Analyzing and predicting the volatile market patterns for trading using a Digital Twin
Team
- e18036, Mahela Bandara, e18036@eng.pdn.ac.lk
- e18149, Ishta Jayakody, e18149@eng.pdn.ac.lk
Supervisors
- Dr. Asitha Bandaranayake , asithab@eng.pdn.ac.lk
Table of content
- Abstract
- Related works
- Methodology
- Experiment Setup and Implementation
- Results and Analysis
- Conclusion
- Publications
- Links
Abstract
The project aims to explore and analyze volatile market patterns to enhance trading strategies through the implementation of a Digital Twin framework. The project delves into various sub-topics, including the application of Reinforcement Learning (RL) in Synthetic Trading Markets, a comparative study between Traditional and Automated Trading methods, Algorithmic Trading strategies, and the utilization of Reinforcement Learning techniques for trading optimization. Additionally, the project investigates investment handling techniques to effectively balance risk levels and maximize returns. By integrating these components within a Digital Twin framework, the project seeks to develop robust trading models capable of adapting to dynamic market conditions, thereby empowering traders to make informed decisions and achieve sustainable profitability in volatile financial markets.
Methodology
Experiments and Findings
Expected Outcomes and Deliverables
Conclusion
In conclusion, this project embarks on a comprehensive exploration of volatile market patterns with the ultimate goal of enhancing trading strategies through the innovative framework of a Digital Twin. By delving into the realms of Reinforcement Learning, Traditional versus Automated Trading methods, Algorithmic Trading strategies, and the optimization potential of Reinforcement Learning techniques, the project aims to provide invaluable insights into navigating dynamic financial landscapes. Moreover, by incorporating investment handling techniques aimed at balancing risk and maximizing returns, the project strives to empower traders with robust models capable of adapting to ever-changing market conditions. Through these endeavors, the project envisions fostering informed decision-making and fostering sustainable profitability in the face of volatility.