This paper analyzes the application of Large Language Models (LLMs) in quantitative finance, focusing on the current state of LLM technology in financial applications, comparative analysis of leading models, Implementation frameworks for production systems, and risk management and quality control considerations.

This paper synthesizes over two dozen peer-reviewed studies on systematic cryptocurrency investment strategies spanning 2018-2025. We identify persistent market inefficiencies across three primary categories: cross-exchange arbitrage, factor-based investing, and on-chain metric signaling.

This research provides a comprehensive analysis of two fundamental approaches in quantitative portfolio management: thematic model grouping and consolidated alpha signal optimization.

The review analyzes systematic approaches that leverage macroeconomic factors and advanced quantitative techniques, emphasizing research that offers implementable insights while highlighting both established frameworks and emerging methodologies that have not yet experienced significant alpha decay.