A Course on Statistics for Finance
1st Edition
Published on 30. June 2020
Book
Paperback/Softback
280 pages
978-0-367-57660-8 (ISBN)
Description
Taking a data-driven approach, A Course on Statistics for Finance presents statistical methods for financial investment analysis. The author introduces regression analysis, time series analysis, and multivariate analysis step by step using models and methods from finance.
The book begins with a review of basic statistics, including descriptive statistics, kinds of variables, and types of data sets. It then discusses regression analysis in general terms and in terms of financial investment models, such as the capital asset pricing model and the Fama/French model. It also describes mean-variance portfolio analysis and concludes with a focus on time series analysis.
Providing the connection between elementary statistics courses and quantitative finance courses, this text helps both existing and future quants improve their data analysis skills and better understand the modeling process.
The book begins with a review of basic statistics, including descriptive statistics, kinds of variables, and types of data sets. It then discusses regression analysis in general terms and in terms of financial investment models, such as the capital asset pricing model and the Fama/French model. It also describes mean-variance portfolio analysis and concludes with a focus on time series analysis.
Providing the connection between elementary statistics courses and quantitative finance courses, this text helps both existing and future quants improve their data analysis skills and better understand the modeling process.
Reviews / Votes
"... Through numerous examples, the book explains how the theory of RDS can describe the asymptotic and qualitative behavior of systems of random and stochastic differential-difference equations in terms of stability, invariant manifolds and attractors. ... provides a variety of RDS for approximating financial models, and studies the stability and optimal control of RDS. The book is useful for graduate students in RDS and mathematical _nance as well as practitioners working in the financial industry."- Ahmed Hegazi (Mansoura ), Zentralblatt MATH
More details
Language
English
Place of publication
Boca Raton
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 234 mm
Width: 156 mm
Thickness: 15 mm
Weight
430 gr
ISBN-13
978-0-367-57660-8 (9780367576608)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Stanley L. Sclove
A Course on Statistics for Finance
E-Book
09/2018
1st Edition
Chapman & Hall/CRC
€68.49
Available for download
Stanley L. Sclove
A Course on Statistics for Finance
E-Book
09/2018
1st Edition
Chapman & Hall/CRC
€68.49
Available for download
Stanley L. Sclove
A Course on Statistics for Finance
Book
12/2012
1st Edition
Chapman & Hall/CRC
€123.80
Shipment within 15-20 days
Person
Stanley L. Sclove is a professor of statistics in the Department of Information and Decision Sciences of the College of Business Administration at the University of Illinois at Chicago (UIC). His areas of specialization within statistics include multivariate statistical analysis, cluster analysis, time series analysis, and model selection criteria. Dr. Sclove's research interests include time series segmentation and regime switching via Markov models. He is an officer of the Classification Society and the Section of Risk Analysis of the American Statistical Association.
Content
INTRODUCTORY CONCEPTS AND DEFINITIONS: Review of Basic Statistics. Stock Price Series and Rates of Return. Several Stocks and Their Rates of Return. REGRESSION: Simple Linear Regression; CAPM and Beta. Multiple Regression and Market Models. PORTFOLIO ANALYSIS: Mean-Variance Portfolio Analysis. Utility-Based Portfolio Analysis. TIME SERIES ANALYSIS: Introduction to Time Series Analysis. Regime Switching Models. Appendices. Index.