AI for Quantitative Trading

The overall goal of the project is to use Artificial Intelligence (AI) and Machine Learning (ML) techniques to predict stock market movement trends by developing a Supervised learning model. This was accomplished via a python framework utilizing the sklearn library (pandas and numpy), a web-based application (jupyter notebook) and the application of a labeling strategy and the utilization of a Supervised Learning AI model (Random Forest). The Nvidia (NVDA) stock data was utilized for this project. Methods included loading data from Yahoo Finance, adding various stock indicators such as moving averages, momentum, volatility and volume indicators, and Bollinger Bands. A labeling strategy was then developed and used to label the data in training the model to perform the prediction of the market movement on NVDA stock. 

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