A Comprehensive Review on AI-Powered Candlestick Pattern Detection for Stock Market Analysis.
Authors/Creators
- 1. Student, Department of MCA, R V Institute of Technology and Management, Bengaluru, India (Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India)
- 2. Assistant Professor, Department of MCA, R V Institute of Technology and Management, Bengaluru, India (Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India)
Description
The financial markets are dynamic and complex, with stock price movements influenced by numerous factors. Traditional methods of technical analysis often rely on manual identification of patterns, which can be time-consuming and prone to human error. This comprehensive review examines the application of Artificial Intelligence (AI) and machine learning (ML) models for automated candlestick pattern detection. The article analyzes various AI-based approaches, including convolutional neural networks (CNNs), object detection algorithms like YOLOv8, and fuzzy logic systems, highlighting their effectiveness in identifying patterns and informing trading decisions. The review discusses the advancements in the field, evaluates the performance of different models, and explores the challenges and future directions of AI in financial market analysis. Our findings indicate that AI-powered systems can significantly enhance the accuracy and efficiency of technical analysis, providing a powerful tool for investors and traders.
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