This repository full of ressources in financial analysis using different quantitative techniques.
- Quantitative portfolio management: Strategies, backtesting frameworks, and optimization algorithms for crafting portfolios that stand the test of market volatility.
- Numerical methods in finance: From Monte Carlo simulations to finite difference methods, explore computational techniques that power modern financial engineering.
- Econometric analysis: Tools and notebooks dedicated to uncovering economic insights from data, employing everything from regression analysis to vector autoregressions (VAR).
- Time series forecasting: Cutting-edge models for predicting financial markets, LSTM networks, MLP, Random Forest with detailed and well commented scripts.
- Download the necessary Python/RStudio environment: Make sure to have all the necessary code environment set up in order to run the scripts properly.
- Clone the repository: Get your local copy.
- Explore the notebooks: Each notebook comes with detailed explanations and code comments.
- Join the community: Participate in discussions, share your findings, or contribute to ongoing projects.
Got a project or an idea that can enrich our repository? We welcome contributions of all forms - new models, improvements to existing ones, or educational content.