Welcome to the Stock Market Manipulation using Deep Learning research project! This project focuses on testing advanced deep learning models to detect and understand stock market manipulation. By leveraging the power of deep learning techniques, we aim to uncover suspicious trading patterns, identify market anomalies, and contribute to a fair and transparent financial ecosystem.
main.ipynb: Contains the implementation of deep learning models and the training pipeline.data/: Includes curated datasets for training and testing the models.results/: Stores the research findings, experimental results, and analysis reports.assets/: Houses supplementary materials, such as diagrams and visualizations.loader/: Contains TAnoGAN dataloader for tensorflow API.
To get started with the research project, follow these steps:
- Clone the repository:
git clone https://github.com/username/repo.git - Install the required dependencies mentioned in
requirements.txt. - Explore the
code/directory for deep learning model implementations. - Access the
data/directory to obtain curated datasets for training and evaluation. - Analyze the research findings and experimental results in the
results/directory. - Utilize the supplementary materials in the
assets/directory for better understanding of the research.
We welcome contributions from the research community to enhance and expand this project. If you find any issues, have suggestions, or want to add new features, please feel free to submit a pull request. We appreciate your contributions!
You can find our presentation in our docs/ folder or on this link.
For any questions or inquiries regarding the project, please reach out to:
This project is licensed under the MIT Licence. Please refer to the LICENSE file for more details.
Join us in our quest to detect and combat stock market manipulation using deep learning techniques. Together, let's contribute to building a fair and transparent financial market environment.