Financial Machine Learning Projects

Link to the project

The project encompasses various machine learning tasks, including:

1. Treasury Squeeze Prediction: Using SGDClassifier and KNeighborsClassifier, achieving moderate accuracy.
2. Corporate Bond Rating Analysis: Employing exploratory data analysis techniques.
3. Home Price Prediction: Comparing OLS, Ridge, and Lasso regression models.
4. Bond Price Prediction: Utilizing PCA, SGDRegressor, and SVMRegressors.
5. Credit Card Default Prediction: Implementing Decision Tree and RandomForest classifiers with high accuracy.
6. Corporate Bond Credit Rating Classification: Using advanced classifiers and achieving high accuracy with RandomForest.
7. Economic Cycle Prediction: Using RandomForest and AdaBoost regressors, achieving high R² scores across various timeframes.