Titlebook: Genetic Algorithms and Genetic Programming in Computational Finance; Shu-Heng Chen Book 2002 Springer Science+Business Media New York 2002

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書目名稱Genetic Algorithms and Genetic Programming in Computational Finance影響因子(影響力)




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男學(xué)院

Grundlagen des CVM in Franchisesystemen,rsimonious, and predictive models. STROGANOFF is related to a traditional GP system which manipulates functional expressions. Both GP systems are examined on a Nikkei225 series from the Tokyo Stock Exchange. Using statistical and economical measures we show that STROGANOFF outperforms traditional GP, and it can evolve profitable polynomials.

FLORA

GP and the Predictive Power of Internet Message Traffic produces cleraly superior results. We experiment with alternative representations for the GP trading rule learner. Finally, we find a potential regime shift in the market reaction to the message volume data, and speculate about future trends.

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擁護(hù)

Hans H. Bauer,Frank Huber,Thomas Kellered software can help beginners to tackle those issues on their own. Once they have a general grasp of how to implement GP effectively, many advanced materials prepared in this volume are there for further exploration.

Gratulate

Genetic Programming: A Tutorial With The Software Simple GPed software can help beginners to tackle those issues on their own. Once they have a general grasp of how to implement GP effectively, many advanced materials prepared in this volume are there for further exploration.

Gratulate

Perennial長(zhǎng)期的

Customer Relationship Managementlatility forecasting, and arbitrage. The direction then turns to agent-based computational finance, a bottom-up approach to the study of financial markets. The review also sheds light on a few technical aspects of GAs and GP, which may play a vital role in financial applications.

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