The document summarizes a proposed approach to predict the rise and fall of a stock index using subtractive clustering, neuro-fuzzy inference systems, and a novel contribution factor algorithm. The approach involves obtaining historical stock market data, performing subtractive clustering on graphs of the data, generating initial rules from the clusters, predicting outcomes using ANFIS modeling, applying the contribution factor algorithm, and making a stock index rise or fall prediction. The goal is to help intraday traders efficiently analyze stock market movements.