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Machine Learning for Financial Engin...

Gyorfi, Laszlo.

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 engineeringData 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:

648143
Financial engineering
--Data processing.Index Terms--Genre/Form:

214472
Electronic books.

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

Dewey Class. No.: 006.31

Machine Learning for Financial Engineering
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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 648143
650 0 $a Machine learning. $3 188639
650 0 $a Investments $x Data processing. $3 210067
655 0 $a Electronic books. $2 local. $3 214472
700 1 $a Ottucsak, Gyorgy. $3 648140
700 1 $a Walk, Harro. $3 648141
830 0 $a Advances in computer science and engineering. $p Texts. $3 648142
856 4 0 $u http://www.worldscientific.com/worldscibooks/10.1142/P818#t=toc