Robust forex trading with Deep Q Network (DQN)

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2019
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Bangkok : Assumption University
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eng
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application/pdf
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19 pages
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ABAC Journal Vol. 39 No.1 (January-March 2019), 15-33
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Abstract
Financial trading is one of the most attractive areas in finance. Trading systems development is not an easy task because it requires extensive knowledge in several areas such as quantitative analysis, financial skills, and computer programming. A trading systems expert, as a human, also brings in their own bias when developing the system. There should be another, more effective way to develop the system using artificial intelligence. The aim of this study was to compare the performance of AI agents to the performance of the buy-and-hold strategy and the expert trader. The tested market consisted of 15 years of the Forex data market, from two currency pairs (EURUSD, USDJPY) obtained from Dukascopy Bank SA Switzerland. Both hypotheses were tested with a paired t-Test at the 0.05 significance level. The findings showed that AI can beat the buy & hold strategy with significant superiority, in FOREX for both currency pairs (EURUSD, USDJPY), and that AI can also significantly outperform CTA (experienced trader) for trading in EURUSD. However, the AI could not significantly outperform CTA for USDJPY trading. Limitations, contributions, and further research were recommended.
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