Actuarial Notes

Regression Modeling with Actuarial and Financial Applications

By Edward W. Frees · Cambridge University Press · 2010

Study guides: Exam SRM, Exam PA

A text that gives budding actuaries and financial analysts a foundation in multiple regression and time series. Cambridge University Press says readers learn the techniques using data on the demand for insurance, lottery sales, foreign exchange rates and other applications, with no specific knowledge of risk management or finance presumed. Beyond the fundamentals it describes advanced statistical topics relevant to actuarial and financial practice, including the analysis of longitudinal, two-part (frequency/severity) and fat-tailed data. The book's website holds datasets, sample R and SAS scripts and tips on writing a statistical report.

On the syllabus

  • Exam SRM — Chapter 1 – Background only; Chapter 2 – Sections 1-8; Chapter 3 – Sections 1-5; Chapter 5 – Sections 1-7; Chapter 6 – Sections 1-3; Chapter 7 – Sections 1-6; Chapter 8 – Sections 1-4; Chapter 9 – Sections 1-5; Chapter 11 – Sections 1-6; Chapter 12 – Sections 1-4; Chapter 13 – Sections 1-6.
  • Exam PA — Chapter 1 – Background only; Chapter 2 – Sections 1-8; Chapter 3 – Sections 1-5; Chapter 5 – Sections 1-7; Chapter 6 – Sections 1-3; Chapter 11 – Sections 1-6; Chapter 12 – Sections 1-4; Chapter 13 – Sections 1-6. While Chapters 7-9 are covered in Exam SRM, these models will not be covered in this exam.

Preface

1 Regression and the Normal Distribution

Part I Linear Regression

2 Basic Linear Regression

3 Multiple Linear Regression – I

4 Multiple Linear Regression – II

5 Variable Selection

6 Interpreting Regression Results

Part II Topics in Time Series

7 Modeling Trends

8 Autocorrelations and Autoregressive Models

9 Forecasting and Time Series Models

10 Longitudinal and Panel Data Models

Part III Topics in Nonlinear Regression

11 Categorical Dependent Variables

12 Count Dependent Variables

13 Generalized Linear Models

14 Survival Models

15 Miscellaneous Regression Topics

Part IV Actuarial Applications

16 Frequency-Severity Models

17 Fat-Tailed Regression Models

18 Credibility and Bonus-Malus

19 Claims Triangles

20 Report Writing: Communicating Data Analysis Results

21 Designing Effective Graphs

Brief Answers to Selected Exercises

Appendix 1 Basic Statistical Inference

Appendix 2 Matrix Algebra

Appendix 3 Probability Tables

Index

Sources