What Is How AI Stock Analysis Actually Works (And What to Trust)?
AI stock analysis combines computational models with market data to evaluate investment opportunities. There are two fundamental approaches: deterministic analysis, where structured signals are computed from market data and interpreted by AI, and generative analysis, where models generate opinions based on training data patterns.
Why It Matters
The critical distinction is auditability. Deterministic analysis provides traceable computation logs showing exactly how each score was derived. Generative analysis produces plausible-sounding opinions that may or may not reflect current market conditions, with no way to verify the reasoning chain.
How LyraIQ Approaches This
LyraIQ uses a deterministic-first architecture where six signals (trend, momentum, volatility, liquidity, trust, sentiment) are computed by proprietary engines before Lyra interprets them. Every score is traceable to its data source, and every interpretation is grounded in computed metrics rather than pattern-matched opinions.
Practical Steps
- Verify whether the AI uses deterministic computation or generative opinions
- Check if scores are traceable to specific data sources and formulas
- Evaluate the model's performance across different market regimes
- Look for regime-aware context, not just isolated metrics
- Confirm that the AI cannot hallucinate metrics — only interpret computed data