The task of predicting future value of company stocks accurately is Stock Market prediction. Successfully estimating the future price of a stock will result in great profit. In this paper, we explore different kind of non-linear models for predicting the stock behavior. We would be implementing three popular algorithms for stock prediction namely – convolution neural network (CNN) using 1d convolution, Long Short-Term Memory (LSTM) and the recurrent neural network (RNN) to gain profits by buying shares which have the potential to be sold at a much higher rate resulting in significant profit. At last, a comparison will be done between the three algorithms stated above to find out which among them was the most effective one and hence could yield a maximum profit when invested in a stock market.