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Financial analytics with R : = building a laptop laboratory for data science /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Financial analytics with R :/ Mark J. Bennett, University of Chicago, Dirk L. Hugen, University of Iowa.
Reminder of title:	building a laptop laboratory for data science /
Author:	Bennett, Mark J.
other author:	Hugen, Dirk L.,
Description:	1 online resource (xvi, 377 pages) :digital, PDF file(s). :
Notes:	Title from publisher's bibliographic system (viewed on 27 Oct 2016).
Subject:	Finance - Mathematical models -
Online resource:	https://doi.org/10.1017/CBO9781316584460
ISBN:	9781316584460 (ebook)

Financial analytics with R : = building a laptop laboratory for data science /
Bennett, Mark J.1959-

Financial analytics with R :building a laptop laboratory for data science /Mark J. Bennett, University of Chicago, Dirk L. Hugen, University of Iowa. - 1 online resource (xvi, 377 pages) :digital, PDF file(s).

Title from publisher's bibliographic system (viewed on 27 Oct 2016).

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.

ISBN: 9781316584460 (ebook)Subjects--Topical Terms:

1197920
Finance
--Mathematical models

LC Class. No.: HG104 / .B46 2016

Dewey Class. No.: 332.0285/513

Financial analytics with R : = building a laptop laboratory for data science /
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520 $a 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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