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Financial Analytics with R Building a Laptop Laboratory for Data Science [Hardcover]

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  • Category: Books (Business & Economics)
  • Author:  Bennett, Mark J., Hugen, Dirk L.
  • Author:  Bennett, Mark J., Hugen, Dirk L.
  • ISBN-10:  1107150752
  • ISBN-10:  1107150752
  • ISBN-13:  9781107150751
  • ISBN-13:  9781107150751
  • Publisher:  Cambridge University Press
  • Publisher:  Cambridge University Press
  • Pages:  392
  • Pages:  392
  • Binding:  Hardcover
  • Binding:  Hardcover
  • Pub Date:  01-May-2016
  • Pub Date:  01-May-2016
  • SKU:  1107150752-11-MING
  • SKU:  1107150752-11-MING
  • Item ID: 100025847
  • Seller: ShopSpell
  • Ships in: 2 business days
  • Transit time: Up to 5 business days
  • Delivery by: Aug 25 to Aug 27
  • Notes: Brand New Book. Order Now.
Financial Analytics with R sharpens readers' skills in time-series, forecasting, portfolio selection, covariance clustering, prediction, and derivative securities.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.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.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.Preface; Acknowledgements; 1. Analytical thinking; 2. The R language for statistlƒ5
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