Third-year Computer Engineering student - building a public lab docummenting experiments in quantiative finance, portfolio optimization, and risk modeling.
This repository serves as a research & development hub for:
- Pricing models and derivatives analysis
- Portfolio construction and allocation strategies
- Machine learning and Quantum applications in financial markets
- Optimization techniques for trading and risk management
(Planned - will evolve as research and studies progresses)
- notebooks/ # Research notebooks (yyyy-mm-dd-topic.ipynb)
- projects/ #Mini case studies with short reports
- src/ # Reusable code (models, pipelines, utils)
- docs/ # Notes, preferences, and technical summaries
- resources/ # Curated books, papers, datasets (will contain links only)
Languages & Labraries: Python, NumPy, Pandas, SciPy, Scikit-learn, PyPortfolioOpt, Matplotlib, StatModels, C++ Tools: Jupyter, Git, Github Actions (CI/CD), Conda/Micromamba Domains: Quantiative Finance, Optimization, Risk Modelling, Machine Learning
MIT Licance - see the LICENSE file for details.
This lab is a work in progress — structured for reproducibility, transparency, and continuous improvement.