Machine Learning For Financial Engineering
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| Title: | Machine Learning For Financial Engineering |
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| Description: | 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. |
| Authors: | Laszlo Gyorfi, Gyorgy Ottucsak, Harro Walk |
| Resource Type: | eBook. |
| Subjects: | Machine learning, Financial engineering--Data processing, Investments--Data processing |
| Categories: | COMPUTERS / Artificial Intelligence / General, BUSINESS & ECONOMICS / Finance / General, MATHEMATICS / Probability & Statistics / General |
| Database: | eBook Collection (EBSCOhost) |
| Abstract: | 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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| ISBN: | 9781848168138 9781848168145 |
