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Volumn 2412, Issue , 2002, Pages 347-358

Intraday FX trading: An evolutionary reinforcement learning approach

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATION; COMMERCE; COSTS; ELECTRONIC TRADING; GENETIC ALGORITHMS; HYBRID SYSTEMS; LEARNING ALGORITHMS; MACHINE LEARNING; PROFITABILITY;

EID: 84947915424     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45675-9_52     Document Type: Conference Paper
Times cited : (21)

References (23)
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    • Computational learning techniques for intraday fx trading using popular technical indicators, IEEE Transactions on Neural Networks
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    • Levich, R.1    Thomas, L.2
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    • Moody, J.1    Wu, L.2    Liao, Y.3    Saffell, M.4
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    • Is technical analysis in the foreign exchange market profitable? A genetic programming approach
    • Also available as Federal Reserve Bank of St. Louis Working Paper 96-006C
    • C. J. Neely, P. A. Weller, and R. Dittmar, Is technical analysis in the foreign exchange market profitable? a genetic programming approach, Journal of Financial and Quantitative Analysis, 32 (1997), pp. 405–426. Also available as Federal Reserve Bank of St. Louis Working Paper 96-006C.
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    • Enhancing Q-learning for optimal asset allocation
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.