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A Course on Statistics for Finance, by Stanley L. Sclove
Free PDF A Course on Statistics for Finance, by Stanley L. Sclove
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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.
- Sales Rank: #3043383 in Books
- Published on: 2012-12-06
- Original language: English
- Number of items: 1
- Dimensions: 9.30" h x .90" w x 6.10" l, 1.20 pounds
- Binding: Hardcover
- 269 pages
Review
"… 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
About the Author
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.
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