This research introduces a novel prompt framework that enhances LLMs for financial market applications using Reinforcement Learning from Market Feedback (RLMF).

• Addresses LLMs' lack of contextual alignment in financial applications
• Incorporates market-specific features and short-term price dynamics
• Generates more precise trading signals than traditional LLM approaches
• Bridges the gap between general language capability and specialized financial insight

Security Impact: The framework improves financial risk management by creating more reliable trading signals, potentially reducing market volatility and enhancing investment security.

FinRLlama: A Solution to LLM-Engineered Signals Challenge at FinRL Contest 2024