Machine Learning in Stock Trading
Student
Yuanyuan Qiu
Advisor
Paul Schrater
Abstract
In this project I investigate a variety of machine learning models to make market decisions based on the stock price movements. Leveraging various technical and economic indicators, the objective is to identify and optimize the buy and sell triggers to maximize trading profits of three stocks: SPY, TLT and USO, covering different types equities in the market. I formulate the trading problem as three different problems: Classification, Regression and Reinforcement Learning, which are solved by different machine learning methods respectively.