Author(s) :

Abhigyan Ranjan.

Volume/Issue :

Abstract :

The growth of big data has transformed stock market analysis, especially in real-time environments, by enabling the aggregation and processing of diverse data sources, including stock prices, financial news, and sentiment from social media. This paper examines the role of big data in real-time stock market analysis and proposes an integrated approach utilizing YOLOv5, a high-performance object detection model. By analyzing visual data streams for events impacting stock values, we aim to create a system that enhances traditional data-driven analysis. Key contributions include the integration of visual and textual data sources, the implementation of machine learning for prediction, and the use of big data tools to ensure low-latency, real-time processing.

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