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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Why customer driven manufacturings. Compared to the traditional arbitrage-based approach, this technique is useful when the underlying asset dynamics are unknown or when the pricing equations are too complicated to solve analytically. Comparing to other established data-driven option pricing techniques such as neural networks, impl

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https://doi.org/10.1007/3-540-31319-2 that is suitable for online trading. Our benchmark for . is the Tucker (1991) put-call-futures (.) parity condition for detecting arbitrage profits in the index options and futures markets. The latter presents two main problems, (.) The windows for profitable arbitrage opportunities exist for short

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Evolutionary Decision Trees for Stock Index Options and Futures Arbitragesampling is used to train . to pick up the fundamental arbitrage patterns. The further novel aspect of . is a constraint satisfaction feature supplementing the fitness function that enables the user to train the .. by learning to satisfy a minimum and maximum set on the number of arbitrage opportuni

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the volume, which will enable readers without a strong programming background to gain hands-on experience in dealing with much of the technical material introduced in this work.978-1-4613-5262-4978-1-4615-0835-9

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https://doi.org/10.1007/978-3-658-43326-0ptimized using Genetic Algorithm (GA). Two training approaches—incremental and dynamic—are designed and studied. The system was evaluated with the stocks in NASDAQ market. Experimental results showed that the system can give reliable buy-sell signals and using the system to perform buy-sell can prod

ONYM

https://doi.org/10.1007/3-540-31319-2sampling is used to train . to pick up the fundamental arbitrage patterns. The further novel aspect of . is a constraint satisfaction feature supplementing the fitness function that enables the user to train the .. by learning to satisfy a minimum and maximum set on the number of arbitrage opportuni

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