Free Kindle Statistics And Data Analysis For Financial Engineering: With R Examples (Springer Texts In Statistics) ebooks Download
The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.
Series: Springer Texts in Statistics
Hardcover: 719 pages
Publisher: Springer; 2nd ed. 2015 edition (April 22, 2015)
Language: English
ISBN-10: 1493926136
ISBN-13: 978-1493926138
Product Dimensions: 6.1 x 1.6 x 9.2 inches
Shipping Weight: 2.5 pounds (View shipping rates and policies)
Average Customer Review: 2.7 out of 5 stars See all reviews (3 customer reviews)
Best Sellers Rank: #397,337 in Books (See Top 100 in Books) #187 in Books > Business & Money > Economics > Econometrics #396 in Books > Business & Money > Education & Reference > Statistics #545 in Books > Textbooks > Business & Finance > Finance
The book includes concepts that are tremendously valuable, but the author is unable to explain these concepts in a lucid manner. Approximately 40% of the book is written in mathematical notation and the author rarely takes the time to define the notation that he uses. At times, it seems like the author purposefully obfuscates the material because his explanations on simple financial concepts are laboriously dense. The author cannot describe simple concepts such as the natural log, or normal distributions in a lucid manner. In regard to more difficult concepts, the reader will be spending ample time at Khan Academy and on the web attempting to deduce the notation and concepts. This book is only useful for mathematicians that have a biblical grasp on mathematical notation.
Not enough example.
Useful book, fantastic!
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