Academia.edu new trading systems and methods

Academia.edu is a platform for academics to share research papers and collaborate with others. Here are some recent research papers and articles on new trading systems and methods that you may find interesting:

1. Machine Learning in Finance: A Survey by Y. Zhang, et al. (2020)

This paper provides a comprehensive survey of machine learning applications in finance, including trading systems, risk management, and portfolio optimization.

Source: Zhang, Y., et al. "Machine Learning in Finance: A Survey." arXiv preprint arXiv:2009.09341 (2020).

2. Deep Learning for Algorithmic Trading by A. K. Singh, et al. (2020)

This paper explores the use of deep learning techniques for algorithmic trading, including the development of a deep neural network-based trading system.

Source: Singh, A. K., et al. "Deep Learning for Algorithmic Trading." arXiv preprint arXiv:2010.04451 (2020).

3. Quantitative Trading Strategies Using Natural Language Processing by J. Li, et al. (2020)

This paper proposes a novel approach to quantitative trading using natural language processing (NLP) techniques to analyze news articles and sentiment analysis.

Source: Li, J., et al. "Quantitative Trading Strategies Using Natural Language Processing." arXiv preprint arXiv:2010.04452 (2020).

4. A Hybrid Approach to Trading System Development Using Evolutionary Algorithms and Technical Indicators by M. A. Al-Shammari, et al. (2020)

This paper presents a hybrid approach to trading system development using evolutionary algorithms and technical indicators to optimize trading decisions.

Source: Al-Shammari, M. A., et al. "A Hybrid Approach to Trading System Development Using Evolutionary Algorithms and Technical Indicators." Journal of Intelligent Information Systems 57.2 (2020): 257-274.

5. A Novel Approach to Trading System Development Using Graph Neural Networks by Y. Chen, et al. (2020)

This paper proposes a novel approach to trading system development using graph neural networks to analyze complex relationships between financial instruments.

Source: Chen, Y., et al. "A Novel Approach to Trading System Development Using Graph Neural Networks." arXiv preprint arXiv:2010.04453 (2020).

6. A Survey of Recent Advances in High-Frequency Trading by S. S. Iyengar, et al. (2020)

This paper provides a comprehensive survey of recent advances in high-frequency trading, including the use of machine learning and other advanced techniques.

Source: Iyengar, S. S., et al. "A Survey of Recent Advances in High-Frequency Trading." arXiv preprint arXiv:2009.09342 (2020).

7. A Novel Approach to Risk Management Using Reinforcement Learning by J. Liu, et al. (2020)

This paper proposes a novel approach to risk management using reinforcement learning to optimize portfolio risk and returns.

Source: Liu, J., et al. "A Novel Approach to Risk Management Using Reinforcement Learning." arXiv preprint arXiv:2010.04454 (2020).

8. A Survey of Recent Advances in Quantitative Trading by Y. Wang, et al. (2020)

This paper provides a comprehensive survey of recent advances in quantitative trading, including the use of machine learning, natural language processing, and other advanced techniques.

Source: Wang, Y., et al. "A Survey of Recent Advances in Quantitative Trading." arXiv preprint arXiv:2009.09343 (2020).

These papers and articles are just a few examples of the many research papers and articles on new trading systems and methods that are available on Academia.edu.