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Machine Learning for Financial Engin...

Gyorfi, Laszlo.

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Machine Learning for Financial Engineering

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine Learning for Financial Engineering/
Author:	Gyorfi, Laszlo.
other author:	Ottucsak, Gyorgy.
Published:	Singapore :World Scientific, : 2012.,
Description:	1 online resource (261 p.)
Notes:	5.4. Universally Consistent Predictions: Unbounded Y.
Subject:	Financial engineering - Data processing. -
Online resource:	http://www.worldscientific.com/worldscibooks/10.1142/P818#t=toc
ISBN:	9781848168145 (electronic bk.)

Machine Learning for Financial Engineering
Gyorfi, Laszlo.

Machine Learning for Financial Engineering[electronic resource]. - Singapore :World Scientific,2012. - 1 online resource (261 p.) - Advances in Computer Science and Engineering: Texts. - Advances in computer science and engineering.Texts..

5.4. Universally Consistent Predictions: Unbounded Y.

This volume investigates algorithmic methods based on machine learning in order to design sequential investment strategies for financial markets. Such sequential investment strategies use information collected from the market's past and determine, at the beginning of a trading period, a portfolio; that is, a way to invest the currently available capital among the assets that are available for purchase or investment. The aim is to produce a self-contained text intended for a wide audience, including researchers and graduate students in computer science, finance, statistics, mathematics, and eng.

ISBN: 9781848168145 (electronic bk.)Subjects--Topical Terms:

2016439
Financial engineering
--Data processing.Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: Q325.5 .M321 2012

Dewey Class. No.: 006.31

Machine Learning for Financial Engineering
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020 $a 1848168144 (electronic bk.)
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100 1 $a Gyorfi, Laszlo. $3 740968
245 1 0 $a Machine Learning for Financial Engineering $h [electronic resource].
260 $a Singapore : $b World Scientific, $c 2012.
300 $a 1 online resource (261 p.)
490 1 $a Advances in Computer Science and Engineering: Texts
500 $a 5.4. Universally Consistent Predictions: Unbounded Y.
520 $a This volume investigates algorithmic methods based on machine learning in order to design sequential investment strategies for financial markets. Such sequential investment strategies use information collected from the market's past and determine, at the beginning of a trading period, a portfolio; that is, a way to invest the currently available capital among the assets that are available for purchase or investment. The aim is to produce a self-contained text intended for a wide audience, including researchers and graduate students in computer science, finance, statistics, mathematics, and eng.
588 $a Description based on print version record.
650 0 $a Financial engineering $x Data processing. $3 2016439
650 0 $a Machine learning. $3 533906
650 0 $a Investments $x Data processing. $3 683480
655 0 $a Electronic books. $2 lcsh $3 542853
700 1 $a Ottucsak, Gyorgy. $3 2016436
700 1 $a Walk, Harro. $3 2016437
830 0 $a Advances in computer science and engineering. $p Texts. $3 2016438
856 4 0 $u http://www.worldscientific.com/worldscibooks/10.1142/P818#t=toc