9781138198371-1138198374-Introduction to Statistical Methods for Financial Models (Chapman & Hall/CRC Texts in Statistical Science)

Introduction to Statistical Methods for Financial Models (Chapman & Hall/CRC Texts in Statistical Science)

ISBN-13: 9781138198371
ISBN-10: 1138198374
Edition: 1
Author: Thomas A Severini
Publication date: 2017
Publisher: Chapman and Hall/CRC
Format: Hardcover 386 pages
Category: Finance
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Book details

ISBN-13: 9781138198371
ISBN-10: 1138198374
Edition: 1
Author: Thomas A Severini
Publication date: 2017
Publisher: Chapman and Hall/CRC
Format: Hardcover 386 pages
Category: Finance

Summary

Introduction to Statistical Methods for Financial Models (Chapman & Hall/CRC Texts in Statistical Science) (ISBN-13: 9781138198371 and ISBN-10: 1138198374), written by authors Thomas A Severini, was published by Chapman and Hall/CRC in 2017. With an overall rating of 4.3 stars, it's a notable title among other Finance books. You can easily purchase or rent Introduction to Statistical Methods for Financial Models (Chapman & Hall/CRC Texts in Statistical Science) (Hardcover) from BooksRun, along with many other new and used Finance books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

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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