AIIntermediate#Tech#Execution
LLM Reasoning
L
Definition
The process by which an AI agent uses large language models (like DeepSeek or Claude) to parse news and market data into trading decisions.
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Concept Diagram
Key Takeaways
1
LLM Reasoning is the cognitive core of autonomous AI traders, transforming raw data into actionable trading decisions.
2
It uses a Chain-of-Thought (CoT) loop: inject context, weigh probabilities, then output a specific command to execute.
3
Unlike traditional algo trading, LLMs can semantically interpret unexpected news and adapt to Black Swan events.
4
The reasoning process integrates price data, order books, and social sentiment before generating an intent.
Practical Example
An AI agent detects DXY rising 0.5% and BTC dominance falling simultaneously. The LLM reasons: 'Strong dollar normally hurts crypto, but falling BTC dominance means alt season is starting — shift allocation from BTC to top altcoins.'
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Related Terms
AI
AgenticityThe degree to which an autonomous entity can perceive its environment, make decisions, and execute actions independently via smart contracts or LLMs.
AI
Chain of Thought (CoT)A prompting technique where the AI agent is encouraged to 'think step-by-step', improving logical reasoning in complex trading scenarios.
AI
Context WindowThe maximum amount of information (tokens) an AI model can 'remember' and process at any single moment during reasoning.
AI
Prompt EngineeringThe art of crafting specific text inputs to get more accurate or specialized behavior from an AI agent.
AI
InferenceThe process of an AI model using its trained knowledge to make predictions or decisions on new live market data.
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