Please use this identifier to cite or link to this item:
http://dspace.cas.upm.edu.ph:8080/xmlui/handle/123456789/23
Title: | AAGFA: Automated ANFIS and GA-Based Forex Agent |
Authors: | Gasmen, Perlita E. Ampol, Ariel Kenneth |
Keywords: | ForEx foreign exchange exchange rates algorithmic trading ANFIS neurofuzzy genetic algorithm NSGA-II |
Issue Date: | Jun-2015 |
Abstract: | With 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. |
URI: | http://cas.upm.edu.ph:8080/xmlui/handle/123456789/23 |
Appears in Collections: | Computer Science SP |
Files in This Item:
File | Description | Size | Format | |
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SP - Ampol.pdf | 2.81 MB | Adobe PDF | View/Open |
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