algorithmic trading using machine learning and deep learning algorithms
Jupyter Notebook
algorithmic trading with deep learning
algorithmic trading using machine learning and deep learning algorithms
This project constructs an algorithmic trading system using Python libraries Numpy, Pandas, Matplotlib, Scikit-learn and TensorFlow.
The trading platform will incorporate machine learning and deep learning classification algorithms to learn and predict market
movement directions in order to place long or short orders to generate an over-benchmark cumulative return including transaction costs.
Stage One: give vectorized backtesting demo
Stage Two: add logistic regression, SVM and decision tree algorithms into the vectorized backtester
Stage Three: add a simple neural network and a complex convolutional neural network into the vectoized backtester
Stage Four: construct an event-based backtester with object-oriented design
Stage Five: learn and predict with the algorithms using the event-based backtester