Source: Cointelegraph
Original: “Cryptocurrency Quantitative Trading Analysis Empowered by AI (Part 3): Agents and Large Language Models”

When AI Has a "Brain" and "Limbs"

The combination of agents and large language models (LLM) is upgrading AI from a "data analyst" to an "all-round trader." These systems can not only interpret market signals but also autonomously formulate strategies, execute trades, and even write analysis reports. This article will reveal how this technology is reshaping the future of cryptocurrency trading.

Agents - The New Employees of the Crypto Market

The core capabilities of agents include:

LLM - Enabling AI to Understand "Human Language"

Large language models (such as GPT-4) inject two superpowers into agents:

Input: Analyze the following information and predict the trend of Bitcoin for the week (up/down).

Information: The Federal Reserve raises interest rates by 50 basis points, Coinbase trading volume surges, Musk tweets support for Dogecoin.

Output: Up. Reason: The macroeconomic negativity has been digested by the market, the increase in both volume and price on Coinbase indicates capital inflow, and the celebrity effect boosts sentiment.

From Solo Operations to Team Collaboration

Multi-Agent Systems enhance efficiency through division of labor and collaboration:

This architecture achieved an annualized return of 45% with a maximum drawdown of only 12% in tests conducted in 2024.

Issues and Challenges

Although LLMs excel in understanding and generating natural language, they struggle with concepts directly related to the physical world. There are still many technical barriers to overcome before achieving fully trustworthy, self-reflective, and digitally sensitive applications. Among these, hallucination and overconfidence are two particularly prominent issues:

Additionally, LLMs face difficulties in handling token-level operational tasks, such as complex counting problems. This flaw limits the model's effectiveness in applications that require precise data processing.

Conclusion: The Future is Here, but Challenges Remain

Despite the immense potential of agents and LLMs, issues such as hallucination (generating incorrect information) and overconfidence (ignoring risks) still need to be addressed. In the future, with the development of explainable AI (XAI) and multi-agent collaboration, crypto trading may evolve into a "transparent battlefield," creating fair opportunities for ordinary investors.

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