• S S DHARSHAN
• Dr. S. Subashini
• M. Dinesh Kumar
• N.M.R. Harrish Nandha

The volatility and unpredictability of the stock market make it difficult to forecast movements. This analysis looks into how prediction accuracy can be increased by using historical data and APIs such as Yahoo Finance for current datasets on stocks, Binance, futures, commodities, index funds, and economic indicators. The study provides deeper insights into future movements by identifying important factors influencing market behavior through the analysis of trends, patterns, and seasonal variations. Recurring trends are found using methods like time series analysis, underscoring the significance of data-driven strategies. The results imply that even basic techniques like pattern recognition and trend analysis can improve the accuracy of stock market forecasts. This highlights how important it is to use historical data to guide better investment strategies by assisting with risk management and making well-informed investment decisions.

Predictive Analytic, Time Series Analysis, Data Analytic, Big Data in Finance, Market Trends.

"ENHANCING STOCK MARKET PREDICTIONS THROUGH DATA ANALYTICS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.b488-b491, November-2024, Available :http://www.jetir.org/papers/JETIR2411164.pdf

"ENHANCING STOCK MARKET PREDICTIONS THROUGH DATA ANALYTICS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. ppb488-b491, November-2024, Available at : http://www.jetir.org/papers/JETIR2411164.pdf