Preface

Summary

Actuaries and other financial analysts quantify situations using data – we are “numbers” people. Many of our approaches andmodels are stylized, based on years of experience and investigations performed by legions of analysts. However, the financial and risk management world evolves rapidly. Many analysts are confronted with new situations in which tried-and-true methods simply do not work. This is where a toolkit like regression analysis comes in.

Regression is the study of relationships among variables. It is a generic statistics discipline that is not restricted to the financial world – it has applications in the fields of social, biological, and physical sciences. You can use regression techniques to investigate large and complex data sets. To familiarize you with regression, this book explores many examples and data sets based on actuarial and financial applications. This is not to say that you will not encounter applications outside of the financial world (e.g., an actuary may need to understand the latest scientific evidence on genetic testing for underwriting purposes). However, as you become acquainted with this toolkit, you will see how regression can be applied in many (and sometimes new) situations.

Who Is This Book For?

This book is written for financial analysts who face uncertain events and wish to quantify the events using empirical information. No industry knowledge is assumed, although readers will find the reading much easier if they have an interest in the applications discussed here! This book is designed for students who are just being introduced to the field as well as industry analysts who would like to brush up on old techniques and (for the later chapters) get an introduction to new developments.