東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁 到查詢結果 [ subject:"Finance- Mathematical models" ]

切換: 標籤 | MARC模式 | ISBD

Financial analytics with R = buildin...

Bennett, Mark J.

FindBook

Google Book

Amazon

博客來

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

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Financial analytics with R/ Mark J. Bennett, Dirk L. Hugen.
其他題名:	building a laptop laboratory for data science /
作者:	Bennett, Mark J.
其他作者:	Hugen, Dirk L.
出版者:	Cambridge :Cambridge University Press, : 2016.,
面頁冊數:	xvi, 377 p. :digital ;24 cm.
附註:	Title from publisher's bibliographic system (viewed on 27 Oct 2016).
標題:	Finance - Mathematical models -
電子資源:	https://doi.org/10.1017/CBO9781316584460
ISBN:	9781316584460

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

Financial analytics with Rbuilding a laptop laboratory for data science /[electronic resource] :Mark J. Bennett, Dirk L. Hugen. - Cambridge :Cambridge University Press,2016. - xvi, 377 p. :digital ;24 cm.

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: 9781316584460Subjects--Topical Terms:

3229044
Finance
--Mathematical models

LC Class. No.: HG104 / .B46 2016

Dewey Class. No.: 332.0285513

Financial analytics with R = building a laptop laboratory for data science /
LDR:01889nmm a2200253 a 4500 001 2212183
003 UkCbUP
005 20161027032536.0
006 m d
007 cr nn 008maaau
008 201107s2016 enk o 1 0 eng d
020 $a 9781316584460 $q (electronic bk.)
020 $a 9781107150751 $q (paper)
035 $a CR9781316584460
040 $a UkCbUP $b eng $c UkCbUP
041 0 $a eng
050 4 $a HG104 $b .B46 2016
082 0 4 $a 332.0285513 $2 23
090 $a HG104 $b .B471 2016
100 1 $a Bennett, Mark J. $q (Mark Joseph). $3 3440304
245 1 0 $a Financial analytics with R $h [electronic resource] : $b building a laptop laboratory for data science / $c Mark J. Bennett, Dirk L. Hugen.
260 $a Cambridge : $b Cambridge University Press, $c 2016.
300 $a xvi, 377 p. : $b digital ; $c 24 cm.
500 $a Title from publisher's bibliographic system (viewed on 27 Oct 2016).
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.
650 0 $a Finance $x Mathematical models $x Data processing. $3 3229044
650 0 $a Finance $x Databases. $3 3440306
650 0 $a R (Computer program language) $3 784593
700 1 $a Hugen, Dirk L. $3 3440305
856 4 0 $u https://doi.org/10.1017/CBO9781316584460