Stock Market Prediction using Machine Learning

Stock Market Prediction using Machine Learning

Priyadarshini Patil, 1. Abhijeet Naikade, 2. Adesh Dhumal, 3. Shubham Bangar, 4. Shubham Harmale

D. Y. Patil College of Engineering, Pune

Abstract—In this report we analyze existing and new methods of stock market prediction. We take three different approaches at the problem: Fundamental analysis, Technical Analysis, and the application of Machine Learning. We find evidence in support of the weak form of the Efficient Market Hypothesis, that the historic price does not contain useful information but out of sample data may be predictive. We show that Fundamental Analysis and Machine Learning could be used to guide an investor’s decisions. We demonstrate a common flaw in Technical Analysis methodology and show that it produces limited useful information. Based on our findings, algorithmic trading programs are developed and simulated using Quantopian

Keywords: Stock Prediction, Data Analysis, Natural Language Processing, Machine Learning.