大葉大學圖書館 |

登入

回首頁

Machine Learning for Financial Engin...

Gyorfi, Laszlo.

Machine Learning for Financial Engineering[electronic resource].

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	006.31
書名/作者:	Machine Learning for Financial Engineering
作者:	Gyorfi, Laszlo.
其他作者:	Ottucsak, Gyorgy.
出版者:	Singapore : : World Scientific,, 2012.
面頁冊數:	1 online resource (261 p.)
附註:	5.4. Universally Consistent Predictions: Unbounded Y.
標題:	Financial engineering - Data processing.
標題:	Machine learning.
標題:	Investments - Data processing.
ISBN:	9781848168145 (electronic bk.)
ISBN:	1848168144 (electronic bk.)
摘要、提要註:	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.
電子資源:	http://www.worldscientific.com/worldscibooks/10.1142/P818#t=toc

Machine Learning for Financial Engineering[electronic resource].
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:

556766
Financial engineering
--Data processing.Index Terms--Genre/Form:

336502
Electronic books.

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

Dewey Class. No.: 006.31

Machine Learning for Financial Engineering[electronic resource].
LDR:01527cam a2200265Mu 4500 001 400052
006 m d
007 cr |n|---|||||
008 140123s2012 si o 000 0 eng d
020 $a 9781848168145 (electronic bk.)
020 $a 1848168144 (electronic bk.)
020 $z 9781848168138
020 $z 1848168136
035 $a ocn794328402
040 $a EBLCP $b eng $c EBLCP $d OCLCQ $d LGG $d CDX $d YDXCP $d OCLCA $d OCLCQ $d DEBSZ
049 $a FISA
050 4 $a Q325.5 .M321 2012
082 0 4 $a 006.31
100 1 $a Gyorfi, Laszlo. $3 556762
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 556766
650 0 $a Machine learning. $3 202931
650 0 $a Investments $x Data processing. $3 556767
655 0 $a Electronic books. $2 local $3 336502
700 1 $a Ottucsak, Gyorgy. $3 556763
700 1 $a Walk, Harro. $3 556764
830 0 $a Advances in computer science and engineering. $p Texts. $3 556765
856 4 0 $u http://www.worldscientific.com/worldscibooks/10.1142/P818#t=toc

筆 0 讀者評論

多媒體

多媒體檔案
http://www.worldscientific.com/worldscibooks/10.1142/P818#t=toc

評論

新增評論分享你的心得

Export

取書館別