Machine Learning for Financial Engineering

This book PDF is perfect for those who love Business & Economics genre, written by László Györfi and published by World Scientific which was released on 14 March 2012 with total hardcover pages 260. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Machine Learning for Financial Engineering books below.

Machine Learning for Financial Engineering
Machine Learning for Financial Engineering
Author : László Györfi
File Size : 51,9 Mb
Publisher : World Scientific
Language : English
Release Date : 14 March 2012
ISBN : 9781908977663
Pages : 260 pages
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Machine Learning for Financial Engineering by László Györfi Book PDF 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. Contents:On the History of the Growth-Optimal Portfolio (M M Christensen)Empirical Log-Optimal Portfolio Selections: A Survey (L Györfi, Gy Ottucsák & A Urbán)Log-Optimal Portfolio-Selection Strategies with Proportional Transaction Costs (L Györfi & H Walk)Growth-Optimal Portfolio Selection with Short Selling and Leverage (M Horváth & A Urbán)Nonparametric Sequential Prediction of Stationary Time Series (L Györfi & G Ottuscák)Empirical Pricing American Put Options (L Györfi & A Telcs) Readership: Researchers, academics and graduate students in artificial intelligence/machine learning, and mathematical finance/quantitative finance. Keywords:Log-Optimal Portfolio;Growth-Optimal Portfolio;Sequential Investment Strategies for Financial MarketsKey Features:Covers machine learning algorithms for the aggregation of elementary investment strategiesHighlights multi-period and multi-asset tradingFocuses on nonparametric estimation of the underlying distributions in the market process

Machine Learning for Financial Engineering

Machine Learning for Financial Engineering by László Györfi,György Ottucsák,Harro Walk

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

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