Sectoral Dynamics and Market Forecasting - An Apriority-Based Study of NSE Nifty

Apriori Algorithm, Association Rule Mining, Predictive Analysis, Co-Movement of Market Index, Sectoral Indices

Predicting stock market performance and identifying the factors that influence stock prices is both intellectually engaging and financially rewarding. Accurate market direction forecasting enhances the decision-making capabilities of individual investors, institutional participants, and regulatory bodies. As a result, financial managers continually seek sophisticated tools to improve predictive accuracy. This study applies a machine learning approach - specifically, the Apriori algorithm - to analyze the trend (bullish or bearish) of the widely followed Indian stock index, NSE NIFTY. It aims to uncover the relationship between various sectoral indices - each representing the performance of specific industrial sectors - and the broader market index, NSE NIFTY. By mining association rules, the research identifies patterns within sectoral movements that may signal the subsequent day’s market direction, offering valuable insights for investors and financial decision-makers.