Framework
The setup in every report is the same: extract the number the market is implying, decide whether that number is correct, and build a falsifiable case for why it isn't.
ASAP Research
In each report, the market was pricing something specific. The question was whether that number was right — and whether the data supported a different one.
A reverse DCF extracted the market-implied pipeline conversion probability: 45.2%. Stage-gate close rates from comparable infrastructure projects put the correct estimate at 65%. The 20-point gap, applied to the 72-module TVA/ENTRA1 pipeline, generates $2.48/sh of incremental value the market is not pricing. The conviction came from the specificity: this was not a qualitative view about nuclear energy — it was a calculated disagreement with one number.
Placer.ai foot traffic showed ULTA gaining share (+3.8% YoY) while specialty retail fell 2.1% — a leading indicator visible months before it appeared in same-store sales. The saturation narrative the market was pricing had already been contradicted. The question was how far consensus would have to move once the data caught up. A second independent path — margin recovery +140bps vs. Street — reinforced the same conclusion.
The market-implied OAS of 77bps did not reflect net leverage declining from 1.46× to ~0.99× by FY27. The opportunity was not mispriced fundamentals — it was upgrade optionality not reflected in current positioning. The same logic, extended into credit.
Common thread
On ULTA, I visited the store twice and conducted consumer interviews — verifying whether the Placer.ai foot traffic reflected genuine purchase intent or casual browsing. On NuScale, I interviewed a Nuclear Engineering PhD student at UW–Madison to stress-test the reactor design, failure modes, and pipeline conversion assumptions. In both cases: get close enough to the underlying reality that the model reflects something true, not just something plausible.
Badger Fund — Incoming Year 2
Starting in Year 2, I will serve as Analyst and Risk Manager at Badger Fund, one of two equity portfolios managed by students within Wisconsin School of Business. The fund runs a long/short SMID-cap book benchmarked against the Russell 2500 Growth.
The mandate is different from the ASAP research. NuScale would not pass Badger Fund's screens — it has no ROIC history and negative FCF. The fund targets companies that are already profitable and already growing, where the question is whether the market has correctly priced the durability of that growth, not whether a pipeline will convert.
The underlying question is the same in both contexts: is the market pricing the right number? The screens and the tools are different. The habit of finding the specific assumption that is wrong is the same.
Screening process
Names passing the screen proceed to a full report and 3/5 committee vote before entering the portfolio. Exit triggers include thesis invalidation, price target reached, and 15% relative sector under/outperformance.