Notebooks covering core machine learning methods and their applications in finance, from regression and clustering to neural nets, Monte Carlo pricing and CAPM performance attribution.
Author: Maci Sekander · M.S. Applied Mathematics & Statistics, Columbia University
| Project | What it does |
|---|---|
| ML Surrogate Option Pricing | Trains ML surrogates to approximate option prices and risk sensitivities (Greeks) |
| Performance Attribution (CAPM) · write-up | Regresses XLK, XLF and XLU excess returns on SPY (2018–2024) to separate beta from alpha, with hypothesis tests and regression diagnostics |
| Black-Scholes Options Pricing | Closed-form European option prices and Greeks |
| Monte Carlo Simulation | Repeated random sampling of price paths to estimate outcomes |
Finance & time series
- ARIMA Time Series Model
- Bollinger Bands
- Nasdaq Top 100 Analysis
- Stock Price Prediction
- Recurrent Neural Network Stock Predictions
- Fama-French factor data: F-F_Research_Data_Factors.csv
Supervised learning
Unsupervised learning
Getting started
Python · NumPy · pandas · SciPy · scikit-learn · statsmodels · pmdarima · Keras · Matplotlib · seaborn · yfinance
git clone https://github.com/MaciSekander/Machine-Learning-Projects.git
cd Machine-Learning-Projects
pip install numpy pandas scipy scikit-learn statsmodels pmdarima keras matplotlib seaborn yfinance pandas-datareader ta jupyter
jupyter notebook