Understanding our LLM-based research approach
Our platform uses large language models (LLMs) to analyze publicly available financial information and generate research assessments. The model reads through SEC filings, earnings transcripts, and reputable financial news to form opinions about stock outlook probabilities and volatility characteristics.
Median absolute daily price change in typical market conditions. Represents the model's estimate of normal day-to-day volatility without major catalysts.
80% confidence interval for total return over the next 30 days. Reflects the model's assessment of likely trading range based on current fundamentals and market conditions.
Scaled probability (0-100) of experiencing an overnight price gap of ≥3% within the next 30 days. Higher values indicate greater likelihood of sudden price movements.
When a known catalyst (earnings, FDA approval, etc.) is approaching, this shows the expected price range during the ±7 day window around the event, reflecting event-specific uncertainty.
Single-episode peak-to-trough decline that is unlikely to be exceeded 95% of the time over a 12-month period. Represents tail risk assessment for significant downturns.
These assessments are for informational research purposes only and should not be construed as investment advice, recommendations, or inducements to buy or sell securities.
Professional Advice: Always consult with qualified financial advisors before making investment decisions. Consider your own circumstances, risk tolerance, and investment objectives.