Financial Data Analysis

Financial data analysis leverages computational methods to extract insights from diverse financial data sources, aiming to improve decision-making in areas like algorithmic trading and risk management. Current research emphasizes the application of large language models (LLMs), often fine-tuned for financial contexts, alongside traditional data mining techniques and knowledge graphs, to analyze both numerical and textual data (e.g., news sentiment, financial reports). This work is significant because it promises more accurate and efficient risk assessment, improved portfolio management strategies, and a deeper understanding of market dynamics.