Framework
What is the market pricing, and is it right?
Stock, bond or term loan, the setup is the same: find the number the market is implying, decide whether it's right, and build a falsifiable case for why it isn't. An idea borrowed from Howard Marks.
Where it comes from
Superior insight into value
“To achieve superior investment results, your insight into value has to be superior. Thus you must learn things others don’t, see things differently or do a better job of analyzing them — ideally, all three.”
The question in this page's title is my way of putting that into practice. Asking what the market is pricing forces the view to be specific enough to disagree with; asking whether it's right is where the three sources of superior insight come in.
An expert call with Wolfe Research on GPU useful life. An interview with a UW–Madison Nuclear Engineering PhD. ULTA store visits and consumer interviews.
Reverse DCFs and spread comparisons turn a narrative into one figure — 45% pipeline conversion, 77bps for a deleveraging BBB — that can be challenged.
Stage-gate probabilities, collateral recovery ranges and horizon scenarios — with an explicit statement of what would prove the thesis wrong.
Applied
How it played out in each report
The market's question was whether a ~$60B debt-funded GPU buildout could service its debt. The lender's question was narrower: if it can't, what is the collateral worth? An expert call with Wolfe Research on GPU useful life, combined with tiered LTV advance rates and take-or-pay contract coverage, supported 40–60% recovery — enough to make a 10.3% base-case return worth the risk.
At 77bps OAS the notes looked fairly priced against the BBB Technology curve. The disagreement was with the peer comparison: HPQ traded ~20bps wide to Dell despite lower leverage, with net leverage on a path from 1.46× to 0.99× by FY27E. Not mispriced fundamentals — upgrade optionality the spread wasn't paying for.
A reverse DCF extracted the market-implied pipeline conversion probability: 45.2%. Stage-gate close rates from comparable infrastructure projects put it at 65%. Applied to the 72-module TVA/ENTRA1 pipeline, that 20-point gap is $2.48/sh. Not a qualitative view on nuclear — a calculated disagreement with one number.
Placer.ai foot traffic showed ULTA gaining share (+3.8% YoY) while specialty retail fell 2.1% — months before it showed up in same-store sales. The saturation narrative had already been contradicted. A second, independent path — margin recovery +140bps vs. Street — pointed the same way.
Primary Research
Get close enough to the underlying reality that the model reflects something true, not just something plausible: two ULTA store visits and consumer interviews; an interview with a UW–Madison Nuclear Engineering PhD on reactor design and failure modes; an expert call with Wolfe Research on GPU useful life.
Badger Fund · Risk Manager & Analyst
A different mandate, the same question
I co-manage risk for Badger Fund, a $5.6M student-run long/short SMID-cap book benchmarked against the Russell 2500 Growth. The mandate is different from the research above: NuScale would not pass the fund's screens — no ROIC history, negative FCF. The fund targets companies that are already profitable and growing, where the question is whether the market has priced the durability of that growth.
On the risk side, the job is making sure the book is exposed to the bets it intends to make and not the ones it doesn't. I monitor gross and net exposure, factor tilts and tracking error against a 6-point compliance framework built on Barra's 13 risk indices, and built the fund's flag-review-act process for responding when a limit is approached.
Different tools, same habit: find the specific assumption — in a stock, or in the portfolio — that is wrong.
A position or exposure approaches a guideline limit.
Identify what is driving the exposure and whether it is intended.
Bring the book back within its guideline limits.
Screening process
Names passing the screen proceed to a full report and a 3/5 committee vote before entering the portfolio. Exit triggers include thesis invalidation, price target reached, and 15% relative sector under/outperformance.