 Exponentiation 64
5.2.4 Mixing 64
5.2.5 Frailty Models 68
5.2.6 Splicing 69
5.2.7 Exercises 70
5.3 Selected Distributions and Their Relationships 74
5.3.1 Introduction 74
5.3.2 Two Parametric Families 74
5.3.3 Limitin
