Financial Analytics with R

Building a Laptop Laboratory for Data Science

Business & Finance, Economics, Statistics, Nonfiction, Science & Nature, Mathematics
Cover of the book Financial Analytics with R by Mark J. Bennett, Dirk L. Hugen, Cambridge University Press
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Author: Mark J. Bennett, Dirk L. Hugen ISBN: 9781316776094
Publisher: Cambridge University Press Publication: October 6, 2016
Imprint: Cambridge University Press Language: English
Author: Mark J. Bennett, Dirk L. Hugen
ISBN: 9781316776094
Publisher: Cambridge University Press
Publication: October 6, 2016
Imprint: Cambridge University Press
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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