Identifying stock patterns and training Classifiers for suggesting investments

This paper explores and analyzes the stock data of companies listed in NASDAQ100 and tries to find out if there is any correlation between various attributes of stock data like opening, closing, daily, weekly, monthly and yearly change in stock prices of these companies. The paper also explores for any market trends that may exist in the stock data up to 2017, and finally train a classifier that gives investing advice to buy/hold/sell stock for the companies listed in NASDAQ100 using machine learning.