國立虎尾科技大學 |

Quantitative finance with Python = a practical guide to investment management, trading, and financial engineering /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Quantitative finance with Python/ Chris Kelliher.
Reminder of title:	a practical guide to investment management, trading, and financial engineering /
Author:	Kelliher, Chris.
Published:	Boca Raton, FL :Chapman & Hall/CRC Press, : 2022.,
Description:	1 online resource.
Subject:	Investments - Management. -
Online resource:	https://www.taylorfrancis.com/books/9781003180975
ISBN:	9781003180975

Quantitative finance with Python = a practical guide to investment management, trading, and financial engineering /
Kelliher, Chris.

Quantitative finance with Pythona practical guide to investment management, trading, and financial engineering /[electronic resource] :Chris Kelliher. - 1st ed. - Boca Raton, FL :Chapman & Hall/CRC Press,2022. - 1 online resource. - Chapman & Hall/CRC Financial Mathematics series. - Chapman & Hall/CRC Financial Mathematics series..

Includes bibliographical references and index.

"Quantitative Finance with Python: A Practical Guide to Investment Management, Trading and Financial Engineering bridges the gap between the theory of mathematical finance and the practical applications of these concepts for derivative pricing and portfolio management. The book provides students with a very hands-on, rigorous introduction to foundational topics in quant finance, such as options pricing, portfolio optimization and machine learning. Simultaneously, the reader benefits from a strong emphasis on the practical applications of these concepts for institutional investors. Features. Useful as both a teaching resource and as a practical tool for professional investors. Ideal textbook for first year graduate students in quantitative finance programs, such as those in master's programs in Mathematical Finance, Quant Finance or Financial Engineering. Includes a perspective on the future of quant finance techniques, and in particular covers some introductory concepts of Machine Learning. Free-to-access repository with Python code available at www.routledge.com/ 9781032014432"--

ISBN: 9781003180975Subjects--Topical Terms:

1135593
Investments
--Management.

LC Class. No.: HG4515.2

Dewey Class. No.: 332.6

Quantitative finance with Python = a practical guide to investment management, trading, and financial engineering /
LDR:02427cam a2200361 a 4500 001 1168145
005 20251017072503.0
006 m o d
007 cr cnu---unuuu
008 251229s2022 flu ob 001 0 eng d
020 $a 9781003180975 $q (electronic bk.)
020 $a 1003180973 $q (electronic bk.)
020 $a 9781000582376 $q (electronic bk. : EPUB)
020 $a 100058237X $q (electronic bk. : EPUB)
020 $a 9781000582307 $q (electronic bk. : PDF)
020 $a 1000582302 $q (electronic bk. : PDF)
020 $z 9781032019147 $q (paperback)
020 $z 9781032014432 $q (hardback)
035 $a (OCoLC)1292532631
035 $a (OCoLC-P)1292532631
035 $a 9781003180975
040 $a OCoLC-P $b eng $c OCoLC-P
041 0 $a eng
050 0 0 $a HG4515.2
082 0 4 $a 332.6 $2 23
100 1 $a Kelliher, Chris. $3 1497476
245 1 0 $a Quantitative finance with Python $h [electronic resource] : $b a practical guide to investment management, trading, and financial engineering / $c Chris Kelliher.
250 $a 1st ed.
260 $a Boca Raton, FL : $b Chapman & Hall/CRC Press, $c 2022.
300 $a 1 online resource.
490 1 $a Chapman & Hall/CRC Financial Mathematics series
504 $a Includes bibliographical references and index.
520 $a "Quantitative Finance with Python: A Practical Guide to Investment Management, Trading and Financial Engineering bridges the gap between the theory of mathematical finance and the practical applications of these concepts for derivative pricing and portfolio management. The book provides students with a very hands-on, rigorous introduction to foundational topics in quant finance, such as options pricing, portfolio optimization and machine learning. Simultaneously, the reader benefits from a strong emphasis on the practical applications of these concepts for institutional investors. Features. Useful as both a teaching resource and as a practical tool for professional investors. Ideal textbook for first year graduate students in quantitative finance programs, such as those in master's programs in Mathematical Finance, Quant Finance or Financial Engineering. Includes a perspective on the future of quant finance techniques, and in particular covers some introductory concepts of Machine Learning. Free-to-access repository with Python code available at www.routledge.com/ 9781032014432"-- $c Provided by publisher.
588 $a OCLC-licensed vendor bibliographic record.
650 0 $a Investments $x Management. $3 1135593
650 0 $a Trading bands (Securities) $3 1497478
650 0 $a Financial engineering. $3 591542
650 0 $a Python (Computer program language) $3 566246
650 0 $a Investments. $3 557691
830 0 $a Chapman & Hall/CRC Financial Mathematics series. $3 1497477
856 4 0 $u https://www.taylorfrancis.com/books/9781003180975