MACHINE LEARNING FOR FINANCIAL ENGINEERI

By: GYORFI LASZLO

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Hardcover | 16 March 2012

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Hardcover
262 Pages

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22.86 x 15.24 x 1.6

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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.

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You Can Find This Book In

Non-Fiction Accounting & Finance Finance Mathematics Probability & Statistics Computing & I.T.Computer Science Artificial Intelligence Machine Learning Business Applications Business & Management Business Mathematics & Systems

Booktopia Publisher Services World Scientific Publishing

Preface	p. v
On the History of the Growth-Optimal Portfolio	p. 1
Empirical Log-Optimal Portfolio Selections: A Survey	p. 81
Log-Optimal Portfolio-Selection Strategies with Proportional Transaction Costs	p. 119
Growth-Optimal Portfoho Selection with Short Selling and Leverage	p. 153
Nonparametric Sequential Prediction of Stationary Time Series	p. 179
Empirical Pricing American Put Options	p. 227
Index	p. 249
Table of Contents provided by Ingram. All Rights Reserved.

MACHINE LEARNING FOR FINANCIAL ENGINEERI

At a Glance

Hardcover

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How to return your order

Defective items

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