Regression Modeling with Actuarial and Financial Applications [Hardcover]

This book teaches multiple regression and time series and how to use these to analyze real data in risk management and finance.This book provides actuarial and finance students with a foundation in multiple regression and time series, along with a discussion of advanced statistical topics that are relevant to actuarial and financial practice. It uses statistical techniques to analyze real data in risk management and finance. No specific knowledge of these areas is presumed.This book provides actuarial and finance students with a foundation in multiple regression and time series, along with a discussion of advanced statistical topics that are relevant to actuarial and financial practice. It uses statistical techniques to analyze real data in risk management and finance. No specific knowledge of these areas is presumed.Statistical techniques can be used to address new situations. This is important in a rapidly evolving risk management and financial world. Analysts with a strong statistical background understand that a large data set can represent a treasure trove of information to be mined and can yield a strong competitive advantage. This book provides budding actuaries and financial analysts with a foundation in multiple regression and time series. Readers will learn about these statistical techniques using data on the demand for insurance, lottery sales, foreign exchange rates, and other applications. Although no specific knowledge of risk management or finance is presumed, the approach introduces applications in which statistical techniques can be used to analyze real data of interest. In addition to the fundamentals, this book describes several advanced statistical topics that are particularly relevant to actuarial and financial practice, including the analysis of longitudinal, two-part (frequency/severity), and fat-tailed data. Datasets with detailed descriptions, sample statistical software scripts in R and SAS, and tips on writing a statistical rló'