Development of an Intelligent System for Stock Market Prediction Using Enhanced Deep Learning Technique With Banking Data

Abstract

The future may be unknown and uncertain, but there are still opportunities to make money by anticipating it. The request of AI and ML to stock market prediction is one such opportunity. Artificial intelligence may be used to generate accurate forecasts before investing, even in a dynamic environment like the stock market. The stock market's data is typically not stationary, and its properties are often uncorrelated. The stock market patterns that are traditionally predicted by several STIs may be inaccurate. To study the features of the stock market using STIs and to make profitable trading decisions, a model has been developed. This study presents an enhanced bidirectional gated recurrent neural network (EBGRNN) for detecting stock price trends using STIs. HDFC, Yes Bank, and SBI, three of the most well-known banks, have had their dataset evaluated. It is a real-time snapshot of the national stock exchange (NSE) of India's stock market. The datasets included business days from 11/17/2008 to 11/15/2018.