Indian Stock Market Forecasting Using Machine Learning Approach

Stock market investors have spent a lot of time trying to figure out how to predict stock prices so they can make more money. However, producing accurate and reliable predictions is difficult because of the many variables that might affect investor sentiment and, in turn, stock market movements. There has been a lot of research done on financial time series forecasting and related applications. Therefore, it is not simple to create a method that is both consistent and accurate. The importance of building sound models and obtaining credible outcomes remains unchanged. The objective of this paper is to predict future trends with high precision and crucial in the volatile financial environment of the stock market. In the methodology, we have used our proposed model with Nifty50 data from the financial year 2020–2023 daily data of opening prices and predictions in the stock market using several processes. Here we used Windowing techniques with Neural Networks to predict the future price values. The output shows our proposed model is robust and has a better prediction which is explained in the data analysis section.