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Cambridge University Press

Regression Modeling with Actuarial and Financial Applications

Regression Modeling with Actuarial and Financial Applications

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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 report, including sample projects, can be found on the book's Web site: http: //research.bus.wisc.edu/RegActuaries.

Author: Edward W. Frees
Publisher: Cambridge University Press
Published: 11/30/2009
Pages: 584
Binding Type: Hardcover
Weight: 2.55lbs
Size: 9.90h x 7.00w x 1.50d
ISBN: 9780521760119

About the Author
Frees, Edward W.: - Edward W. (Jed) Frees is a Professor of Business at the University of Wisconsin, Madison and is holder of the Assurant Health Insurance Professorship of Actuarial Science. He is a Fellow of both the Society of Actuaries (SoA) and the American Statistical Association (ASA). Professor Frees is the author of Longitudinal and Panel Data (2004) and has published more than fifty articles in leading refereed academic journals.

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