Skip to content

Due to scheduled maintenance, if purchasing is normally available on this site, it will not be available from Saturday 18th November 07:00 GMT until Sunday 19th November 15:00 GMT. We apologise for the inconvenience.

Your Cart

×

You have 0 items in your cart.

Register Sign in Wishlist

Financial Analytics with R
Building a Laptop Laboratory for Data Science

  • Date Published: November 2016
  • availability: In stock
  • format: Hardback
  • isbn: 9781107150751

Hardback

Add to wishlist

Other available formats:
eBook


Looking for an examination copy?

If you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact collegesales@cambridge.org providing details of the course you are teaching.

Description
Product filter button
Description
Contents
Resources
Courses
About the Authors
  • Are you innately curious about dynamically inter-operating financial markets? Since the crisis of 2008, there is a need for professionals with more understanding about statistics and data analysis, who can discuss the various risk metrics, particularly those involving extreme events. By providing a resource for training students and professionals in basic and sophisticated analytics, this book meets that need. It offers both the intuition and basic vocabulary as a step towards the financial, statistical, and algorithmic knowledge required to resolve the industry problems, and it depicts a systematic way of developing analytical programs for finance in the statistical language R. Build a hands-on laboratory and run many simulations. Explore the analytical fringes of investments and risk management. Bennett and Hugen help profit-seeking investors and data science students sharpen their skills in many areas, including time-series, forecasting, portfolio selection, covariance clustering, prediction, and derivative securities.

    • Contains an ideal blend of innovative research and practical applications
    • Tackles relevant investor problems
    • Provides a multi-disciplined approach, solving problems from both fundamental and non-traditional methods
    Read more

    Reviews & endorsements

    "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)

    See more reviews

    Customer reviews

    Not yet reviewed

    Be the first to review

    Review was not posted due to profanity

    ×

    , create a review

    (If you're not , sign out)

    Please enter the right captcha value
    Please enter a star rating.
    Your review must be a minimum of 12 words.

    How do you rate this item?

    ×

    Product details

    • Date Published: November 2016
    • format: Hardback
    • isbn: 9781107150751
    • length: 392 pages
    • dimensions: 254 x 180 x 22 mm
    • weight: 0.92kg
    • contains: 60 b/w illus. 100 colour illus. 40 exercises
    • availability: In stock
  • Table of Contents

    Preface
    Acknowledgements
    1. Analytical thinking
    2. The R language for statistical computing
    3. Financial statistics
    4. Financial securities
    5. Dataset analytics and risk measurement
    6. Time series analysis
    7. The Sharpe ratio
    8. Markowitz mean-variance optimization
    9. Cluster analysis
    10. Gauging the market sentiment
    11. Simulating trading strategies
    12. Data mining using fundamentals
    13. Prediction using fundamentals
    14. Binomial model for options
    15. Black–Scholes model and option implied volatility
    Appendix. Probability distributions and statistical analysis
    Index.

  • Resources for

    Financial Analytics with R

    Mark J. Bennett, Dirk L. Hugen

    General Resources

    Instructor Resources

    Welcome to the resources site

    Here you will find free-of-charge online materials to accompany this book. The range of materials we provide across our academic and higher education titles are an integral part of the book package whether you are a student, instructor, researcher or professional.

    Find resources associated with this title

    Type Name Unlocked * Format Size

    Showing of

    Back to top

    *This title has one or more locked files and access is given only to instructors adopting the textbook for their class. We need to enforce this strictly so that solutions are not made available to students. To gain access to locked resources you either need first to sign in or register for an account.


    These resources are provided free of charge by Cambridge University Press with permission of the author of the corresponding work, but are subject to copyright. You are permitted to view, print and download these resources for your own personal use only, provided any copyright lines on the resources are not removed or altered in any way. Any other use, including but not limited to distribution of the resources in modified form, or via electronic or other media, is strictly prohibited unless you have permission from the author of the corresponding work and provided you give appropriate acknowledgement of the source.

    If you are having problems accessing these resources please email lecturers@cambridge.org

  • Authors

    Mark J. Bennett, University of Chicago
    Mark J. Bennett is a senior data scientist with a major investment bank and a lecturer in the University of Chicago's Master's program in analytics. He has held software positions at Argonne National Laboratory, Unisys Corporation, AT&T Bell Laboratories, Northrop Grumman, and XR Trading Securities.

    Dirk L. Hugen, University of Iowa
    Dirk L. Hugen is a graduate student in the Department of Statistics and Actuarial Science at the University of Iowa. He previously worked as a signal processing engineer.

Sign In

Please sign in to access your account

Cancel

Not already registered? Create an account now. ×

Sorry, this resource is locked

Please register or sign in to request access. If you are having problems accessing these resources please email lecturers@cambridge.org

Register Sign in
Please note that this file is password protected. You will be asked to input your password on the next screen.

» Proceed

You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.

Continue ×

Continue ×

Continue ×

Find content that relates to you

Are you sure you want to delete your account?

This cannot be undone.

Cancel

Thank you for your feedback which will help us improve our service.

If you requested a response, we will make sure to get back to you shortly.

×
Please fill in the required fields in your feedback submission.
×