LLMs and Gamma Exposure: Obfuscation Testing for Market Pattern Detection

This research investigates the ability of Large Language Models (LLMs) to identify subtle patterns in financial markets, specifically gamma exposure. The study's focus on obfuscation testing provides a robust methodology for assessing the LLM's resilience and predictive power within a complex domain.

• •The study explores the application of LLMs in analyzing complex financial data.
• •Obfuscation testing is used to evaluate the LLM's ability to discern patterns under challenging conditions.
• •The research focuses on detecting gamma exposure patterns in the market.