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Online portfolio selection : principles and algorithms /
With the aim to sequentially determine optimal allocations across a set of assets, Online Portfolio Selection (OLPS) has significantly reshaped the financial investment landscape. Online Portfolio Selection: Principles and Algorithms supplies a comprehensive survey of existing OLPS principles and pr...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Boca Raton, FL :
CRC Press,
[2016]
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Li, Bin, |e author. | |
| 245 | 1 | 0 | |a Online portfolio selection : |b principles and algorithms / |c Bin Li and Steven C.H. Hoi. |
| 264 | 1 | |a Boca Raton, FL : |b CRC Press, |c [2016] | |
| 264 | 4 | |c ©20 | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a data file | ||
| 504 | |a Includes bibliographical references. | ||
| 588 | 0 | |a Online resource; title from digital title page (viewed on November 25, 2015). | |
| 505 | 0 | |a I. Introduction -- II. Principles -- III. Algorithms -- IV. Empirical studies -- V. Conclusion. | |
| 520 | |a With the aim to sequentially determine optimal allocations across a set of assets, Online Portfolio Selection (OLPS) has significantly reshaped the financial investment landscape. Online Portfolio Selection: Principles and Algorithms supplies a comprehensive survey of existing OLPS principles and presents a collection of innovative strategies that leverage machine learning techniques for financial investment. The book presents four new algorithms based on machine learning techniques that were designed by the authors, as well as a new back-test system they developed for evaluating trading strategy effectiveness. The book uses simulations with real market data to illustrate the trading strategies in action and to provide readers with the confidence to deploy the strategies themselves. The book is presented in five sections that: Introduce OLPS and formulate OLPS as a sequential decision task Present key OLPS principles, including benchmarks, follow the winner, follow the loser, pattern matching, and meta-learning Detail four innovative OLPS algorithms based on cutting-edge machine learning techniques Provide a toolbox for evaluating the OLPS algorithms and present empirical studies comparing the proposed algorithms with the state of the art Investigate possible future directions Complete with a back-test system that uses historical data to evaluate the performance of trading strategies, as well as MATLAB® code for the back-test systems, this book is an ideal resource for graduate students in finance, computer science, and statistics. It is also suitable for researchers and engineers interested in computational investment. Readers are encouraged to visit the authors' website for updates: http://olps.stevenhoi.org. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 630 | 0 | 0 | |a MATLAB. |
| 630 | 0 | 7 | |a MATLAB |2 fast |
| 650 | 0 | |a Portfolio management. | |
| 650 | 0 | |a Investments. | |
| 650 | 6 | |a Gestion de portefeuille. | |
| 650 | 6 | |a Investissements. | |
| 650 | 7 | |a portfolios (financial records) |2 aat | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Finance. |2 bisacsh | |
| 650 | 7 | |a Investments |2 fast | |
| 650 | 7 | |a Portfolio management |2 fast | |
| 700 | 1 | |a Hoi, Steven C. H., |e author. | |
| 776 | 0 | 8 | |i Print version: |z 9781482249637 |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781482249644/?ar |z Texto completo (Requiere registro previo con correo institucional) |
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