Predicting the Movement of Index (Bank Nifty) Using Day’s First Support & Resistance with Pivot Points Standard Indicator

Predicting stocks and stock indexes movement has remained a primary focus of scholars in nearly all emerging and developed countries because interest to investors and policymakers. Predictive modelling for stock prices refer to models that can accurately interpret and anticipate events based on examining historical data to speculate on possible future prices. This paper analyses the internal representation of a system that predicts the best times to purchase and sell equities on the BSE & the NSE. First, support and resistance are used, which are established by candlesticks of contrasting colours, and the point of control is combined with open-interest data to complete the depiction. For NIFTY, BANK NIFTY, and FNO stocks, a variety of learning algorithms and prediction methodologies are formed. Simulations of stock trading demonstrated a high potential for profit using the prediction method, and the process created accurate predictions. We have examined the trend of intraday trading volume on 2 Indian exchanges (the BSE & the NSE), and replicate our study over the course of 264 trading days to ensure that our findings are consistent.