AI BriefingVerified LLM Routine
Key point
In investment research, a chain that enforces a fixed task order works better than an LLM's default reasoning.
Details
Here's a summary of results from using LLMs for real capital small fund research over several years.
Chain of thought works, but performance improves significantly when you specify the order a human expert analyzes things in, rather than simply adding "step by step."
The recommended order is roughly as follows.
- Understanding the business model
- Competitive landscape analysis
- Financial analysis
- Management evaluation
- Valuation
- Risk identification
In particular, if you have the model do valuation first, it tends to produce shallow conclusions that just fit numbers without understanding the company, so designing the order of reasoning itself is considered important. The key point is that the model's default path is optimized for generating fluent sentences, while an expert's path is optimized for analytical accuracy.
Also, investment analysis isn't a single task completed in one shot but a problem bundling multiple sub-tasks, so problem decomposition is said to be very important. This is because a misunderstanding of the business model propagates into the competitive analysis, and that distortion in turn propagates into financial forecasts and valuation, accumulating errors.
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