Testing Different Reinforcement Learning Configurations for Financial Trading: Introduction and Applications-Reference-Cited by-同舟云学术

Testing Different Reinforcement Learning Configurations for Financial Trading: Introduction and Applications

Published:2012 Issue: Volume:3 Page:68-77
ISSN:2212-5671
Container-title:Procedia Economics and Finance
language:en
Short-container-title:Procedia Economics and Finance

Author:

Bertoluzzo Francesco,Corazza Marco

Publisher

Elsevier BV

Subject

General Economics, Econometrics and Finance

Reference9 articles.

1. Barto, A.G. and Sutton, R. (1996). Reinforcement Learning: An introduction. Adaptive Computation and Machine Learning.

2. Bertsekas, D.P. and Tsitsiklis, J.N. (1996). Neuro-Dynamic programming. Belmont: Athena Scientific.

3. Bosq, D. (1996). Algorithms for minimization without derivatives. Nonparametric statistics for stochastic processes. Estimation and prediction.Lecture notes in statistics. New York: Springer-Verlag.

4. Brent, R.P. (1996). Algorithms for minimization without derivatives. Englewood Cliffs: Prentice-Hall.

5. Gold, C. (2003). FX trading via recurrent Reinforcement Learning. Proc of IEEE Intl Conf on Computat Intel in Financial Engin, 1(1), 363-370.

Cited by 27 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Pro Trader RL: Reinforcement learning framework for generating trading knowledge by mimicking the decision-making patterns of professional traders;Expert Systems with Applications;2024-11

2. Algorithmic Trading Using Double Deep Q-Networks and Sentiment Analysis;Information;2024-08-09

3. A Transparent Single Financial Asset Trading Framework via Reinforcement Learning;Selected Papers from the 10th International Conference on E-Business and Applications 2024;2024

4. Ensemble Deep Reinforcement Learning for Financial Trading;Intelligent Systems Reference Library;2024

5. A reinforcement learning algorithm for trading commodities;Applied Stochastic Models in Business and Industry;2023-10-03