Machine learning for financial engineering

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Title:

Author:

Gyorfi, László.

ISBN:

9781848168138

Publication Information:

London : Imperial College Press ; Singapore : Distributed by World Scientific Pub., c2012.

Physical Description:

ix, 250 p. : ill. ; 24 cm.

Series:

Advances in computer science and engineering. Texts ; v. 8

Advances in computer science and engineering. Texts v. 8.

Contents:

On the history of the growth-optimal portfolio / M.M. Christensen -- Empirical log-optimal portfolio selections : a survey / L. Gyorfi, Gy. Ottucsák, and A. Urbán -- Log-optimal portfolio-selection strategies with proportional transaction costs / L. Gyorfi and H. Walk -- Growth-optimal portfolio selection with short selling and leverage / M. Horváth and A. Urbán -- Nonparametric sequential prediction of stationary time series / L. Gyorfi and Gy. Ottucsák -- Empirical pricing American put options / L. Györfi and A. Telcs.

Subject Term:

Financial engineering -- Data processing.

Machine learning.

Investments -- Data processing.

Added Author:

Gyorfi, László.

Ottucsák, Gyorgy.

Walk, Harro, 1939-

Copies:

Available:*

Library	Material Type	Item Barcode	Shelf Number	Copy	Status
Searching... 1:IIEMSA	1:GEN-BOOK	33168025581949	332.60285631 G997M 2012	1	Searching... Unknown

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Summary

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 engineering.