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Reinforcement Learning in Financial Markets

School of Computer Science, Building J12, University of Sydney, 1 Cleveland Street, Darlington, NSW 2006, Australia
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Data 2019, 4(3), 110; https://doi.org/10.3390/data4030110
Received: 30 June 2019 / Revised: 23 July 2019 / Accepted: 26 July 2019 / Published: 28 July 2019
(This article belongs to the Special Issue Data Analysis for Financial Markets)
Recently there has been an exponential increase in the use of artificial intelligence for trading in financial markets such as stock and forex. Reinforcement learning has become of particular interest to financial traders ever since the program AlphaGo defeated the strongest human contemporary Go board game player Lee Sedol in 2016. We systematically reviewed all recent stock/forex prediction or trading articles that used reinforcement learning as their primary machine learning method. All reviewed articles had some unrealistic assumptions such as no transaction costs, no liquidity issues and no bid or ask spread issues. Transaction costs had significant impacts on the profitability of the reinforcement learning algorithms compared with the baseline algorithms tested. Despite showing statistically significant profitability when reinforcement learning was used in comparison with baseline models in many studies, some showed no meaningful level of profitability, in particular with large changes in the price pattern between the system training and testing data. Furthermore, few performance comparisons between reinforcement learning and other sophisticated machine/deep learning models were provided. The impact of transaction costs, including the bid/ask spread on profitability has also been assessed. In conclusion, reinforcement learning in stock/forex trading is still in its early development and further research is needed to make it a reliable method in this domain. View Full-Text
Keywords: reinforcement learning; stock market; foreign exchange market; trading; forecasts reinforcement learning; stock market; foreign exchange market; trading; forecasts
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Meng, T.L.; Khushi, M. Reinforcement Learning in Financial Markets. Data 2019, 4, 110.

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