GaTech OMSCS Machine Learning - Spring 2016

Methodologies

Data: SPY stock

1. mc1-a1 - Standard deviation and environment validation
2. mc1-p1 - Implementation of Portfolio metrics: Sharpe Ratio, volatility on daily returns, and cumulative return
3. mc1-p2 - Portfolio optimization with sci-py
4. mc2-p1 - Market simulation with fund and SPY metrics
5. mc2-p2 - Implementation of Bollinger Bands for buy and sell strategy with backtests
6. mc3-p1 - Implementation KNN, Bagging, and Linear Regression Learners
7. mc3-p2 - Implementation of KNN, Bagging, and Linear Regression Learners as portfolio strategy (see readme file for additional information)
8. mc3-p3 - Implementation QLearning for portfolio strategy