And going be rough.

Portfolio is in red this year. Total current value $54,550 against the $58,119 we started the year with. We’ve clawed back about a third of the drawdown in the past weeks. One position is up 67%. One name lost 37% from cost and I’m still holding it.

The bright spot is passive portfolio, but thats not the subject of this substack.

The portfolio right now

Positions as of Friday’s close, sorted by performance since purchase:

I will go through each position laying out my current understanding.

Garrett Motion (GTX): the one that is working

Entered March 6 at $18.49. Friday close $30.98. Up 67.6% from cost. The position is now 15.5% of the book and the largest by dollar value behind cash.

The full thesis is in the GTX deep dive post.

At the time of the analysis market priced GTX extremely attractively with a small caveat. Main business is ICE and it’s going out of fashion.

I happened to disagree. And instead of testing my conviction market suddenly repriced the stock launching it high.

I think what every one caught on is REEV. Range-extender EVs are a separate category from PHEVs. In China the pure PHEV growth has stalled, but the REEV segment grew 181% in 2023, 124% in H1 2024, and is forecast at 17% CAGR through 2030. Every REEV needs a turbocharger that runs at fixed-RPM peak efficiency. That is exactly the engineering Garrett is good at. Li Auto, BYD, Geely, Leapmotor are all REEV players. Leapmotor is being built in Europe via a Stellantis partnership starting 2026, which is Garrett’s home turf.

Q4 2025 results were operationally strong, FCF held at $403M, they announced a $250M buyback for 2026 (about 4.4% of market cap). FY2025 results in February were a clean print. The stock walked from $18 to $32 over the spring on no real news, just the bear case quietly dying as more people realized ICE wasn’t going to fall off a cliff by 2030.

My model fair value is $41 vs current price of around $30. The position is 15.5% of the book carrying +67.6% of unrealized gain. Selling now to lock the gain is tempting but I’m holding.

One thing worth mentioning. Oaktree Capital holds 6.57% of their fund in this name, going back to the Garrett bankruptcy and emergence in 2020-2021. They’ve been gradually selling. Fairfax (Watsa) holds a smaller position and has also been reducing. Big-name distressed investors taking profits is not the same as conviction breaking, but it’s a flag worth tracking.

Dorman Products (DORM): boring as a feature

Entered April 3 at $100.19. Friday $116.16. Up 15.9% from cost. About 11% of the book.

The DORM post went up April 10 a week after purchase and after a bit of growth. I know, I know. I was a bit late.

What got me sold on DORM was the ROIIC profile. And I was working to update my whole portfolio understanding based on that.

The full methodology is in the ROIIC post, but for DORM specifically: 10-year ROIIC of 11.1%, reinvestment rate 76%, intrinsic value growth around 8.5% per year. The DCF said fair value $154 against a price of $100 at the time. Both the quality lens and the price lens agreed. That doesn’t happen often. When it does, you take the trade.

Q1 came in clean. Revenue +4%, EBIT margins held in the 16-17% range, FCF generation strong, guidance reaffirmed. Capital allocation continues to be disciplined. The thesis hasn’t been tested by adverse data. The position just compounds quietly. The way it’s supposed to work.

The hope..

As with GTX I am holding DORM. No need to change anything yet.

On Holding (ONON): the bull case validated, but I bought too high

Last years purchase at $44.90. Friday $37.26. Down 17.0% from cost. About 7% of the book.

The NKE + LULU + ONON positions now drag my portfolio like never before. And the drama is in.

I don’t think I’ve ever told the story how I got into ONON. The short version is - I’ve started seeing it everywhere. Not just on runners, but every second person I’ve met at the local mall had a pair.

Held it ever since and I disappointed me every time I’ve looked at it.

On March 3 they reported Q4 and missed on guidance. Stock cratered to the high $30s. The next few weeks were ugly.

This is the only position I’ve never had a model on.

I needed a way to justify keeping it. So I built two.

A base case with conservative APAC deceleration following the Nike China growth pattern, and a bull case where APAC stays hot and tariffs get absorbed.

Base case said fair value $21.02. Bull case said $39.24. The stock was at $35. Which model was right was a $20-per-share question.

The Q1 print on May 12 sort of answered it. Revenue +26.4% in constant currency against bull-case expectation of 26.9%. EMEA +25.6% (sixth straight quarter at 25%+). APAC +61.4%, now over 20% of the business with no visible deceleration. Adj EBITDA margin guide raised to 19.5-20%, implying EBIT in the 15.3-15.8% range, ahead of even the bull case for year one. Tariffs absorbed without lowering profitability, which neither model had built in.

The bull case is now the working fair value. The ONON is the next LULU in China framing turned out to be the right read, and I had it as a side bet rather than the main case.

Pure gamble if you ask me. Could have gone the other way.

I am still down 17%. The bull-case fair value is $39.24. Even if the bull case plays out exactly, the position only recovers to about $39 against my $44.90 cost. The Q1 print closed some of the gap but the math says I paid too much.

The current question is what to do with it. Hold and see if ONON improves? Or just sell it now as it reaches my valuation?

Guess I will have to decide sooner, rather than later. It is a growth company that might run out of steam. Especially given the NKE and LULU drama that is going in the background.

One observation that matters more than the position math: ONON Q1 was the cleanest validation of any model I’ve run. APAC was the decisive factor and the framing I used in the bull case (premium athletic share-shift, runway intact) turned out to be exactly right. I’ll see if it stands.

Nike (NKE): the position I have to talk about

Entered April 14 last year $56.13. Friday $41.88. Down 25.4% from cost. About 14% of the book.

This is the awkward one. Not because of the loss. Because the loss happened in a specific way that I was transparent about.

I wrote about my mistake in a separate piece: the NKE teardown.

The post lays out the five mistakes: instant-recovery margins from year one (no turnaround drag modeled), ΔNWC set to zero across all eight years, top-line growth peaking at 10% for three consecutive years instead of building bottom-up by segment (where it tops out at 6.6%), CapEx declining while revenue grows (internally inconsistent), and using FCFE instead of FCFF which made all the other errors easier to miss.

The old model wasn’t aggressive. It was just garbage. But it’s my first. Like the first love. Utterly undefensible.

That teardown post was the most uncomfortable thing I’ve written so far. I owned a stock based on a fair value that wasn’t real. Walking through five specific errors in your own work is a different exercise than critiquing someone else’s.

It hurts.

But it had to be public because I learned a lot in the past year.

So now I’m holding a stock the new model says is overvalued. Why? Three reasons, and none of them are good enough on their own.

The brand is real. North America wholesale was up 11% in Q3 FY26. Running grew 20%. The classics cleanup is in its late innings. Elliott Hill has a coherent strategy and he’s executing it. Tariffs are a structural ~120bp permanent headwind I’ve baked into the model, but the rest of the business is recovering.

The model could still be wrong on the upside. My new fair value of $38.33 caps the terminal EBIT margin at 12.5% to reflect tariffs as permanent. If the tariff regime eases, that cap is too low. The bull scenarios for normalized margins are in the $50-70 range, but I’d need a specific things to happen to upgrade. But I am not there yet.

Third is China. Greater China comps were -10% in Q3 FY26 and guided to -20% next quarter. The competitive displacement from Anta and Li Ning isn’t just macro, it’s structural. The bull-case argument that “China comes back” is the weakest link. But NKE is investing into new experience there. Lets see how this plays out.

Together those 3 are ways for upside to show. But then again..

10-year ROIIC essentially zero. Reinvestment dominated by debt-funded buybacks rather than productive capital. The brand is still the brand, but the capital allocation pattern of the last decade was extracting value from the business, not compounding it.

The ROIIC numbers don’t tell me to sell. They tell me to be honest about what I’m holding. I am holding a brand cyclically depressed, with structural headwinds, where management is shifting from financial engineering to operational rebuilding. That’s a fine thing to own at $25. Less obvious at $42.

I’m holding a position the model says is overvalued, or I treat it as an exit candidate. The next forced data point is Q4 FY26 results in late June. Probably the right time to sit down and decide.

Nomad Foods (NOMD): the macro you can’t escape

Entered late last year at $12.68. Friday $9.80. Down 22.7% from cost. About 7% of the book.

I refreshed this model today. Fair value went from $35.84 (previous model) to $27.13. A 24% cut on the same business.

The reasons are worth talking about because they apply to almost every European consumer name with European factories.

NOMD makes Birds Eye fish sticks, Iglo frozen peas, Findus everything. 18 manufacturing plants across Europe. World’s largest buyer of MSC-certified fish. They source vegetables from European growers, chicken from South America, and they freeze everything in factories that consume meaningful electricity and natural gas. The pre-2022 EBIT margin norm was about 12.7%. The 11-year average. The 6-year average. The number I had in my head when I bought the stock.

That margin was built on a regime that no longer exists. Cheap Russian gas piped into European factories. Cheap nitrogen fertilizer from Russia and Belarus flowing into pea and spinach grower contracts. Cheap-ish diesel for cold-chain logistics. The fertilizer-driven cost of agricultural inputs sat in the low single digits as a share of revenue. Everything was cheap.

That regime is gone. The 20-F discloses something the headlines don’t make explicit. NOMD’s “hedges,” the ones the CFO references on every earnings call, are physical fixed-price supply contracts that run one to twelve months. There is no financial commodity hedge book. The Note 29 disclosure says they hedge FX and interest rates only. When the 2026 fixed-price physical contracts roll into 2027, the company is fully exposed to spot energy and spot fertilizer prices.

The CFO was explicit on the Q1 call. Coverage extends through most of 2026. The incremental inflation starts flowing through the P&L in Q4 2026 and into fiscal 2027 if current conditions hold.

I spent the morning today on a ground-up cost decomposition of NOMD’s COGS from the 20-F Note 6, cross-checked against peer disclosures. Factory energy lands at 3-4% of revenue. Logistics fuel another 1-2%. Vegetable raw materials, where fertilizer is the embedded driver, around 5%. Poultry feed (corn and soy, also fertilizer-driven) around 4-5%. Total energy plus ag-commodity-linked inputs land at 14-19% of revenue, which is roughly 19-26% of COGS. A 30% sustained increase in those inputs is a 130-290 basis point hit to EBIT margin, partly offset by the €200M three-year cost program, leaving net margin pressure around 100-150 basis points.

The terminal margin in my updated model is 10.75%, anchored to FY2025 reality, not 12.7% from previous years. The 2027 sags to 9.0% as the contracts repricing into elevated spot. Fair value falls from $35.84 to $27.13.

So am I selling? Probably not. At least not yet.

At $9.80 the stock is below the 50% margin of safety line of $13.57. The market is pricing something materially worse than the new normal model assumes.

The bull trigger to watch is macro resolution. Sustained EU TTF gas back to €20-25/MWh ($200 per thousand cubic meters), Brent in the $50-60 range, fertilizer normalized, all three together. That implies Russia-Ukraine resolution with Nord Stream restart, and Mid-East de-escalation. If any of that happens, this model is too conservative and the fair value needs to come back up toward 12% terminal margin and FV in the $30-35 range.

But it’s a strong candidate for sell. May be I am missing something. No matter how much negative factors I add to my model, it’s still valued very conservatively by the market. What am I missing?

Lululemon (LULU): the deepest cut, and the most reframed

Entered in December 2025 at $190.08. Friday $119.14. Down 37.3% from cost. About 6% of the book. The worst drawdown by percent. The most chaotic narrative.

The stock has been a study in how many ways a position can hurt you in less than a year.

Q4 FY25 earnings on March 19 missed and the stock fell from ~$170 to the low $150s. Then drift.

Then on April 22 the company named Heidi O’Neill as CEO and the stock dropped 13.33% in a single session on the news. Then more drift, down to $119 by mid-May.

The CEO event is interesting. Heidi O’Neill came from Nike. Twenty-eight years at Nike. Most recently President of Consumer, Product and Brand. The market read this as “Nike-arc CEO joining a Nike-arc company.”

The activist investor Elliott had preferred Jane Nielsen from Ralph Lauren and didn’t get her. Chip Wilson, the founder with a 4.27% stake, launched a formal GOLD-card proxy contest nominating three alternative directors including Marc Maurer from On Holding.

The board responded by appointing Chip Bergh (ex-Levi Strauss CEO) and Esi Eggleston Bracey (ex-Unilever) as independent directors. The picture is board-vs-activist-vs-founder, three-way struggle.

Most of the analysts did not like O’Neill as a CEO.

The bear case for O’Neill is that she came from the late-Nike era of DTC oversaturation and lifestyle-over-technical product. That era hurt Nike’s margins. The argument runs: she’ll do the same thing at LULU.

The reframe I now hold is that LULU doesn’t need the same thing Nike did. Nike was a wholesale-heavy business trying to transition to DTC. The over-DTC playbook hurt them because they cut wholesale and lost shelf space. LULU is already 95%+ DTC. They don’t need to dismantle wholesale. They need to defend premium positioning against Alo Yoga and Vuori without resorting to markdowns. May be some innovation and quicker product development might help.

O’Neill’s actual playbook at Nike, before the strategic drift took over, was the opposite of margin compression. She grew the NCX (NikePlus) membership program at roughly 30% per year to over 100M members. She built the SNKRS app where gamified members spent five times more than guest shoppers. She launched the House of Innovation flagships in New York and Shanghai where visitors spent 30% more with the brand in subsequent months. That is retention plus monetization-per-customer playbook. That is exactly what LULU needs to defend its premium without discounting. Whether she imports that playbook or imports the late-Nike drift is the real question. The activist contest aside, the playbook fit is better than everybody gives her credit for.

I also sourced her compensation package details from the April 22 8-K. Base salary $1.4M, target bonus 200% of base, $10M annual equity awards split 60% performance-vesting RSUs and 40% stock options, one-time signing equity $7M, and a $2M cash retention bonus. Pay at risk is about 77% of total comp. The 60/40 RSU-to-options mix is bullish-skewed for a turnaround. The specific RSU performance metrics are not yet disclosed and will land in the FY26 proxy statement, which is the next document to read.

So today I refreshed the model again. I extended the EBIT margin trough by one year to reflect what I’m calling the lost year. O’Neill doesn’t take over until September 8, 2026 because of her Nike non-compete. First strategic articulation lands around December 2026. First operating year fully under her is FY2027. The previous model had margin recovering from 18.5% in FY26 to 19.5% in FY27 to 21% in FY28. The lost-year version holds 18.5% in FY27 and pushes everything right by one year.

New fair value $185.17. 30% margin of safety line $129.62. Current price $119.14 is $10.48 inside the buy zone. Not deep in the buy zone, but inside.

I’m holding the position.

Probably adding more if it continues to drift.

CASH: 40% bracing for the impact

214 shares of an iShares T-bill ETF. About $21,500. Yields whatever the front of the Treasury curve is paying, currently around 4.3% on an annualized basis.

S&P at ATH. recently made his statement about current market valuation. And I mostly agree.

I diligently track a lot of stocks that satisfy my criteria for investing. But finding good value is impossible. And even quality is right now - all trades at a premium.

Berkshire recently disclosed that they’ve tripled their position in Google at current prices. Which can be a bullish AI signal. Yet they still sit at a substantial pile of cash. And a few fellow substack investors have been discussing what could that mean. The consensus is bullish and I will write about that in the future. I think it is different with Google in particular. Google may be one of the few companies that in my opinion will get hit the least when AI cycle will inevitably come to a close.

So this cash will go either towards ideas that I find like DORM or GTX, or will serve as a dry powder if we get a major sell-off near the end of the year.

What I’m watching

The named events in the next 30 days are short.

GTX Investor Day this Wednesday. Largest dollar position, $250M buyback announced, multi-year framework reveal. Post-event model refresh window May 25-30.

LULU proxy battle is interesting piece of drama.

NOMD is a decision. Might finalize my first loss in this experiment.

ONON decision frame still open. Q1 print validated the bull case. Waiting for Q2 and then we will see.

NKE structural call is the longest open question in the book. Held against a model that says overvalued. Will probably need to dive deep into this one after next print.

What I have learned in eight weeks

Three things, none of them surprising in retrospect.

Sitting in losing positions is harder than the books make it sound. Especially when the model fair value keeps falling with each new data point. The discipline isn’t in being right. It’s in being honest about whether the thesis is still intact while the price moves against you. I am at peace with the answer on every position right now. That does not mean I’m right.

Old models from 2025 were materially overstated. NKE’s came down 53% on rebuild. LULU’s came down 32% on first refresh. NOMD’s came down 24% today. The shape of the errors was similar across positions. Once the framework changed, the fair values changed. Learning every day.

The most useful addition to the toolkit was ROIIC. It’s not a valuation tool. It’s a conviction tool. It tells me whether the business is actually good before the DCF tells me whether it’s cheap. Two of my positions look very different after running it.

The plan stays the same. Real money, real models, real positions disclosed with entry prices and sizes. No daily updates. No signals. When I have something worth your time, I publish.

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Trust your chuyka. Don’t let FOMO eat you alive.

Not an investment advice. Think for yourself. Don’t trust online experts.

I guess it will be useful to compare expenditures to other investors, so feel free to jump into the comment section. But first, a little intro.

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A passive investing disclaimer

Overwhelming part of my investments are currently passive. I’ve been running a passive portfolio for over 10 years, and so far it compounded at 7% a year. Which is a decent result. In line with my expectations.

The passive portfolio is 4-5 ETFs (depending on the period) - IVV, IEFA, VGLT, VCLT, PCY. As you can imagine - holding this costs close to zero. Establishing this portfolio on 2015 cost me a couple of books and articles read.

Yet I could not sit still.

In 2014 before I’ve started my investment journey I’ve read the normal stuff you read before you start investing. I’ve been lucky to start with value investing stuff like Graham, Buffet with a bit of Lynch. I could have gone trading route, but God and broker commissions saved me from that choice.

Long story short - that value investing thing did not stick. I’ve figured it took too much time, which was a precious resource for a new father and a devoted oil and gas warrior. So I quickly went full passive.

Value-investing side-quest

Now, with a bit of extra cash laying around I chose to come back to my roots. I’ve set aside $55 000 and started writing online about my side-quest to invest with a value-oriented stock-picking approach.

If you’ve been following me - it’s not been smooth.

My portfolio is bleeding red and even with S&P at ATH it’s not getting any better.

Seeing my passive portfolio up in 2026 and comparing it to 8% draw down in open active portfolio made me ask myself a question. Why am I doing this?

I am spending a lot of time looking for opportunities, researching them, doing DCFs, custom data analysis tooling. Thats quiet a significant portion of my free time.

And while on this thought I’ve also started adding up my expenses to run this thing. And they go way beyond broker’s fees.

Here is the breakdown of my costs.

The total runs at $5 450 per year.

On a portfolio that is $55 000.

What have I done?

Components

And I can’t really exclude much from this table. Here is my rationale for each.

Financial Modelling Prep

I found FMP to be the best and fastest source of data for my use case. I use Ultimate tier, which is $99 per month if you pay for the whole year. It has 30 years of financial statement data, prices, earnings calls, insider actions, analyst consensus.

Everything feeds into my analysis. An overkill? Not exactly.

You need at least 10-15 years of historical data to judge the business quality through stuff like ROIIC.

Earnings calls are essential to get management sentiment. You don’t just need a single company’s earnings calls - you should look into the whole sector and cross-check how they view their business and if management you target company is delusional.

Insider actions and analyst consensus is critical to judge how market views the current state of things. If you are bullish on the stock and everyone else is selling - you should be at least cautious in your conclusions. Markets can stay irrational longer than you can stay invested.

So FMP is a bedrock that everything else is built on.

Claude AI

I use a second to highest tier of Claude Max. I don’t have a degree in CS but a relatively robust understanding of LLMs and their limitations.

The primary use is - coding all the tooling that I need for models, screeners etc., since I don’t trust LLM math.

Claude also helps with reading. LLM is ok with 10Ks and earning calls. And since I don’t have a whole day to pour through them - I use it as a shortcut and self-imposed limitation for my experiment.

The logic being - if I can’t do a research with LLM, then there is no chance for retail investor to actually make money reading other analysts digests.

The Max tier also is mandatory since I do work in short bursts. Other tiers are quickly maxed-out and no progress been made.

Gemini AI

Acts as my main research helper for specific questions through Deep Research tool.

I found that it is more robust and gives better numbers and links if you aim it at a problem. Claude is prone to hallucinations and short-cuts if you give him an open-ended task with web-search.

I also enjoy Gemini as a companion to watching series like Game of Thrones for asking lore questions and getting explanations. So cost justified in my opinion :)

Financial Times, WSJ, Bloomberg

Arguably something I can actually think of cutting.

With so much writing here on substack, I have a hard time keeping up with all three.

But there is one huge drawback to substack that I can’t deal with right now. It’s algorithmic feed. I have to sift through “this AI prompt will make your stock research for you” and “how I’ve predicted next 100 bagger” before I get to actually relevant pieces.

With news outlets it’s much easier right now. They are not polluted with self-promotion and click-bait. Only reporting on subjects that currently matter. And the reporting quality itself is very good.

So may be one of them should go. But that is a hard pill to swallow.

One of the few blogs that I am actually paying for to read. His move to substack coincided with me starting my stock-picking journey and I enjoy reading and learning from him.

I believe this to be one of the most high-value sources for both education and stock-picks. People say he predicted the last 8 market crashes that never happened. But at least he is the one with skin in the game and suffers from his public convictions for everyone to see with the rest of us. Nothing but respect and a huge shout out.

Cassandra Unchained

Cassandra Unchained is now Dr. Michael Burry’s sole focus as he gives you a front row seat to his analytical efforts and projections for stocks, markets, and bubbles, often with an eye to history and its remarkably timeless patterns.

By Michael Burry

A bit of an off beat blog for stock market dwellers. But as an oil and gas professional and an energy nerd I find it most entertaining.

The analysis is spot-on and predictions are also public and clear.

I’ve been working to add oil and gas to my portfolio, but probably being an insider and knowing all the risks I have been too hesitant to act. Now all opportunities have been priced-out for me. So until next time.

Still a worthwhile read in my opinion.

Doomberg

A lateral-thinking approach to energy, finance, and geopolitics | Subscribe below for free previews of new articles | Click through to our About page for pricing and FAQ.

Private Server Hosting

This is a part of my experiment. My aim is to have my portfolio live with every step logged for public. That means my portfolio will have to live somewhere online.

There are cheaper alternatives. But given that I am not a professional coder I have to choose options that are user-friendly.

The page is still in development and most of the screenshots you see on this substack are from there. I am aiming to bring it live sooner rather than later so stay subscribed :)

Value vs Cost

So the question remains.

Is $5 450 per year justified on a $55 000 portfolio?

Probably not.

Probably there are cheaper ways to do the exact same thing with a -2,65% from inception result.

But here at Chuyka my aim is to provide real open view into the dealings of a random retail investor that is trying to beat his own long-term passive result.

All passive-investing community is preaching - is that it is impossible.

I think it is possible. It just takes a lot of grit and perseverance to achieve this. And I am here to f-around and to find out myself.

Feel free to jump into the comments section and share how your expenses look. I bet there are different approaches to data acquisition and analysis. Will be glad to learn.

Trust your chuyka. Don’t let FOMO eat you alive.

Not an investment advice. Think for yourself. Don’t trust online experts.

If you choose to stay with me and bear my clunky English pieces I will be forever grateful. If not, I cannot blame you. Writing this is as hard as reading. But I am trying to improve. And improve I will.

The value investing cosplay circa 2026

The Graham/Buffett game in 2026 is mostly cosplay. People say “good business at a fair price” and what they actually mean is “find something cheap with a story I can write about.” The story does the work. Fundamentals show up later as decoration.

The trouble is stories are easy.

Every dropping stock has one.

Every undervalued narrative has a following of believers explaining why this one is different.

What rarely shows up is the part where someone explains, in mechanical terms, what makes a business actually good. Not “wide moat.” Not “great management.” Real numbers about real things.

I’ve been working through this question for the last few months and ROIIC is the cleanest answer I’ve found so far. Not the only answer. But the one that most directly tells you whether the next dollar this business reinvests is going to be a good investment, or just a dollar. That distinction is the whole game.

This post walks through two ways to compute it. Huber’s version and Mauboussin’s version. One is quick. One is precise. I’ll show the formulas, where the inputs live on the 10-K, and run them both through Walmart 2006-2016 to see what the numbers actually say.

This is not an original idea and I am following the footsteps of Huber and Mauboussin. But that’s the way I learn and I hope you will learn too.

Why headline ROIC lies

Return on Invested Capital (ROIC) looks simple. Earnings divided by the capital the business uses to earn them.

ROIC = Earnings / Invested Capital

A business earning 20% on capital is producing more per dollar deployed than a business earning 5%. Headline ROIC is that number for the whole company at a point in time.

The problem is that ROIC does not give the “business quality today” picture.

Capital deployed in 2010 at 25% returns sits next to capital deployed in 2024 at 8% returns and you get a respectable-looking 17% blended number. The blended number lies. As an investor buying the business today, you don’t get the historical 25%, or even 17%. You get the future returns of the capital deployed. Whatever the business does with its NEXT dollar.

Picture two buckets. First is an old capital the company deployed a decade ago when it was a different business in a different market. Second is new capital deployed over the last few years at current economics. Headline ROIC stirs both buckets together. The investor buying today is lucky to only fund on second bucket terms. If situation is improving - that’s a good thing. But I rarely see companies that are improving today with tariffs, wars and other stuff going on.

Return on Incremental Invested Capital (ROIIC) is different to ROIC in that it measures the second bucket. The marginal return on capital actually being deployed recently.

ROIIC = ΔEarnings / ΔInvested Capital

The delta is the key. We look only at incremental.

ROIIC = (Earnings_year_N − Earnings_year_0) / (InvestedCapital_year_N − InvestedCapital_year_0)

Two endpoints, one subtraction each, one division. The formula is simple. The hard part is picking the right inputs, and that is where we introduce two investing experts: Huber and Mauboussin. Both are household names.

And before we go into details - one teaser. Pair ROIIC with a reinvestment rate and you get the punchline formula for how intrinsic value of a company compounds:

Intrinsic Value Growth ≈ ROIIC × Reinvestment Rate

A business with 25% ROIIC and 80% reinvestment compounds IV at 20% per year. A business with 10% ROIIC and 25% reinvestment compounds at 2.5%. Same math. Wildly different investor outcomes over ten years.

Most of value investing debate is about the price. This formula is about the business. The price determines your entry; this formula determines whether the business is worth entering at all. And that’s exactly what we are looking for to determine if the business is actually any good.

Method 1: Huber

John Huber at Saber Capital wrote the cleanest practical guide to computing ROIIC I’ve come across. His Return on Capital series is the curriculum I wish someone had handed me when I started taking this stock-picking thing seriously. The piece that compiles the math is Calculating the Return on Incremental Capital Investments. Read it. My summary is shorter; his original is better.

Huber’s recipe is mechanically simple. Two numbers at year 0, the same two at year N.

Earnings:

Earnings = Net Income

Net income off the income statement. The number the equity holder actually pockets after everything.

Tangible Invested Capital:

Tangible IC = Total Debt + Total Equity − Goodwill − Excess Cash

Why each piece:

• Total Debt because interest-bearing capital is real capital the business has to earn a return on.

• Total Equity because book equity is the cumulative retained earnings and paid-in capital the business is operating with.

• Minus Goodwill because acquired goodwill is price paid above book value, not productive capital.

• Minus Excess Cash because cash sitting idle inflates the denominator and depresses ROIC. A rough heuristic: anything above 2% of revenue for a mature business, 5% for a growth business.

Here’s the statement-to-line-item cheat sheet:

Pair ROIIC with a reinvestment rate, computed two ways:

Method A:

Reinvestment Rate_A = ΔInvested Capital / Σ Earnings (over the period)

Of every dollar the business earned across the window, how many got plowed back into the capital base?

Method B:

Reinvestment Rate_B = (RetainedEarnings_year_N − RetainedEarnings_year_0) / Σ Earnings

Of every dollar earned, how many stayed inside the company versus walking out as dividends?

The two should match. When they don’t, the gap is telling you something.

• Method A > Method B by a lot

  • Debt or equity issuance funded the gap. Capital came from outside, not from retention. Ask: is the debt service sustainable? Was the equity issuance dilutive?

• Method A < Method B by a lot

  • Retained earnings were returned via buybacks or used for debt paydown rather than deployed into new productive capital. Ask: were the buybacks below intrinsic value, or buyback-to-nowhere?

• Method A ≈ Method B

  • Clean reinvestment via retention. Default healthy case.

The final idea stays the same either way:

IV Growth ≈ ROIIC × Reinvestment Rate

Huber uses net income because it’s simple and it’s what the shareholder actually takes home. He admits in the piece that NOPAT or owners’ earnings are more precise. Enter Mauboussin.

Method 2: Mauboussin

Michael Mauboussin and Dan Callahan published Calculating Return on Invested Capital at Credit Suisse in 2014. It is the modern industry standard, 23 pages, dense, and worth every minute. If Huber wrote the practitioner’s recipe, Mauboussin wrote the reference manual.

The core difference is the earnings input. Where Huber uses net income, Mauboussin uses NOPAT. Three changes come with that swap.

Change 1: EBITA, not EBIT.

EBITA = Operating Income + Amortization of Intangibles

Depreciation stays as an expense. It represents real physical wear on real physical assets. Amortization of acquired intangibles is just an accounting echo of past M&A and gets added back. The goal is to capture the true operating cash earning power of the business, undistorted by prior acquisitions.

Change 2: Cash taxes, not the statutory rate.

Cash Taxes = Tax Provision + ΔDeferred Tax Liability − (Interest × Tax Rate)

Three pieces. The tax provision from the income statement, adjusted for any unusual items. The change in deferred tax liability captures the gap between book and cash taxes. A growing deferred tax liability reduces the current cash burden. The third piece is the tax shield on interest, which has to be removed to put levered and unlevered companies on equal footing. Otherwise a company with lots of debt looks artificially more profitable just because its interest expense reduced its tax bill.

Putting it together:

NOPAT = EBITA − Cash Taxes

Or the modeling shortcut Mauboussin gives for projections:

NOPAT = EBITA × (1 − Cash Tax Rate)

The cash tax rate is typically a touch below the statutory rate for growing companies.

Change 3: Invested capital from both sides of the balance sheet.

Mauboussin recommends computing invested capital two ways and reconciling.

Assets side:

Invested Capital = Net Working Capital
                 + Net PP&E
                 + Goodwill
                 + Other Operating Assets

Where net working capital is current assets minus non-interest-bearing current liabilities. Accounts payable counts as non-interest-bearing. Short-term debt does not.

Liabilities + Equity side:

Invested Capital = Short-term Debt + Long-term Debt
                 + Deferred Tax Liabilities
                 + Other Long-term Liabilities
                 + Preferred Stock
                 + Shareholders' Equity

The two sides should agree. When they don’t, that is the information. Usually it is a minority interest line, a weird long-term liability, or an inconsistent excess-cash adjustment that didn’t get propagated to both sides. Hunt it down and fix it.

Mauboussin’s universal decision rule for anything borderline:

“If you are wondering whether to include an item in invested capital, simply ask if the company could generate the same level of NOPAT without the item. If not, include it. If so, exclude it.”

That single sentence resolves 80% of the edge cases.

The Mauboussin ROIIC formula itself is the same shape as Huber’s, sharper notation:

ROIIC = (NOPAT_year_N − NOPAT_year_0) / (InvestedCapital_year_N − InvestedCapital_year_0)

The two methods side by side

The two frameworks are not alternatives. They are complementary. I default to Huber for the first pass because net income is what shows up 10Ks. Mauboussin sits next to it as a divergence check. When the two answers agree, the Huber number is reliable. When they disagree by more than five percentage points, something is going on with leverage or taxes or intangibles and it is worth figuring out what.

Both are cleaner if you run them on 5-year and 10-year rolling windows rather than a single snapshot. The 5-year catches cyclicality. The 10-year smooths through a full business cycle. Reading them together tells you whether a dip is cyclical or structural. Mauboussin actually walks through a Cisco example where the 1-year ROIIC was +304% in 2012, −778% in 2013, and the 3-year rolling came out at 47%. The 1-year numbers are noise. The window matters.

Worked example: Walmart 2006-2016

This is Huber’s canonical example. The data is public, the conclusions are non-obvious, and the contrast with what headline ROIC says is exactly the teaching moment ROIIC was built for.

I’m rounding. The real numbers are in Walmart’s 10-K filings on SEC EDGAR.

Step 2: Compute Tangible Invested Capital (Huber)

Tangible IC_2006 = $42B + $53B − $13B − $6B = $76B
Tangible IC_2016 = $44B + $78B − $17B − $7B = $98B

Huber’s numbers in his worked example are $76B and $111B. Mine for 2016 came out at $98B. The difference is Huber appears to include Walmart’s accumulated other comprehensive income, minority interest, and a slightly different cash adjustment in his total capital number.

I’m going to use Huber’s numbers because that is what his published analysis uses, but you can see right here the “this calculation takes 15 minutes” is actually “this calculation takes 15 minutes once you’ve decided which version of each line item to use.” :)

Using Huber’s numbers:

Tangible IC_2006 = $76B
Tangible IC_2016 = $111B

Step 3: Compute ROIIC

ΔNet Income = $14.7B − $11.2B = $3.5B
ΔInvested Capital = $111B − $76B = $35B

ROIIC = $3.5B / $35B = 10.0%

Walmart deployed $35 billion of incremental capital over a decade and got back $3.5 billion in incremental annual earnings. That is the marginal return on everything built between 2006 and 2016. Ten cents on the dollar.

For context, Walmart’s headline ROIC in 2016 was 13.2%. The headline number is what most investor commentary was built on. The marginal number is three full percentage points lower and that is the one that actually matters for the next decade of returns.

Step 4: Compute the reinvestment rate

Method A:

Reinvestment Rate_A = $35B / $148B = 23.6%

Method B:

Reinvestment Rate_B = ($90B − $49B) / $148B = $41B / $148B = 27.7%

Pretty close to each other. Method B is a touch higher, which means retention slightly outpaced deployment, which means some of the retained capital went into buybacks rather than productive capital. For Walmart that checks out. The company was buying back shares throughout this period. Not a red flag, just a description of what they were doing.

Step 5: Compute the compounding rate

IV Growth ≈ ROIIC × Reinvestment Rate
          ≈ 10% × 24%
          ≈ 2.4% per year

The investor who bought Walmart in 2006 should have expected about 2.4% annual intrinsic value growth just from the reinvestment math. Add the dividend yield (call it 2-3%) and some multiple expansion and you’re looking at total returns in the 5-8% range. Which is roughly what Walmart did from 2006 to 2016. The math worked.

Step 6: What the numbers actually say

Walmart in 2016 looked like a quality compounder. Headline ROIC 13.2%, the largest retailer in the world, steady dividend, defensive earnings. Every generic value investing commentary could include Walmart and nobody would blink.

The ROIIC decomposition tells a different story.

Marginal capital earning 10%, reinvestment at 24%, intrinsic value compounding at 2.4%. A legacy moat in late stage. The business was still high quality, but the per-dollar returns on new investment were already fading, and the total returns story depended almost entirely on dividends and buybacks, not on the underlying business growing.

Headline ROIC said great business. ROIIC said great business that had run out of places to put capital. Both statements were true. The second one was the one that mattered for buying in 2016.

What Mauboussin would do differently

Same company, same 10-K, same period. Mauboussin’s framework changes the numbers in three places.

Operating leases. Pre-2019 Walmart had a massive off-balance-sheet operating lease book. Store leases, equipment, vehicle fleet. ASC 842 hadn’t arrived yet. Rough-cut capitalization at 6-8x annual rent expense would add somewhere around $20-30 billion to the 2006 invested capital base and $25-35 billion to the 2016 base. Both endpoints get bigger. The differential also gets bigger. Net effect: ROIIC comes down another 1-2 percentage points.

NOPAT instead of net income. Walmart is not SBC-heavy and its tax rate is stable, so the swap from NI to NOPAT is cleaner than it would be for a tech company. The EBITA add-back for amortization of intangibles is small because Walmart’s intangibles are mostly goodwill from acquisitions, which doesn’t amortize. The cash tax adjustment matters a bit. Probably moves the numerator by a low single-digit percentage.

Both-sides reconciliation of invested capital. Walmart has minority interest from its international joint ventures, which appears on the liability side but not the asset side by default. The reconciliation forces you to decide how to treat it. Mauboussin’s convention is to include it. Adds a few billion to the denominator.

Net effect on Walmart 2006-2016: Mauboussin-adjusted ROIIC probably lands somewhere around 7-8%. Huber’s number is 10%. Both point in the same direction and both tell you Walmart in 2016 was a mediocre business for incremental capital deployment.

That directional agreement is the signal. When Huber and Mauboussin agree on a name, the simpler number is reliable. When they disagree materially, you have real work to do figuring out which distortion is responsible. For Walmart they agree. I trust the Huber number. For a debt-funded roll-up like TransDigm or a SBC-heavy hyperscaler like Nvidia, I would run both and dig into any gap.

Adjustments worth knowing about

Each of these can move ROIIC by several percentage points when they apply. Links go to the primary sources.

Excess cash. Strip it. Cash above about 2% of revenue for a mature business and 5% for growth is excess. Apple historically had hundreds of billions parked on the balance sheet and its ROIC looked mediocre until you stripped the excess cash, at which point the underlying business turned into one of the highest-ROIC operations in history. Direction: strip excess cash → IC goes down → ROIC and ROIIC go up.

Goodwill, in or out. Compute both. Including goodwill answers “did past M&A create value at the prices paid.” Excluding goodwill answers “what does the underlying organic operation earn on tangible capital.” Different questions, different decisions. For evaluating future M&A specifically, ROIC is the wrong tool entirely; Mauboussin says use NPV instead.

R&D capitalization. For software, pharma, semis, anywhere R&D is above ~5% of revenue, expensing R&D as it happens understates both the capital base and the NOPAT. The fix: capitalize cumulative R&D as an intangible asset, amortize over an industry-appropriate life (3-5 years for software, 10-15 for pharma), and replace the current period’s R&D expense in NOPAT with amortization of the accumulated balance. Mauboussin’s worked example: Microsoft FY2013 R&D was $10.4B vs $4.3B in capex. R&D was 2.4x the size of capex. Without capitalization, both NOPAT and invested capital are badly understated.

Owners’ earnings as the input filter. For tech and other SBC-heavy businesses, GAAP net income overstates real economic earnings because stock-based compensation gets added back as a non-cash expense. The cash spent on buybacks to mop up the resulting dilution is real money. Burry and Clifton have the cleanest treatment if you want the full version. For Nvidia, Meta, Palantir the right earnings input for ROIIC is owners’ earnings. For non-SBC-heavy businesses the adjustment doesn’t matter.

Hidden reinvestment in the income statement. Marketing spend at consumer brands. Customer acquisition cost at subscription businesses. R&D as already covered. These run through opex but function economically as growth investments. Separating maintenance from growth spend is harder than it sounds. The realistic move is to flag where it’s happening and note that the reported capex line is undercounting true reinvestment. A consumer brand spending 10% of revenue on marketing is reinvesting heavily even if its capex says otherwise.

Wrap-up

ROIIC is a quality screen and a trajectory tool. It tells you whether a business is good and whether the “good” is getting better or worse. It does not tell you whether the price is fair. That is what DCF is for. The two work together. I now use quality filter first, valuation second.

The reason to have both Huber and Mauboussin in the toolbox is that the gap between them is itself a signal. They agree on clean operating businesses with stable tax rates and modest intangibles. They disagree on leveraged roll-ups, SBC-heavy tech, and heavy-lease retailers. Each disagreement points you at the specific thing that distorts the simpler number. That is more useful than picking one methodology and pretending you know the answer.

ROIIC is also historical. Past ROIIC does not guarantee future ROIIC. Chipotle’s 35% ROIIC from 2006 to 2015 compressed sharply after 2015 as the unit growth runway saturated. The math gives you the baseline. The qualitative judgment about whether the moat persists and the runway stays open is still on you. The math just makes the qualitative question worth asking.

What I take away from spending the last few months on this: the catchy story is almost never the answer. My investments into NKE, LULU, ONON - are the prime example. The mechanical question of whether the next dollar of capital is going to earn a real return is almost always the right question. ROIIC is the first tool I reach for now. Everything else comes after.

Trust your chuyka. Don’t let FOMO eat you alive.

Not an investment advice. Think for yourself. Don’t trust online experts.

Speaking of the recent rally - here is the current state of my portfolio. It still feels like garbage. But I stand behind most of my positions. There is still capital to deploy and that’s what I am working on right now.

The one stock that’s quietly making money sells brake hardware, exhaust manifolds, and window regulators. Not AI. Not cloud. Not athleisure. Replacement auto parts.

There’s a lesson in this and it took me a while to see it.

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What Dorman actually does

When the window motor on your 2014 Honda Civic dies, you have two choices. Go to the dealer and pay $400 for an OEM part. Or your mechanic orders a Dorman part for $120 that fits the same, installs the same, and often lasts longer because Dorman actually fixed the design flaw that made the original fail.

That’s the business. Dorman reverse-engineers parts that break on cars, improves them, and sells them to mechanics and DIY enthusiasts through distributors like AutoZone and O’Reilly. They have 138,000 different parts in their catalog. Last year they introduced 5,335 new ones.

The key detail: about a third of what Dorman sells has no aftermarket alternative. They’re the only option between the dealer and nothing. That’s not a brand story - it’s an engineering moat. You can’t copy a reverse-engineered transmission control module by putting a different label on a Chinese generic. You need electrical engineers who can decode proprietary software, test it, and certify it works. Dorman has been doing this for 15 years. Their competitors haven’t started.

Why aftermarket is a compounder’s game

Here’s a number I keep coming back to: the average car on American roads is 12.8 years old. That’s a record.

Cars don’t get younger. Every year a car stays on the road, it needs more parts. Window regulators fail. Brake calipers seize. Exhaust manifolds crack. Electronic modules glitch. This isn’t cyclical demand that depends on consumer confidence or interest rates. It’s entropy. Physics doesn’t care about the Fed.

The aftermarket grows when car sales are strong (more cars on the road eventually). It also grows when car sales are weak (people keep older cars longer). The only scenario where it shrinks is if everyone stops driving, which hasn’t happened in a hundred years.

And the mix is shifting in Dorman’s favor. Modern cars have more electronics, more sensors, more modules that can fail. A 2024 vehicle has roughly 3x the electronic content of a 2010 model. When a $15 mechanical part becomes a $200 electronic module, the aftermarket grows without a single additional car on the road.

Dorman’s revenue hasn’t declined in 25 years. Not during the financial crisis. Not during COVID. Not during the tariff wars. The 30-year revenue CAGR is 10.2%. I haven’t found another business with that consistency. Take that with a grain of salt, it’s been just under a year, that I’m back to active stock-picking.

Is Dorman Products actually a quality business?

Good story is not enough. “Cars get older, parts break” is a nice narrative, but narratives don’t compound. Capital does. I need to know whether Dorman earns a real return on the money it puts back into the business - or whether it’s just growing revenue while destroying value.

I’ve been working through a framework for this. It comes from John Huber at Saber Capital (check out his substack, it’s a goldmine, now archived) - a fund manager who thinks about quality in terms of what the next dollar of invested capital earns, not what the historical average looks like. The concept is called Return on Incremental Invested Capital, or ROIIC.

The ROIIC idea is simple. Take the change in net income over 10 years. Divide by the change in capital invested over the same period. If the business earned $100M more than a decade ago and deployed $500M of new capital to get there, the incremental return is 20%. Every dollar invested created 20 cents of new annual earnings.

Headline ROIC - the number most screeners show - tells you about the average return across all capital ever deployed. A business that earned 25% in 2005 and earns 10% today might show 18% headline ROIC. Looks fine. But the marginal return is collapsing. ROIIC catches that. The investor who buys today is buying the marginal future, not the historical average.

ROIIC is a great indicator of quality. We must bear in mind that it has a trailing nature and past performance does not guarantee future results. But it is still a great way to analyse a company in numbers terms.

I’m writing a full post on this framework - the math, the methodology, how I apply it across my portfolio. For now, here’s what it shows on Dorman.

What the DORM ROIIC numbers say

Three things stand out.

First, the V-shape. ROIIC compressed from 10.4% to 4.4% in 2022-2023, then recovered to 11.1%. That was in my view the SuperATV acquisition digesting. Dorman bought a powersports parts company, funded it partly with debt, and spent two years integrating. Capital went up, earnings hadn’t followed yet. By 2025, the deal is earning and ROIIC is back above pre-acquisition levels.

Second, the 5-year is higher than the 10-year. 12.3% vs 11.1%. This is the recovery signal - recent capital is earning better than the long-run average. The SuperATV acquisition drag is washing out of the shorter window. When the 5Y is below the 10Y, the business is deteriorating. When it’s above, the business is improving. Dorman is improving.

Third, the reinvestment rate is 76%. Dorman puts three quarters of its earnings back into the business. Not buybacks. Not dividends. Back into new SKUs, new distribution, new engineering capability. And it earns 11% on every reinvested dollar. That’s management vote of confidence for their business engine.

Pop the the hood

There’s a second lens on this that I find even more interesting. When I strip out the financing costs - the interest on the debt Dorman took on for acquisitions - and look at the pure operating return on tangible capital, the picture changes dramatically.

The operating return is 26.8%. Not 11.1%.

The gap - 15.7 percentage points - is entirely the cost of acquisition debt. Dorman borrowed to buy SuperATV and a new deal in 2025. The interest on that debt eats into net income, which is what the 11.1% measures. But the underlying operations are earning 27 cents on every dollar of tangible capital deployed.

Why does this matter? Because debt gets paid down. Dorman’s total debt has already dropped from $849M to $633M since the SuperATV peak. As it continues to decline, the interest cost shrinks and more of that 27% operating return flows through to shareholders. The equity-holder return is converging upward toward the operating return.

It’s like buying a rental property with a mortgage - the property earns 12% on its value, but after mortgage payments you pocket 5%. As you pay off the mortgage, your take-home rate climbs toward 12%.

The moat assessment

Where does the moat actually sit?

It’s not brand (nobody knows Dorman outside of mechanics). It’s not patents (they have 500+, but the moat isn’t a patent wall). It’s not network effects. It’s a process advantage with three layers:

Speed. Dorman identifies failure modes, reverse-engineers a fix, and launches before anyone else. 1,659 “new to aftermarket” parts last year. By the time competitors copy, Dorman has moved to the next failure mode. The moat resets constantly - it’s a treadmill, not a fortress.

Complexity. Modern cars are stuffed with electronic modules - transmission controllers, engine computers, electronic steering racks. Reverse-engineering these requires decoding proprietary software. Dorman has 15 years of accumulated capability here. A Chinese generic manufacturer can copy a brake caliper. They can’t copy a transmission control module. And every year, the electronic content per vehicle increases. The barrier gets higher over time, not lower.

Scale. 138,000 SKUs. Distributors like AutoZone want one supplier who covers the catalog, not 50 vendors. Once you’re in the system at that scale, you don’t get ripped out. And when 21% of your competitors are in financial distress (per Lazard 2025), your 14% EBIT margins let you absorb the pricing pressure that bankrupts the 5%-margin players. You get their shelf space.

None of these alone is a wide moat. Together, they create a narrow-to-moderate moat that strengthens as the vehicle fleet ages and grows more complex. That’s the quality case.

The contrast that made it click

You still can feel that I’m sour from my Nike misjudgement. I tore it down last week and I am still digesting this position.

Nike earns less today than it did in 2015. It deployed $6.9 billion of incremental capital over a decade and generated negative $54 million of incremental earnings. The entire capital increase came from debt that funded share buybacks - not a single dollar went into productive reinvestment that grew the business.

Dorman is doing the opposite. It reinvests most of its earnings, earns 11% on that reinvestment (27% on an operating basis), and the business keeps growing. The trajectory is up, not down.

One is a compounder. The other is a cash machine running on fumes, returning money it doesn’t really have.

I own both. Draw your own conclusions about which one I’m more comfortable with.

What I paid and what I think it’s worth

I bought 50 shares at $100.19 during the early April sell-off. The stock was trading below my 30% margin of safety level for the first time.

The DCF model - built segment by segment, stress-tested with two NWC scenarios, cross-checked against a March version that arrived at the same number via different assumptions - says fair value is $154 per share.

That means I bought at 35% below fair value. In my framework, that’s comfortable. Not euphoric, not skinny - comfortable.

At the current price of $110, the stock is still 28% below fair value. The margin of safety hasn’t evaporated. It’s narrowed, but it’s there.

Key model assumptions:

• Revenue growth: 7-9% (management’s 2026 guide; I use 7%)

• EBIT margin: 15.5% near-term (tariff drag), recovering to 16.5% steady state

• WACC: 8.72%

• Terminal growth: 2.5%

The model is conservative by design. It assumes margins stay below the pre-acquisition 17-20% range.

If margins recover to 18%, fair value moves to $175+. I’m not modeling that because I haven’t seen it yet.

The risks I’m watching

Customer concentration. AutoZone, O’Reilly, and Advance Auto Parts together account for a significant chunk of revenue. If Advance Auto goes bankrupt (it’s struggling), Dorman loses a customer but likely picks up the volume through other channels - mechanics still need parts. The bigger risk is pricing pressure from consolidated customers.

Tariffs. Dorman sources about 38% from China (down from 70% a few years ago). Management has been diversifying aggressively, but a Section 232 tariff at 25% on aftermarket parts would compress margins by 1-2 percentage points. This is already in my model.

The SuperATV question. Dorman bought a powersports company (UTVs, ATVs) that’s 13% of revenue and carries lower margins. This is an adjacency move - auto aftermarket company branching into recreational vehicles. Adjacency diversification is a yellow flag in the ROIIC framework. It suggests core auto runway might be narrower than management says. I’m watching whether SuperATV margins converge upward or stay as a permanent drag.

Boring doesn’t mean safe. The stock dropped 30% from its 2025 highs before I bought it. It can do that again. Dorman is illiquid by large-cap standards - a $5.5 billion market cap with moderate trading volume. It moves fast in both directions when the market gets nervous.

Why this matters beyond one stock

I started this portfolio last year, and the most important lesson so far is that my instincts about what makes a good investment were exactly backwards.

I was drawn to the names with the stories. Nike - iconic brand, turnaround, new CEO. Lululemon - premium athletic wear, loyal customers, international expansion. On Running - the hot shoe brand that everyone’s wearing. These names selling at a discount were looking like slam-dunks.

Every one of those “exciting” positions now is deeply underwater. I know it’s too early to tell, but the boring one - the one that sells exhaust manifolds and window motors - is the one actually making money.

This isn’t a coincidence. Boring businesses often compound because nobody’s paying a premium for the story. There’s no narrative to inflate the multiple. No influencer wearing Dorman brake calipers on Instagram. The stock trades on cash flow and earnings growth, not on vibes.

The ROIIC framework made this visible in a way I couldn’t see before. Nike has a famous brand and negative incremental returns. Dorman has no brand recognition outside of auto mechanics and earns 11% on every dollar it reinvests. The framework doesn’t care about your feelings. It measures capital efficiency.

I’m not selling Nike or the other positions - each has its own thesis and timeline. But if I’m being honest about where my conviction is highest, it’s in the company that makes car door handles.

Chuyka check

My gut says this is the kind of stock you buy and forget about for five years. The business doesn’t need a turnaround, doesn’t need a new CEO, doesn’t need China to cooperate, doesn’t need interest rates to drop. It needs cars to keep getting older. They will.

I am much more comfortable holding this position than many others in my portfolio. And if fundamentals stay strong I am happy holding it for years to come even if bargain price keeps persisting.

The model says it’s worth $154. My gut says the model is conservative. The fleet keeps aging. The electronics keep getting more complex. The catalog keeps growing.

Sometimes boring is the best thing you can own.

50 shares of DORM at $100.19 average cost. Current price ~$110. Fair value estimate $154. This is not investment advice. Think for yourself. Don’t trust online experts.

Trust your chuyka. Don’t let FOMO eat you alive.

Go read it if you want. It’s in Russian, but the numbers are universal.

Дело пахнет керосином

Открываем сезон активных инвестиций

Отрицать свою предвзятость в выборе первой акции для возобновления вэлью-портфеля бесполезно. Но мы помним слова классика…

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a year ago · Ilya

But the story went in a wild direction.

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For a while, the market agreed with me. Nike ran to $74 - up 31% from my entry. I was sitting on $3,000 in profit, watching the thesis play out, feeling like a value investing god. Six months back into stock picking after a decade of index funds and already up 31% on my first high-conviction idea. Hard not to feel validated.

Then it went to $44.

I just rebuilt the model from scratch. New framework, proper assumptions, segment-level revenue, actual working capital math. New fair value came out at $38.

Not $77. Not even close. $38.

The stock currently trades around $44. I own 173 shares at a $56.13 cost basis. That’s roughly $2,000 in unrealized losses, or about -21% on the position. This mistake has a price tag, and I look at it every day in my portfolio.

This post is about the five specific mistakes that created a $43 gap between what I thought the company was worth and what it’s actually worth. Not hindsight. Every one of these errors existed when I built the original model and could have been caught then. I just didn’t know what to look for.

What the old model said

The bull case was straightforward. Nike has problems - everyone knows this. Failed DTC strategy, aging product lineup, new CEO cleaning up the mess. But the brand is iconic, free cash flow is healthy, and turnarounds at this scale tend to work eventually.

I used a simple FCF growth model. Conservative start - 5.5% growth while the turnaround plays out, then ramping to 10% as the recovery kicks in, then tapering back down to a 2.5% terminal rate. 9% WACC. Fair value: $77. At $55-56, that’s a 30% margin of safety. Textbook value entry.

I built a detailed Excel DCF.

Except it was wrong. By a lot.

What the new model says

Six months later, I rebuilt everything using an FCFF framework with segment-level revenue, explicit margin modeling, and actual working capital assumptions. Here’s the comparison.

Same company. Same public data. I was enthusiastic. After a decade of passive index funds, I was finally doing the stock picking thing again. I wanted to start buying. That energy is good for getting started. Less good for catching your own mistakes. The difference between these two models is not information - it’s questions I asked myself and answers I found.

The five mistakes

1. Real life is messy. Still try to model it.

On the revenue side, I actually did model a downturn - slow start, then ramp. I’ll show it below.

But on margins, I didn’t. I applied a flat 10% net margin from Year 1 through Year 8. No recovery curve. Just the destination.

Nike’s actual net margin was around 7% at the time. It has since fallen to 4.8%. The company was mid-CEO transition, reversing its DTC strategy, destroying $4 billion worth of classic franchise inventory, and eating tariff costs. All happening simultaneously. Every one of these drags on margins, and every one of them takes time to work through.

Look at the gap in the early years. That’s where the damage happens. The old model assumed 13% from day one while reality was sitting much lower and falling. The new model starts EBIT at 7.5% and takes six years to reach 12.5%.

The fix is to actually model the real world. Start at the current depressed level and build the margin back with specific drivers - NA wholesale returning, running category growing, classics cleanup finishing. Not the 13-14% Nike used to earn - tariffs make that ceiling unreachable now. 12.5% is the new normal in my opinion.

How did I calibrate the recovery speed? I looked at other consumer companies going through similar transitions. Lululemon’s 2013 CEO change cost 740 basis points of operating margin over three years. Gap lost 710 bps in its transition year. Under Armour lost 970 bps starting in 2022 and still hasn’t recovered. Even Starbucks, with arguably the smoothest handoff, lost 200 bps. These are all consumer brands with strong positioning. The pattern is consistent - 1 to 2 years of margin drag from decision paralysis, talent churn, strategy resets. Nike is doing CEO transition, DTC reversal, inventory cleanup, and tariff absorption all at the same time. Modelling instant recovery was fantasy.

The impact: Year 1 cash flow was overstated by roughly 60-80%. That’s $4.7 billion modelled vs $2.8 billion actual. Years 1-3 get the heaviest discounting in a DCF, but overstating them by that much still compounds through the whole model.

The lesson: If a company is changing strategy, don’t just model the final state. Try to understand how fast things actually move in the real world. Look for precedents - other companies that went through the same kind of transition. Study how their fundamentals reacted and how long the recovery took. History doesn’t repeat itself, but it sure rhymes. Use that rhythm to calibrate your model.

2. A growing business ties up more cash in inventory and receivables

I set change in net working capital to $0 for all eight projection years. So translating it to normal-people-speak - I was assuming it wouldn’t grow.

Think about what working capital actually is in a physical business. It’s sneakers sitting in warehouses waiting to ship. It’s invoices sent to Foot Locker and Dick’s that haven’t been paid yet. It’s the float between Nike paying its Vietnamese factories and collecting from its retail partners. That’s real money tied up in the physical operation of selling shoes.

When revenue grows, all of that grows with it. More shoes sold means more inventory in the pipeline, more receivables outstanding, more cash locked up in the cycle. Nike’s 11-year average is about 1% of revenue per year in incremental working capital needs. On $46-65 billion in projected revenue, that’s $500 million to $1 billion per year that the business absorbs before it becomes free cash flow.

Over eight years, ignoring this drained roughly $6-7 billion of cumulative cash flow from the model. That’s $4-5 per share in present value that simply didn’t exist.

The lesson: If the business is physical - it makes things, stores things, ships things, invoices customers - then growth costs working capital. The faster it grows, the more cash gets locked up. Model it as a percentage of revenue growth and check it against history. A $0 change only makes sense for a business that collects cash before delivering the product.

3. Build revenue from segments, not a single growth rate

As I mentioned above - I did model the downturn. The old growth curve started at 0%, ramped to 4%, and only then hit 10%. I wasn’t ignoring the downturn on the revenue side. The problem was where I assumed the recovery would peak.

Where did 10% come from?

I looked at Nike’s history and anchored to the best years. FY2012 was +16%. FY2015 was +10%. FY2023 was +9.6%. The COVID rebound in FY2021 hit +19%. If you cherry-pick the peaks, 10% looks conservative. But Nike’s 15-year median growth is 6.0%. The 10-year CAGR ending FY2025 is 4.2%. I anchored to the highlights, not the average.

And there’s a deeper issue.

The Nike that grew 10% in FY2015 may not exist anymore. Hoka, On Running, and New Balance own the cultural moment in running and lifestyle. Nike’s sportswear market share fell from 15.2% to 14.1%. China - which was 18% of revenue at peak - is structurally losing ground to Anta and Li Ning with government propping them up. Converse is in decline with no recovery timeline. The competitive landscape shifted, and a single growth number can’t tell you that.

If you try to build revenue from segments to get 10% consolidated growth - it requires miracles from Nike everywhere at once. North America is 42% of revenue and realistically does 6% in a good year. China can spike to 15% in a recovery quarter, but it’s only 13% of the total. EMEA peaks at 8%. And Converse is declining.

Blend it all together and the consolidated peak is 6.6%. Not 10%.

Look at this chart. Thirteen years of history on the left, projections on the right. You can see exactly where the 10% anchor came from - North America hit 18% in FY2014 and FY2023. China was the growth engine at 20-24% in the mid-2010s. Those peaks made 10% consolidated growth feel conservative. But those peaks came from a different Nike in a different competitive landscape. The projections on the right are deliberately calmer. Five regions, five completely different trajectories. China goes from -12% to +15% and back. North America is the steady engine but it’s slowing. No single number captures this.

The difference in terminal revenue: $75.7 billion in the old model vs $64.8 billion now. Every dollar of that excess flows through to margins and cash flow.

There’s another benefit in building by segments I didn’t expect. And this approach applies to modelling as a whole.

When you model by segment (or disaggregate other compound numbers), you’re building around the same metrics management tracks and optimizes. Earnings calls show you where their eyeballs are. Hill talks about NA wholesale recovery, China store resets, running category growth - these are specific, measurable goals. If I model NA at +6% because management is focused on wholesale rebuild, I can check that against actuals every quarter. Did they hit it? Are they ahead or behind? The model becomes a scorecard for management execution, not just a fair value calculator.

A single growth rate gives you nothing to check against. “Did Nike grow 10%?” is a useless question. “Did North America wholesale recover while China stabilized?” - that’s a proper question.

The lesson: Build revenue and other compound numbers from components. A single growth rate invites anchoring to historical peaks. Bottom-up forces you to justify where each dollar of growth comes from. It’s much harder to be accidentally optimistic when every geography has to work on its own. And it gives you a framework to judge management against their own promises.

4. CapEx must be consistent with revenue growth

I started CapEx at $919 million and declined it to $482 million by Year 8. Nike had been cutting CapEx for years - from $1.1 billion to $430 million. I just extrapolated the trend (wtf.. why?).

But those cuts are just turnaround measures. Cash conservation during restructuring. $430 million was Nike’s lowest CapEx since 2003, when the company was one-third its current size. You can’t grow revenue from $46 billion to $76 billion while spending $482 million on property, equipment, and technology. That’s 0.6% of revenue. Below maintenance for a company with $7.5 billion in PP&E.

And think about where the money needs to go. Hill’s strategy is “elevated retail presentation” - making stores feel premium again after years of underinvestment. China has 5,000+ monobrand doors that management admits “aren’t compelling”. They’re running pilot store resets in Beijing and Shanghai that show better traffic and comp growth. That’s the playbook - but rolling it out across thousands of stores costs real money. Nike Digital needs investment too. You don’t rebuild a brand experience on a declining CapEx budget.

The history tells you everything. Nike spent $900 million to $1.1 billion a year on CapEx in its prime (FY2014-2020). Post-COVID it collapsed to conservation mode - $430 million in FY2025, the lowest since 2003. The old model extrapolated that decline to $482 million by Year 8 - below FY2012 levels when Nike was half its current size. The new model ramps back to $1.3 billion, which is just getting back to where Nike was in FY2016-2019. A 3x gap by Year 8.

The lesson: Don’t extrapolate CapEx cuts during a restructuring. If your revenue is growing and your CapEx is shrinking, your model is broken. Something has to give.

5. Know what your valuation framework hides from you

The old model used FCFE - Free Cash Flow to Equity. Start with net income, add depreciation, subtract CapEx and NWC, adjust for net borrowing. Discount at cost of equity. FCFE is a perfectly valid method. For certain companies - especially financials or stable businesses with predictable capital structures - it can be the right choice.

But every framework makes trade-offs in what it shows you and what it buries. FCFE starts from net income, which blends operating performance with tax strategy, interest costs, and one-time items. When net borrowing is in the cash flow, you think less carefully about reinvestment needs. The margin assumption? Buried inside a single net income number. Working capital? Easy to forget when it’s just one more line in an already blended formula.

FCFF - Free Cash Flow to the Firm - decomposes the business differently. EBIT margin is a line item. Tax rate is a line item. D&A, CapEx, and NWC each stare at you from their own row. For a turnaround story like Nike, where the whole point is tracking margin recovery and reinvestment needs, that visibility matters.

The FCFE framework didn’t cause the other four mistakes. But it made them easier to make and harder to spot. I think didn’t deliberately skip working capital - the framework just didn’t force me to think about it.

The lesson: Understand the weaknesses of whichever framework you use. Every method hides something. If you know what’s hidden, you can check for it. If you don’t, you’ll find out when the model breaks.

The one thing I got right

In the original post, I wrote about competition. Satisfy, Bandit Running, Tracksmith. Hoka. On. I personally switched from Nike running shoes to Hoka after an injury. And I liked them more than Nike. I said so publicly.

That qualitative insight was correct. Nike’s competitive position is weaker than it was five years ago, and the running category specifically has seen real share losses. My new model reflects this - North America growth caps at 6%, not 10%, partly because brands like On and Hoka aren’t giving market share back.

But here’s the thing. In October, I wrote about the competition in one section, then ignored it in the model. The spreadsheet projected revenue growth as if Nike was still the only game in town. The gut said one thing, the model said another, and I went with the model.

If your analysis identifies a real competitive threat and your model doesn’t reflect it, one of them is lying.

The dangerous model

The most uncomfortable part of this story isn’t that the model was wrong. It’s that it felt conservative.

Revenue growth was muted in years one and two. The discount rate was above 9%. Terminal growth was a cautious 2.5%. It looked careful. It looked skeptical. If you squinted at it, it looked like the work of someone who’d done their homework.

But “conservative on the things you can see” doesn’t help if you’re wrong on the things you don’t model. Zero change in working capital, instant margin recovery, declining CapEx, no segment decomposition - these aren’t aggressive assumptions. They’re missing assumptions. The model didn’t decide to be optimistic about working capital. It just forgot to include it.

The difference between a $82 fair value and a $38 fair value is not a difference of opinion. It’s a difference of rigor.

I’ve since rebuilt every model in my portfolio using the FCFF framework. Every position gets segment revenue, explicit margin paths, modeled NWC, and CapEx tied to growth. Two of the five came back looking different. Nike was the worst - you’ve seen the numbers. Lululemon (LULU) went from $283 fair value to $192 - a 32% haircut - once I modeled the CEO transition margin sag, tariff-adjusted working capital, and regional revenue build-up instead of a single growth rate. Same pattern. Same category of mistakes.

The process upgrade was worth more than any single stock pick.

So what now

This is the part I’ve been putting off.

I own 173 shares of Nike at $56.13. The stock is at $44. My updated model says it’s worth $38. I didn’t just buy at a premium to the market - I bought at a premium to my own revised fair value. That’s a $9,700 position in a stock I now think is overvalued.

The textbook answer is simple. Sell. The model says the stock is 14% above fair value. Take the $2,000 loss, redeploy the capital into something with actual upside, and move on. Sunk cost fallacy is the enemy. Be rational.

But it’s not that clean.

Nike is still Nike. The brand isn’t broken - the execution was. North America is growing again. Wholesale is +11%. Running is up 20% for three straight quarters. The product pipeline is the strongest in years. Hill knows the business - 32 years in, he’s not guessing. The turnaround is real, it’s just slower and more expensive than the market hoped.

My model gives Nike a 12.5% EBIT ceiling because of tariffs. But tariffs are political, not structural. If they ease - and my original thesis was that they would - the margin ceiling lifts and the fair value moves up. At 13.5% terminal EBIT instead of 12.5%, fair value jumps to mid-$40s. At 14%, it’s north of $50. The model is sensitive to this assumption because it affects every year of the projection.

So the real question isn’t “is Nike overvalued today.” It’s “what’s the probability that one or more of my conservative assumptions turns out to be too conservative.”

Here’s what I’m doing. I’m holding. But with conditions.

The turnaround has specific milestones I can track. NA revenue must stay positive. Gross margins must stay above 38%. EBIT margin inflection should show up by Q2 FY2027 - that’s management’s own timeline. China needs to at least stabilize. If these hold, I keep the position and let the thesis play out. If any of them break - especially NA turning negative again or margins deteriorating further - I sell. No averaging down. No adding. This is a position I need to earn my way out of through patience and monitoring, not through throwing more capital at it.

The honest version: I’m not confident enough to add, and I’m not panicked enough to sell. The model says one thing, the qualitative picture says something slightly different, and I’m going to let the next two quarters of earnings settle the argument.

Q1 FY2027 reports in late June. That’s the next checkpoint.

Chuyka check

Here’s what the numbers don’t capture.

I liked Nike. I wear Nike. I quoted Peter Lynch in the original post - “liking a store or a product is a good reason to get interested in a company.” And it is. But somewhere between getting interested and hitting buy, the analysis has to take over from the affection.

I did the work. I built a model. I found a margin of safety. But the work had holes in it, and the margin of safety was an illusion built on missing assumptions. The price looked right because the model was shaped to make it look right - not intentionally, but through omission.

My chuyka on this one was wrong. Not because the gut read was bad - Nike is still a great brand with real competitive advantages. But because I let the gut substitute for math in places where the math mattered.

The next time I feel strongly about a company, I’ll still listen to the feeling. That’s the whole point - data gets you 90% there, chuyka gets you the rest. But I’ll also double-check that the model doesn’t have any convenient blind spots where the feeling is doing the work the spreadsheet should be doing.

Trust your chuyka. Don’t let FOMO eat you alive.

Not investment advice. Think for yourself. Don’t trust online experts.

Before we continue, I would love if you subscribed using button below. I am looking for a thoughtful conversation and push-back on my positions. I am 9% down YTD and clearly something is not working. Your feedback is very important. Never thought that transition from passive to active investing would be such a rollercoaster.

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Now let’s get into one of the more recent additions. I’ve bought 270 shares of GTX for $18.49 - it is now trading at around $17 amid the market sell-off. An opportunity to increase the position? Let’s test the thesis.

The bigger turbo

When I was younger I was into time attack. You take your car to a track and try to set the fastest lap in your class. I had a Mitsubishi Evolution X. Great car.

Since I couldn’t really drive, the main way to go faster was modifications. Intake, exhaust, ECU tune, cooling, tires, rip out half the interior. The basic minimum. The luxury maximum was always an engine rebuild - forged pistons, MOTEC brain, and a Garrett turbo kit.

I never got to the luxury maximum. Around the same time I got into investing. First I realized the best investment was in myself as a driver. Then I realized the best investment wasn’t in myself or the car - it was in the stock market. Sold everything. Here we are.

The dream of a bigger Garrett turbo and a louder exhaust had to go. But now I can afford to buy a piece of their company, trading under the ticker GTX.

What Garrett Motion does

Garrett Motion designs and manufactures turbochargers for passenger and commercial vehicles - gasoline and diesel. The company sells directly to OEMs: Volkswagen, BMW, Mercedes, Stellantis, plus Chinese automakers. A small share comes from aftermarket parts and automotive software.

Garrett is a former Honeywell division, spun off in 2018. In 2020 the company went through Chapter 11 bankruptcy - not from operational problems, but from asbestos liabilities inherited from Honeywell. Emerged in 2021 with a clean balance sheet, no legacy baggage.

Headquarters in Switzerland. 6,600 employees. Trades on NASDAQ. CEO Olivier Rabiller has been running the company since the spin-off.

Three major players in the turbocharger market: Garrett, BorgWarner, and what’s left of Honeywell’s turbo business. Effectively an oligopoly.

Why the stock is cheap

GTX traded at the time of original thesis at $18.23 against my DCF fair value of $41.00. P/FCF around 10x. EV/EBITDA at 8.6x. FCF yield of 9%. For a company that consistently generates $325-430 million in free cash flow, that’s not a lot.

The market is saying something like this: “Garrett is an ICE business. Electrification will kill it. Everything it earns today will slowly disappear.” That’s where the discount comes from.

52-week range: $7.01-$21.43. The stock is closer to the upper end, but still sits at the 50% margin of safety level from my valuation.

What management says

On the Q4 2025 earnings call, management explained the current situation:

• Europe is weak. Light vehicle production hasn’t recovered to pre-pandemic levels (still -21%). Diesel keeps losing share in cities.

• Commodity pass-through. Lower raw material prices mechanically reduce revenue by about 2% - margins aren’t affected.

• Currency problems. EUR/USD and JPY swings cost about $34 million for the year.

• China is the growth story. Win rate on new platforms above 50%. The bet is on PHEV/REEV - range-extender EVs where the combustion engine runs in a narrow RPM band and needs a high-performance turbo.

Fundamentals

Revenue and margins

Revenue peaked around $3.9 billion in 2023 and has been gently declining. But EBIT margin holds steady at 13-14% - that’s 3x the sector average of 4.7% per Lazard’s 2025 Global Automotive Supplier Study. Gross margin stays in the 24-27% corridor across several cycles. Not a coincidence - structural pricing resilience.

FCF swings year to year because of working capital, but averages $300-440 million annually. For a company with a $3.5 billion market cap, that’s substantial.

Capital returns

This is where it gets interesting. Since emerging from bankruptcy, Garrett has been returning cash aggressively:

• FY2023: $818 million in buybacks. More than FCF that year. Roughly 20%+ of the entire market cap repurchased in one year.

• FY2024: $304 million

• FY2025: ~$211 million + a new $250 million program announced for 2026

• Dividend: $0.28/share (1.5% yield)

Management targets converting 60% of EBITDA into capital returns. At TTM EBITDA of ~$595 million, that’s ~$357 million a year in buybacks and dividends. Promises match actions - that’s rare.

The flip side: aggressive buybacks pushed book equity into negative territory (~-$4/share). That’s not insolvency - cash generation is real - but P/B and ROE are now economically meaningless. Look at FCF yield and EV/EBITDA instead.

Balance sheet

• Net debt: ~$1.4B

• Net debt / EBITDA: 2.2x

• Interest coverage: 4.7x

• Current ratio: 0.97

Leverage is moderate. 2.2x on EBITDA isn’t aggressive for a business with stable FCF. But there’s not much buffer if volumes drop hard. A 25% fall in EBITDA pushes leverage to 3x - that gets uncomfortable.

Piotroski F-Score: 7/9

Strong. Fails on two signals: leverage ticked up slightly, current ratio sits just below 1.0. All profitability and operating efficiency signals are green.

Competitive moat

Narrow moat - engineering lock-in to the platform.

Turbocharger development is tied to a specific engine program. Certification takes 3-5 years. Once a supplier wins a platform, they stay on it for 8-12 years - the full lifecycle of that engine. OEMs don’t swap turbo suppliers mid-program.

But the moat doesn’t widen over time - it resets with each new engine generation. If ICE programs shrink, Garrett’s captive revenue pipeline shrinks with them.

One detail the market isn’t pricing in: Garrett is a consolidation beneficiary in a distressed sector. 20.6% of the auto supplier industry is already in financial distress per Lazard 2025. When weak turbo suppliers go bankrupt, their OEM content has to go somewhere. In an oligopolistic market (Garrett + BorgWarner), there aren’t many places for it to land. Garrett at 14% EBIT margin can absorb the pricing pressure that kills a competitor running at 5%.

Two catalysts that weaken the bear case

1. EU softened the ICE ban

In December 2025, the EU revised its 2035 target for banning combustion engines. Was: 100% emissions reduction (effectively a ban). Now: 90% reduction, with the remaining 10% offsettable through e-fuels, biofuels, and carbon credits.

The practical effect: OEMs that had frozen new ICE/hybrid program investments can now invest again. Every new engine program is a potential Garrett platform win for 8-12 years. The push for this change came from Germany, Italy, Hungary, and Poland - countries whose OEMs (VW, BMW, Mercedes, Stellantis) are Garrett’s core European customers.

2. China REEV is growing despite PHEV slowdown

Pure PHEVs in China have slowed (Q4 2025: -12% YoY). But REEV - range-extender EVs - is a different story: 640 thousand units in 2023 (+181% YoY), ~1.2 million in 2024 (+83%), forecast 3.2 million by 2030 (CAGR 17.1%).

Why this matters for Garrett: REEV generators run at a fixed optimal operating point - Miller/Atkinson cycle, narrow RPM band, maximum thermal efficiency (Chinese OEM engines hitting 46%). This demands more precise turbocharger engineering than a standard combustion engine. Commodity competitors lose here - plays directly into Garrett’s hands.

Li Auto tried to pivot to pure BEV - failed - and came back to REEV, targeting 550 thousand deliveries in 2026. Leapmotor is targeting 1 million units. Geely, BYD, Xiaomi, XPeng - all entering REEV. The trend is confirmed across multiple OEMs.

Peer comparison

Garrett stands out on margins - nearly double the nearest competitor. EV/EBITDA is higher, but that’s the premium for business quality. FCF yield is in line with the sector, but the quality of that cash flow is significantly better.

DCF valuation

Key inputs:

• Revenue: $3,584M base, growing at +3% per year (linear)

• EBIT margin: 14.0% (flat, at TTM level)

• Tax rate: 21%

• WACC: 6.45% (beta = 0.70, adjusted up from reported 0.376)

• Terminal growth: 2.0%

• Projection period: 8 years

At the current price, GTX trades below the 50% margin of safety level. The market is pricing in either a significantly worse revenue trajectory, or structurally lower margins, or a much higher discount rate. All three are possible - but all three at once?

Terminal value as % of EV: 72.2%. Near the 75% threshold but acceptable. Most of the value sits in the long-term franchise - turbo leadership plus potential EV products - not in near-term cash flows.

Risks

1. EV transition accelerates. The EU softened the target, but the drift toward electrification continues. If OEMs front-load their EV mix for CO2 compliance, revenue could decline 4-7% per year.

2. China REEV stalls. If the Chinese government pivots back to favouring pure BEVs, or if Li Auto and BYD start making turbochargers in-house, the thesis weakens.

3. Tariffs. Management flagged tariff risk on the Q4 2025 call. Cross-border manufacturing creates real exposure if trade wars escalate.

4. Leverage. At 2.2x net debt/EBITDA it’s manageable. A 25% drop in EBITDA and you’re at 3x - the safety cushion disappears.

5. Buybacks vs. debt. In FY2023 the company spent more on buybacks than it generated in FCF. The pace has slowed, but negative book equity is a fact. Financial flexibility is limited.

How to think about this

Garrett is not a “combustion engines forever” story. It’s a time-boxed bet on the 2025-2030 window. Over the next five years, ICE and hybrids hold roughly 60% of new vehicle sales per IEA, BloombergNEF, and S&P Global. In that window, Garrett collects cash, buys back shares, and builds new product lines - e-boosting, fuel cells, e-cooling for data centres.

The question isn’t “will ICE survive?” It will, at least until 2030. The question is: “will Garrett earn the right to compete after 2030?”

At 9% FCF yield and buybacks shrinking the share count every year, the hurdle rate for acceptable returns is very low. Even with stagnant revenue, the math works. If China REEV accelerates and the consolidation thesis plays out, the upside is significant.

I bought 270 shares of GTX at $18.49 in my active portfolio.

Chuyka Check

After all the numbers and all the models - here’s what sits with me. Garrett is the kind of stock that makes you feel slightly uncomfortable owning. The market narrative is clean and easy to understand: EVs will kill this business. And maybe they will. Eventually.

But “eventually” is doing a lot of heavy lifting in that sentence. The turbocharger industry isn’t shrinking tomorrow. It’s an oligopoly with real engineering barriers, and the China REEV angle is something most investors haven’t even looked at. The company throws off cash like it’s going out of style, and management is buying back stock at prices that my model says are half of fair value.

My chuyka says this is one of those situations where the market has priced in a death that’s 10 years away and forgotten about the 5 years of cash collection in between. I could be wrong. The EV timeline could compress. But at this price, I’m getting paid to wait and find out.

If you want to follow me and see if I am wrong or right in my assumptions - here is a field with a button for you :)

Trust your chuyka. Don’t let FOMO eat you alive.

Not an investment advice. Think for yourself. Don’t trust online experts.

I’m a different beast. Down 9% YTD, holding six losing positions and a pile of cash, watching the market grind lower while oil trades above $100 and the Fed sits on its hands.

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But here’s where I came from, where I am, and where this is going.

The passive decade

I started investing in 2014. My first trade was buying one share of Tesla and selling it eight minutes later. I didn’t know what I was doing, but I knew I wanted to learn.

For the first couple of years I studied value investing. Intrinsic value, margin of safety, the whole Buffett and Graham reading list. I ran a blog about it in Russian. I had opinions about stocks I barely understood. Then life happened - career got demanding, I was working 12-hour shifts on oil rigs in Iraq, and I quietly switched to passive indexing. Meb Faber’s global asset allocation. Five ETFs: IVV, IEFA, VCLT, VGLT, PCY. Set it and rebalance once a year.

I ran that portfolio for a decade. It compounded at over 7% annually - decent, not spectacular. Most of that came from the S&P 500 carrying the rest. The international diversification, the bond allocation, the carefully balanced global exposure - all of it underperformed a simple 60/40 btw for most of the years, except when it beat S&P500 in 2025. I’ve achieved my goals of financial security and now it keeps running.

The biggest lesson from ten years of passive investing wasn’t about asset allocation. It was this: sitting still is the hardest thing in investing. Not selling during drawdowns. Not chasing what’s working. Not tinkering with something that’s fine. That discipline became the foundation for everything that came after.

The itch that wouldn’t go away

Somewhere around year seven or eight, the value investing itch came back. I’d been building data science skills through Yandex’s program, applying AI to problems in oil and gas at work, and I kept thinking: the tools have changed. What used to require a Bloomberg terminal and a team of analysts - pulling financial statements, building DCF models, screening for quality factors, reading earnings calls - a single person with the right setup can now do all of that.

Not better than a professional analyst. But good enough to make an informed bet. And that’s all value investing is - an informed bet with a margin of safety.

So in early 2025 I carved out $55,000 more from oil and gas money, opened a separate brokerage account, and started building positions. One stock at a time. Full transparency - every entry price, every share count, every P&L published in real time. (Now there is a Russian version of live tracking on my blog, but I will add an English one soon.) The passive portfolio stays. This is the experiment running alongside it.

The rules of the experiment

The philosophy is simple. Simple doesn’t mean easy.

Buy businesses, not tickers. I want to understand what a company does, how it makes money, and why it will keep making money five years from now. If I can’t explain it clearly, I don’t own it.

Value is the only reason to buy. I build a DCF model for every position. Full FCFF projection, explicit assumptions, terminal value with a sanity check on the implied multiple. The model gives me a fair value. I only buy below it - ideally at a 30-50% discount. No exceptions for “great company, fair price.” If the math doesn’t work, I wait.

Cash is not a failure. Half my portfolio is in SGOV right now. That’s not indecision - valuations are rich, and I’d rather hold dollars than overpay for a narrative. The ability to act during a selloff is an asset. Most investors are fully deployed when the best opportunities show up. I’d rather miss a rally than catch a falling knife without dry powder.

Show the work. Every stock gets a published deep dive with the full model. Not just “my fair value is $X” but every assumption behind it - revenue growth, margins, capex, WACC, terminal growth rate. You can disagree with any input and rebuild the model yourself. That’s the point.

Document mistakes. When I’m wrong - and I will be wrong - the losing trades stay on the record with the original thesis next to them. No deleting posts, no quiet exits. The process matters more than any single outcome.

Where things stand right now

Let me show you what honesty looks like. Here’s the portfolio as of March 20, 2026:

Total portfolio value: $52,917. Down from $55,000 starting capital. YTD return: -8.95%.

Every single equity position is red. SGOV - the cash proxy - is the only thing in the green, and barely. The unrealized loss across the equity book is -$3,661.

This is what value investing looks like in practice. You buy stocks the market hates. Then the market keeps hating them. You sit there, check the thesis, and either add more or wait. The thesis on each of these names hasn’t changed. The prices have. That’s the difference between price and value, and being comfortable with that gap is the entire game.

Quick thesis summary on each:

• NKE - Nike at $52, trading near a 52-week low. The market is pricing in a rough transition under new CEO Elliott Hill. I think the brand is too strong to stay here. March 31 earnings will be the next data point.

• GTX - Garrett Motion, a turbocharger manufacturer spun off from Honeywell. Fair value per my DCF is $41. At $17 the market is pricing in permanent ICE decline. I disagree.

• LULU - Lululemon post-earnings. The product quality is real - I own their stuff and it lasts years. At $163 it’s priced like a broken growth story. I think margins recover.

• NOMD - Nomad Foods, European frozen food. Boring business, beaten down by a shelf filing overhang. Trading at 7x earnings for a company with stable cash flows.

• ONON - On Holding. Best-in-class growth in athletic footwear. At $38 after a guidance miss, it’s the most expensive name I own and the one I have least conviction on. Minimum position size.

Started building that set of outcasts last year. It went well, until it didn’t.

Not one of these is a crowd favourite right now. That’s by design.

The plan from here

This is what Chuyka will be:

Stock deep dives - full analysis with DCF model assumptions. When I buy something, you’ll know exactly why, with every assumption laid out for you to challenge.

Portfolio updates - real numbers, real P&L, no hiding. When positions go against me, you’ll see it happen in real time. When I add or sell, you’ll know the reasoning right as I execute.

Process posts - how I source ideas (tracking superinvestor 13F filings, sifting through 52 week lows, mostly), how I read earnings calls, how I build models. The unsexy infrastructure of doing this alone.

I publish when I have something worth your time. Not on a schedule.

I’ve been writing about investing in Russian for over a decade. But I’ve been missing something important - the conversation. Thoughtful pushback. Someone saying “your WACC is too low” or “you’re ignoring the competitive threat from X.” That kind of discussion is how investing logic sharpens. Writing in English opens that door.

If you’re a value investor, an aspiring one, or just someone who wants to see what this process actually looks like with real money on the line - stick around.

If you’re here for hot takes and trade signals, this isn’t the place. I bought Nomad Foods. I hold 50% cash. Nothing about what I do is exciting. But I think it’s right.

Trust your chuyka. Don’t let FOMO eat you alive.

Not an investment advice. Think for yourself. Don’t trust online experts.