
Quantitative IPO research built on the signals you can actually see before a company starts trading. Every deal scored on the same framework, with no hindsight.
Companies with an active SEC filing or confirmed banker engagement, scored before they price. Pershing Square, Cerebras, SpaceX, Databricks, and more.
Historical IPOs, scored using only the S-1 data that was available before they listed. See how the model held up against the actual Day 1 returns.
A 0 to 100 score plus Day 1 pop and Week 1 hold probabilities, blended from binary deal signals and ratio quality, then adjusted for the current market regime.
Eleven yes or no signals pulled from each S-1 and the deal mechanics. Things like underwriter quality, float structure, anchor investors, lockup terms, growth, and profitability.
Gross margin, revenue growth, and cash runway scored on a continuous scale, then blended with the binary layer based on the current market regime (bull, neutral, or bear).
Valuation premium, Rule of 40, debt-to-revenue, burn multiple, and net revenue retention each push the score down where the fundamentals don't justify the price.
The composite maps to one of five labels (Avoid, Cautious, Moderate, Strong, or Exceptional) along with an estimated Day 1 pop probability and a Week 1 hold probability.