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dc.contributor.advisorGasmen, Perlita E.-
dc.contributor.authorAmpol, Ariel Kenneth-
dc.date.accessioned2015-07-24T11:12:09Z-
dc.date.available2015-07-24T11:12:09Z-
dc.date.issued2015-06-
dc.identifier.urihttp://cas.upm.edu.ph:8080/xmlui/handle/123456789/23-
dc.description.abstractWith Forex as the largest and most liquid financial market, the practice of algo- rithmic trading has become of interest in the market, as well as in research. This study explores the use of the Adaptive Neuro-Fuzzy Inference System as a pre- dictor, combined with the Non-Dominated Sorting Genetic Algorithm II for trade timing to create a smart autonomous Forex trading agent that produces sizable profits. Upon performing a backtest, the agent was shown to be able to garner approximately $80 in profit in a span of two months and nearly $500 in profit for a one-year period. Empirical evidence is also provided that the trading agent running live is able to open trades which profitably closed.en_US
dc.language.isoenen_US
dc.subjectForExen_US
dc.subjectforeign exchangeen_US
dc.subjectexchange ratesen_US
dc.subjectalgorithmic tradingen_US
dc.subjectANFISen_US
dc.subjectneurofuzzyen_US
dc.subjectgenetic algorithmen_US
dc.subjectNSGA-IIen_US
dc.titleAAGFA: Automated ANFIS and GA-Based Forex Agenten_US
dc.typeThesisen_US
Appears in Collections:Computer Science SP

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