Introduction to Statistical Methods for Financial Models

Nonfiction, Science & Nature, Mathematics, Statistics, Business & Finance, Finance & Investing, Finance
Cover of the book Introduction to Statistical Methods for Financial Models by Thomas A Severini, CRC Press
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Author: Thomas A Severini ISBN: 9781351981903
Publisher: CRC Press Publication: July 6, 2017
Imprint: Chapman and Hall/CRC Language: English
Author: Thomas A Severini
ISBN: 9781351981903
Publisher: CRC Press
Publication: July 6, 2017
Imprint: Chapman and Hall/CRC
Language: English

This book provides an introduction to the use of statistical concepts and methods to model and analyze financial data. The ten chapters of the book fall naturally into three sections. Chapters 1 to 3 cover some basic concepts of finance, focusing on the properties of returns on an asset. Chapters 4 through 6 cover aspects of portfolio theory and the methods of estimation needed to implement that theory. The remainder of the book, Chapters 7 through 10, discusses several models for financial data, along with the implications of those models for portfolio theory and for understanding the properties of return data.

The audience for the book is students majoring in Statistics and Economics as well as in quantitative fields such as Mathematics and Engineering. Readers are assumed to have some background in statistical methods along with courses in multivariate calculus and linear algebra.

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This book provides an introduction to the use of statistical concepts and methods to model and analyze financial data. The ten chapters of the book fall naturally into three sections. Chapters 1 to 3 cover some basic concepts of finance, focusing on the properties of returns on an asset. Chapters 4 through 6 cover aspects of portfolio theory and the methods of estimation needed to implement that theory. The remainder of the book, Chapters 7 through 10, discusses several models for financial data, along with the implications of those models for portfolio theory and for understanding the properties of return data.

The audience for the book is students majoring in Statistics and Economics as well as in quantitative fields such as Mathematics and Engineering. Readers are assumed to have some background in statistical methods along with courses in multivariate calculus and linear algebra.

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