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Cambridge Financial Analytics with R - Hardback - 06 October 2016: Building a Laptop Laboratory for Data Science Hardcover – 6 October 2016

by Mark J. Bennett (Author), Dirk L. Hugen (Author)
4.0 out of 5 stars 28 ratings
Edition: 1st
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This book provides the intuition and basic vocabulary as steps towards the financial, statistical, and algorithmic knowledge needed to resolve current industry problems, while also presenting a systematic way of developing analytical programs for finance in the statistical language R. This book is a key training resource for students and professionals alike.
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  1. ISBN-10
    1107150752
  2. ISBN-13
    978-1107150751
  3. Edition
    1st
  4. Publisher
    Cambridge University Press
  5. Publication date
    6 October 2016
  6. Language
    English
  7. Dimensions
    17.15 x 2.54 x 25.4 cm
  8. Print length
    392 pages
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Product description

Review

'A very well-written text on financial analytics, focusing on developing statistical models and using simulation to better understand financial data. R is used throughout for examples, allowing the reader to use the text and code to actively engage in the financial market. It is simply the best text on this subject that I have seen. Highly recommended.' Joseph M. Hilbe, Arizona State University

'There's a new source in town for those who want to learn R and it's a good, old-fashioned book called Financial Analytics with R: Building a Laptop Laboratory for Data Science … it is a one-stop-shop for everything you need to know to use R for financial analysis. The book meaningfully combines an education on R with relevant problem-solving in financial analysis. [It] is thorough and contextualized with examples from extreme financial events in recent times such as the housing crisis and the Euro crisis. The code samples are relevant - think functions to compute the Sharpe ratio or to implement Bayesian reasoning - and answer many of the questions you might have while trying them out. This is a book that will make you a better practitioner/student/analyst/entrepreneur - whatever your goals may be.' Carrie Shaw, Quandl

'The book at hand is unusual in addressing beginners, and in treating R as a general number crunching tool. … It is also one of very few books on R really written for non-statistician non-programmers. … R seems a viable programming language for STEM students to learn, and learning a programming language seems a good idea for such students. This book appears to be the best option for accomplishing that.' Robert W. Hayden, Mathematical Association of America Reviews (www.maa.org)

Book Description

Financial Analytics with R sharpens readers' skills in time-series, forecasting, portfolio selection, covariance clustering, prediction, and derivative securities.

Product details

  • Publisher ‏ : ‎ Cambridge University Press; 1st edition (6 October 2016)
  • Language ‏ : ‎ English
  • Hardcover ‏ : ‎ 392 pages
  • ISBN-10 ‏ : ‎ 1107150752
  • ISBN-13 ‏ : ‎ 978-1107150751
  • Dimensions ‏ : ‎ 17.15 x 2.54 x 25.4 cm
  • Customer Reviews:
    4.0 out of 5 stars 28 ratings

About the authors

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  1. Dirk L. Hugen

    Dirk L. Hugen

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    Dirk L Hugen was born in Sioux City, Iowa and studied electrical engineering at Iowa State University. After working as a signal processing engineer in Duisburg, Germany, and Zurich, Switzerland he returned to the United States and completed master's degrees in finance and statistics at the University of Iowa. His current projects include development of multi-factor deep-value strategies and statistical characterization of beta-minimizing stock/option blended equity strategies.

    See more on the author's page
  2. Mark J. Bennett

    Mark J. Bennett

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    Mark Bennett is from the Chicago area and has been working in large datasets and real-time high performance computing for over three decades. His early work experience was in applied mathematics at Argonne National Laboratory and as research scientist at Unisys Corporation. Later he was a member of technical staff at AT&T Bell Laboratories, senior technical advisor and engineering manager at Northrop Grumman aerospace, senior technology specialist at XR Trading Securities and senior quantitative finance analyst at Bank of America Securities.

    Mark is currently senior data scientist at Nvidia Corporation. He has taught financial analytics at the University of Iowa and the University of Chicago. Mark holds a Ph.D. from UCLA, an M.S. from the University of Southern California, and a B.S. with Distinction from the University of Iowa, all in computer science.

    See more on the author's page
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4 out of 5 stars
28 global ratings

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  • I I
    4.0 out of 5 stars INCREDIBLE. Where are the files and the coding?
    Reviewed in Spain on 14 February 2020
    Verified Purchase
    I finally found it; they should give a mention in the book or indication.
    In fact there are two cambridge sites: one with nothing (what is the use of it otherwise than confuse?), and another with zip files.
    Report
  • tham
    3.0 out of 5 stars Three Stars
    Reviewed in the United Kingdom on 11 June 2017
    Verified Purchase
    Really good book but lacking financial market data
    Report
  • turbopro
    5.0 out of 5 stars As advertised
    Reviewed in the United States on 6 October 2020
    Verified Purchase
    This book I rated 5 stars because it delivers the goods. If you are so inclined, like I was, to go through the text cover to cover, you will learn how to develop a laptop laboratory to do data science on several financial instruments, to include stocks, forex, options. Of course, you should know the programming language 'R,' some knowledge of the financial markets, and some college level maths. You may encounter some challenges with the ongoing software development of one or two libraries in 'R,' most prominent of which is 'Quantmod,' but persevere, google, and you'll be fine. Highly recommended.

    I should ask the authors to work on the second edition to resolve the changes in the 'R' libraries as early as possible.
    Report
  • Andrew B.
    4.0 out of 5 stars Approachable Treatment of a Powerful Fields of Study
    Reviewed in the United States on 22 December 2019
    Verified Purchase
    I'm still working through this book, and this book does a good job breaking down how to get into Financial Analytics with R. I'm not using this as my only book on the topic, I'm having to work through independent sources on some of the math. But the tone of the book is very approachable for someone like me whose new to finance and too using R.
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  • PM
    5.0 out of 5 stars Great book for first attempts using r for portfolio optimization
    Reviewed in the United States on 25 April 2019
    Verified Purchase
    As an individual investor used to Excel, I would not venture to say it is a beginner's book for learning R, but rather more advanced. Having said that, as a beginner in R, I did manage to work through much of the code and have benefitted greatly. Looking forward to a second read.
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