Harnessing LLMs in Mixture of Experts for Smarter Trading Strategies
Introduction
Financial markets are complex and highly volatile, demanding robust and adaptive trading strategies. Traditional methods, such as statistical modeling and machine learning, often fall short in handling dynamic market conditions. To address these limitations, researchers have proposed a Mixture of Experts (MoE) approach, which distributes decision-making across multiple specialized models.
This paper LLM-Based Routing in Mixture of Experts: A Novel Framework for Trading introduces LLMoE—a novel framework that integrates Large Language Models (LLMs) as routers within an MoE architecture. We are going to implement that isn this blog post.