Financial trading systems: Is recurrent reinforcement the via?
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- Jin Zhang & Dietmar Maringer, 2016. "Using a Genetic Algorithm to Improve Recurrent Reinforcement Learning for Equity Trading," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 551-567, April.
- Marco Corazza & Francesco Bertoluzzo, 2014. "Q-Learning-based financial trading systems with applications," Working Papers 2014:15, Department of Economics, University of Venice "Ca' Foscari".
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KeywordsFinancial trading system; recurrent reinforcement learning; no-hidden-layer perceptron model; returns weighted directional symmetry measure; gradient ascent technique; Italian stock market.;
- C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-CMP-2006-11-18 (Computational Economics)
- NEP-MST-2006-11-18 (Market Microstructure)
- NEP-RMG-2006-11-18 (Risk Management)
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