A Review on Long Short Term Memory based Stock Price Prediction Techniques

The stock market is a widely-known financial vehicle with a significant influence on the global economy. It will be every investor’s ambition to be able to foresee the market’s rise and fall and profit handsomely from doing so. However, the future of prices is quite uncertain. Even though several types of analysis such as fundamental analysis, technical analysis, etc. have existed for quite some time. Today, several algorithms are utilized to make predictions about prices in the future. The ability to accurately forecast future stock prices is crucial since it provides traders and investors with valuable information about the market’s potential direction. Therefore, they will be able to enter or leave the market at the optimal moment. The most difficult endeavor is to foresee the stock market. There are many aspects to consider, both objective and subjective, rational and illogical. The combination of these elements makes it not only difficult but impossible, to make an accurate prediction of the price of shares. As part of our research, we analyzed several Neural Network techniques, including Long Short-Term Memory (LSTM) and Recurrent Neural Networks (RNN), both of which are effective in predicting stock price.