- We will send in 10–14 business days.
/images/books/5755257/9781138198371.jpg)
- Author: Thomas A Severini
- Publisher: CRC Press
- ISBN-10: 1138198374
- ISBN-13: 9781138198371
- Format: 16 x 22.9 x 2.5 cm, hardcover
- Language: English
- SAVE -10% with code: EXTRA
Introduction to Statistical Methods for Financial Models (e-book) (used book) | bookbook.eu
Reviews
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.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 20d.23:16:25
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Thomas A Severini
- Publisher: CRC Press
- ISBN-10: 1138198374
- ISBN-13: 9781138198371
- Format: 16 x 22.9 x 2.5 cm, hardcover
- Language: English 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.
Reviews