I feel like the stock market is overvalued right now, and the risk/reward isn't there for me personally. Most companies are experimenting with and overspending on AI without any clear ROI yet. The same logic applies to chip and memory stocks, prices are up only because of huge demand driven by data center buildouts and hyperscalers competing with each other, but the moment any one of them slows down capex, those order books get canceled fast, and the premiums they're charging will vanish.

I feel like Meta's plan to sell/release compute is a sign that capex is going to slow soon, and that AI demand or revenue isn't going to match what companies expected or spent toward. I also feel that AI token demand is bit inflated by services automatically summarizing stuff, rather than actual usage (Word summarizing document without any prompt or meeting summaries). Another thesis that I have is that there is some accounting math/lag going in earnings calculation, where the NVDA or memory companies are counting their revenues and profits immediately but hyperscalers are not expensing it (so their true impacts of spending is not yet visible in net earnings, same thing played out in dot-com time). For now I'm parking my money in CDs and booking some profits. How is everyone else preserving capital or hedging right now?

On a separate note, I feel like most of us have never actually been through a real stock market crash. The COVID downturn barely lasted a year or two, same with the tariff sell-off, which lasted a month or less. The last real crash was 2000/2007-08, and it took 13 years to fully recover for dot com and 7 years for housing bubble and the current scale is so much higher. For those who lived through an actual crash, what are you doing differently?

I still feel a little sick about this one.

Intel was my highest-conviction pick. The only American company that still makes its own chips, the last one standing anywhere near TSMC. I actually believed in it.

Then earnings hit, worst day in the company’s history, and I watched it bleed from $31 toward $20 while every headline called it dead. I couldn’t take it. I sold near $21 and told myself I was being smart, cutting my losses.

Then it turned. Past $50, into the triple digits, doing exactly what I’d bought it for. I sat there and watched until I couldn’t stand it, and bought the same shares back near $100.

Sold low because I was scared. Bought back high because I couldn’t stand missing it. That round trip cost me about $7,600. I was never wrong about the company. I was wrong about me.

And the worst part is it shows up nowhere. No red number, no line item. It just quietly becomes the price of getting back in, and you never learn.

Tell me I’m not the only one. Do you actually manage to sit still through a scary quarter? And has anyone found something that genuinely stops them, something stronger than just telling yourself to be disciplined?

Act as an expert equity research analyst and value investor deeply trained in the school of Benjamin Graham, Warren Buffett, and Charlie Munger.

I want to analyze \[Meta Technologies META\] to determine if it is currently cheap, expensive, or fairly valued, and whether it offers a sufficient margin of safety at its current price of \[578.49\].

Please run a comprehensive valuation triangulation using the following three distinct lenses based on the "Swedish Investor Masterclass framework":

\### Phase 1: Relative Valuation & Multiples

1. Identify the current Trailing P/E and Forward P/E for this company.
2. Compare these multiples against the company's own 5-year and 10-year historical medians. Are they trading at a premium or discount to their history?
3. Compare these multiples against 3-4 of its direct industry peers. Is there an industry-wide overvaluation trap, or does this company emerge as a genuine value alternative? Is it cheap for a good reason (deteriorating fundamentals), or is it mispriced?

\### Phase 2: Absolute Valuation (Discounted Cash Flow - DCF)
Using the concept that intrinsic value is the sum of all future cash flows discounted to today's value, please calculate a conservative 10-year DCF:

1. \*\*The Cash (FCF):\*\* Identify the current Free Cash Flow (Cash from Operations minus Capital Expenditures).
2. \*\*The Timeline & Growth:\*\* Project FCF out for 10 years. Use a highly conservative growth rate grounded in the company's historical trends and broader industry caps (avoid unrealistic double-digit assumptions unless highly justified).
3. \*\*The Terminal Value:\*\* Calculate the value from year 11 to infinity using a 10-year historical median Exit Multiple (Price/FCF).
4. \*\*The Certainty (Discount Rate):\*\* Discount these future cash flows back to the present. Use a discount rate calculated as: Current 10-Year Government Bond Yield + a 3% Equity Risk Premium (or adjust higher if the business is unpredictable).
5. State the resulting calculated intrinsic value per share.

\### Phase 3: Business Certainty & The "Moat"
Address Buffett’s third question: "How certain are you?"

1. Look at the historical track record of the financials (Revenue, Operating Margin, FCF). Is it highly stable and predictable, or erratic?
2. Is this business highly susceptible to rapid technological or structural change, or is it a stable "absence of change" business where its competitive advantage (moat) will look identical in 10-15 years?

\### Conclusion: Triangulation & Margin of Safety
Synthesize the findings from all three lenses.
\- What is the estimated intrinsic value range?
\- Based on the current stock price of \[INSERT CURRENT STOCK PRICE\], what is the exact percentage of the Margin of Safety?
\- Give me a final "Spear Fisher" verdict: Is this a screaming buy that jumps off the paper, a fair price for a wonderful company, or a value trap to be skipped?

Hi all,

I’ve been riding some massive gains in short time in NVIDIA and GE (both up over 50% for me), and I’m now at the point where I need to rebalance and take some profits off the table. My plan is to trim these positions and redeploy that capital into other high-conviction names, ideally staying within the tech sector since that’s where I have the most conviction and understanding.

The core question I’m wrestling with is where to put that money to work for the next five years with the goal of outperforming the broader market. I’m not looking to just match the S&P 500 — I’m willing to take on more volatility and risk in exchange for outsized returns, as long as the thesis is solid.

Right now, the names I’m considering are: Microsoft, Google (Alphabet), Nebius, Palantir, Micron, and Marvell.

I’d love to get the community’s deeper take on each of these, especially through a 5-year lens. A few specific thoughts and questions on each:

· Microsoft — The Azure and AI narrative is obviously powerful, and Copilot integration across the enterprise stack seems like a genuine multi-year growth driver. But at this market cap, can it realistically double or more in five years, or is it becoming a safer but lower-upside compounder at this stage? Are we reaching a point where the law of large numbers kicks in meaningfully?

· Google (Alphabet) — The valuation is more reasonable than many peers, and they have arguably the deepest AI research bench in the world. But I worry about the existential risk to search from AI answer engines, regulatory overhang, and whether they can actually monetize AI without cannibalizing their core business. Do you see YouTube and Cloud carrying enough weight to offset any search headwinds over a half-decade horizon?

· Nebius — This is the one I know the least about and would especially appreciate insight on. It seems to be positioning itself as a leading AI cloud infrastructure provider, heavily linked to the former Yandex team. The growth story sounds compelling, but liquidity, corporate structure, and geopolitical ties concern me. Is this a legitimate high-growth AI infrastructure play or more of a speculative bet that could just as easily go to zero?

· Palantir — The commercial acceleration story is finally playing out, and AIP seems like a real product that enterprises actually want. But the valuation has run up so much that I’m struggling to figure out how much future growth is already priced in. Is there a realistic path to $100B+ in annual revenue in 5 years, or are we in hype territory where even great execution won’t justify the current multiple?

· Micron — Memory is brutally cyclical, but the long-term thesis around HBM (high-bandwidth memory) and AI-driven demand seems structurally different this time. Is Micron the best non-GPU way to play the AI buildout over five years, or will the cycle inevitably turn and wipe out a big chunk of these gains? How do you handicap the cycle timing risk versus the secular demand story?

· Marvell — Their pivot to custom AI silicon and data infrastructure is super interesting, and their design wins in optical connectivity and ARM-based computing give them a different angle than NVIDIA. But this is complex silicon IP — execution risk is real, and they’re competing with Broadcom and others. Can Marvell carve out a big enough niche to deliver market-beating returns over a full five-year cycle?

Beyond these specific names, I’m also wondering if I’m thinking too narrowly by focusing on these larger, already well-known names. Should I be spending more time looking at smaller-cap companies where the growth runway and potential multiples expansion could be much more explosive? Smaller names can obviously deliver life-changing returns in a way that a $3 trillion company simply can’t, but the failure rate is also exponentially higher.

As a reference point, I do hold Amprius (AMPX) as a long-term speculative bet because I believe their silicon anode battery technology could be transformative if they can scale manufacturing. I’m comfortable with that kind of risk/reward profile for a portion of my portfolio. Would love suggestions on other smaller names that people feel have similarly disruptive potential over a 5-year time horizon — whether in AI infrastructure, energy storage, space, biotech, or any other tech-adjacent space. I’m particularly interested in companies that have already de-risked the technology somewhat and are now in the commercial scaling phase, rather than pure pre-revenue lottery tickets.

So my questions to the community, in summary:

1. Of the six names I listed (MSFT, GOOGL, Nebius, PLTR, MU, MRVL), which do you have the highest 5-year conviction in for beating the market, and why? Which would you avoid?
2. Is now actually a good time to deploy fresh capital into any of these, given where valuations are across the AI/tech landscape, or should I consider holding some cash and waiting for a pullback?
3. Should I tilt my portfolio toward smaller, higher-growth companies for the next five years rather than these mega and large-cap names? If so, what are your best small-cap ideas with truly disruptive potential?

Appreciate any and all thoughtful responses — especially from those who have deep knowledge of these companies or the specific sub-sectors they operate in. Thanks in advance.

TLDR: this is an early attemp to do a valuation of $HONA which was spun off on the 29th June. Due to the FOG of War, this aerospace company is priced currently at fair value, i do expect that investors will bid up the price once data is made available.

Honeywell Aerospace in $hona, financial year: Jan-Dec, This Report: Spun off. Today: 6th July

0 Recent Price: 247 Marketcap: 78bn Revenue 17.68bn

1 EPS TTM (Diluted): 4.76 (Normalised, Morningstar): 9.37, (Zacks) -, (SA): -, (Lucy Diamonds): 8.82

(Comment: due to the spin off with lots of one time items, the range of values varies greatly for the adjusted or Normalised EPS. It might be better to the End 2025 figures instead or maybe use this year's 2026 expect adjusted EPS nos).

Adjusted EPS	MStar	CFRA	SA	Zacks	Barron's	Lucy Diamonds
2025	9.40	-	-	-	-	9.82
Q1-TTM	9.37	-	-	-	-	8.82
2026 (this year)	-	9.11	8.97	7.75	9.12	-
2027	-	10.08	10.16	8.90	10.23	-
2028	-	-	11.38	-	11.44	-

2 Yield - , -

3 ROA: 8.21, ROE: 66.25, ROIC: 22.35 (FOW: quarterly Equity is negative)

4. P/E 2026 range = 27.11 to 31.87 (due to range of estimates)

5. Debt / Equity = N/A (FOW: quarterly Equity is negative), if i use 2025 Bookvalue, the D/E -= 1.86 (!)

Netdebt / Ebitda is around 3.1 ( my calculation is 4.2, CFRA + etc says it is currently at 3.1x)

6. FCF Conversion = FCF/Netincome = 73 to 90% currently

7. Past Growth:

Source: Refer to slide one:

Past Growth	2022-2025 CAGR
Sales	11%
Adjusted EBIT	9%
FCF	13%

8. Management Guidance:

2026: Organic Growth 7 - 9%

See Slide 2 for industry growth assumptions

2030: Sales Growth 6-8%, Adjit EBIT 9%,

See Slide 4,6 & 7 for industry growth assumptions

9. Forward growth assumptions by external parties

Source:	EPS Next 3 to 5 years CAGR
SA	11.2% (manually calc) to 12.30% (stated)
CFRA	10%
DCF & Zack's & MS-NR	-

10. My calculation of Fairvalue:

(Caution: there are many moving parts compared to other companies because of the spin-off, in making assumtions, we aim to be conservative but not pessismisti)

Assumption 1: by end 2026. the company will earn adjust EPS of 7.11

Assumption 2: Management has said that they except 5 year of Adjusted EBIT growth of 9% for the next 5 years from 2025 to 2030 (see slide 7). I assume that EPS will growth that 9%, this is a bit dicey, on the one hand Management said they expect to exceed this, and FCF will grow even faster, on the other hand, due to elevated debt level, currently at a 3.1x leverage, they will incur higher interest expense which will affect earnings per share independently of EBIT. Anyway analysts estimates are higher see no.9.

Assumption 3: I assume a 10 year duration of 9% growth. i will stick to 9% as discount rate. (The WACC of Honeywell Intl, the former parent company is around 7.45% to 8.9%). I will also assume a 3% perpetual growth rate. It isn't sexy to use a perpetual growth rate as 2/3 of the valuation is based on terminal value. But I am sticking to my guns on consistency, despite some strong protestation from many commenters.

Duration	10 years	5 years
Growth %	9%	9%
Adusted EPS	9.11	9.11
Multiplier	27.17x	22.17x
Fairvalue	27.17 x 9.11 = 247.49	22.17 x 9.11 = 201.94

11. Morningstar and CFRA fairvalue calculation for HONA

Morningstar: $285.

CFRA: No Fair value but has a price target of $282

12. Conclusion

my fair value is around 201 to 247. If you believe that Honeywell Aerospace's 100 year old business business won't be able to protect its moat past the next 5 years then the fair value is around $201. i will probably buy a blob below 250 and then do more due diligence until the fog of war lifts.

What i not discussed here are the Catalysts, Redflags, etc. I will probably clean up what i wrote yesterday and paste it in this thread. (my current thinking is that is is a very company, but not as great as GE Aerospace, see my next thread).

=============================

(Below is a copy and paste verbatim from my notes):

• Honeywell Aerospace looks interesting indeed, it is a very good business with a strong tailwind. It isn’t as great as GE aerospace as manifested by its 1year backlog versus GE’s 4 years backlog, here are the reasons why it is a very good but not the widest moat:
  • there is a great push towards open source avionic standards, if this happens HONA could find its secret sauce eroded.
  • unlike GE where choice of engines is usually a seperate customer negotiation process, HONA’s stuff are embedded with the OEs. This means their negotiation power will not be as good as GE’s .
  • They are more exposed to Defense than GE.
• What i like about HONA:
  • 90% embedded in all airframe, especially the auxillary power unit
  • dominant in the business jet category, the tail wind is the fractional ownership business. The products will include avionics, apu, control systems, engines etc.
• Red flags
  • Debt leverage of 2.5 may limit the amount of dividend issued. They could follow GE’s play book and give a token dividend until the debt is reduced and then increase the dividend. In the spinoff , they did mention issuing a dividend but nothingi is declared yet. Of course back then GE (the industrial conglemerate) had a net debt / ebitda of 4.x + versus Honeywell’s current leverage ratio of about 2.5x)
    • Frankly, management has said the purpose of the spinoff is to pursue growth versus margin expansion that was the priority pre-split.
• Catalysts (short term)
  • CFO and CEO alluded that they have stuff identified to fix:
    • (a) Inventory Turns from 2-2.5 to 3.5 to 4 (pre-covid)
    • Supply chain issuesinventory turn to improve
    • go for growth opportunities versus just margin expansion
• Catalysts Longer term
  • Secular growth in commercial flight 6% industry growth with concentration in Asia
  • aging planes need to be refreshed by 2040
• Guidance
  • Company guiding to 9% EBIT growth for next 5 years.
  • eps is around $9.
  • this puts a fair value estimate of roughly 27 x 9 = 243

I established a portfolio of long-term compounder stocks that represented value at the time (2023/2024) with the intention of holding them forever. However, due to the AI buildout, several of these stocks have appreciated to the point I cannot justify their valuation:

AMAT, LRCX, KLAC, ASML, MRVL, AMD

(To be clear, there are also stocks in the basket that have lost much money, like UNH...)

My general philosophy has been to trim lightly as they've moved up. They're up so much now I am wondering if I should liquidate 50-75% or more of these positions. However, I am reading in other threads things like don't trim "when the stock is a compounder, which can rise for decades". I do think these are stocks that will be much higher decades from now, but also they could crash and not rise for many years.

What is your philosophy around a situation like this?

I estimated FY36 FCF of big tech (MSFT in this case) and what it would take for Microsoft to deliver given my desired rate of return to be 12%. It is working backwards to see what market cap makes sense from FY36 FCF. Grill me on my assumptions as I'm an amateur trying my best to make sense of the data but man do I see 50-60% drawdowns for them to make value investors thirst over these companies.

• Market Cap: $2.9T
• Current FCF (FY26 e): $60B (Yield: ~2.1%)
• Current Revenue: $318B (FCF Margin: ~18.9%)
• Current FCF Multiple: 48.3x

To justify the current price and achieve a 12% target return with an exit FCF multiple of 25x:

• Implied Required FCF Growth: 19.6% CAGR for the next 10 years.
• Required Terminal FCF: $360B (a massive jump from the current $60B).

Discounting the cash flows at 12.0%, here is how the potential growth paths stack up against today's valuation:

Case	10-Yr Growth Est.	Terminal FCF	Estimated Fair Value	Implied Upside
Bull	16.0%	$265B	$2.1T	-26.5%
Base	12.0%	$186B	$1.5T	-48.3%
Bear	8.0%	$130B	$1.0T	-64.0%

• My Buy Threshold: $1.3T (Applying a 15% Margin of Safety to the 12% Base Case fair value). This implies a 56% drawdown from current levels to get a significant safety cushion.

Thoughts?

I’ve been looking at UK housebuilders as value investments, and Barratt Redrow looks particularly interesting at around 279p.

The obvious bull case is UK planning reform, political support for housebuilding and eventually lower mortgage rates. But these tailwinds could take years to translate into earnings, so I’m more interested in whether the shares are cheap enough without relying on them.

Barratt Redrow recently reported tangible net assets of £6.18bn, or 433p per share. At 281p, the shares trade at around 64% of tangible NAV.

The largest assets are land and work in progress, so I tried stress-testing their value:

• No haircut: 433p/share
• 10% haircut: 380p/share
• 20% haircut: 327p/share
• 30% haircut: 274p/share

Very simplistically, the current share price therefore appears to imply close to a 30% write-down of Barratt’s net land and WIP assets.

Obviously, this isn’t liquidation value. But the downside protection still looks interesting.

Barratt also holds around 5 years of owned land versus a medium-term target of 3.5 years and has sharply reduced new land approvals.

This creates a potential route to shareholder returns that doesn’t require a housing boom:

Reduce land purchases → build out existing sites → convert inventory into cash → return capital to shareholders.

There is also activist pressure for larger buybacks. The argument is simple: why spend £1 buying more land when the company can effectively repurchase £1 of its existing net assets for around 64p?

On top of that, you have potential Redrow synergies, eventual housing recovery, planning reform and possible corporate action.

The main bear case, as I see it, is that the discount is justified because Barratt earns inadequate returns on its large asset base. Cheap assets aren’t necessarily valuable if they remain tied up for years generating poor returns.

At around 279p, though, I think the risk/reward looks attractive.

What am I missing? Is the NAV discount real, or is there a good reason Barratt deserves to trade this far below tangible book value?

Hey everyone,

32M here and pretty new to investing.

I can invest around €400 per month and I’m looking for some ideas on stocks to research for the long term.
To give a bit of background, investing was never really an option for me before. My father passed away a few years ago, and since then I’ve been supporting my family financially. I had loans to pay off, helped take care of my mother, and supported my younger sibling through university. Because of all that, I never really had money left over to save or invest.

Now that the loans are finally paid off and things are a bit more stable, I’ve decided it’s time to start investing and building something for my future.

I’ve been doing my own research and learning as much as I can, but one thing I really like about this community is that people often mention companies I’ve never heard of before. Some of them turn out to be really interesting once I start digging into them.

So I thought I’d ask: what are some stocks you think are worth looking into for a 10 - 15+ year hold?

Not looking for get rich quick plays just companies with strong long-term potential that I can research further.

Thanks in advance for any suggestions!

What stocks are on your radar this week? What's undervalued? What's overvalued? This is the place for your quick stock pitches or to ask what everyone else is looking at.

This discussion post is lightly moderated. We suggest checking other users' posting/commenting history before following advice or stock recommendations.

New Weekly Stock Ideas Megathreads are posted every Monday at 0600 GMT.

Please challenge my thesis, I’m looking for the strongest counter arguments.
Wise is a founder led company with an expanding moat driven by economies of scale. As volumes increase, it lowers fees, attracting more users, and reinforcing the flywheel.
The current TAM is over $30T and should continue expanding as more cross border payments move online, creating a tailwind away from legacy providers like Western Union.
I’d appreciate hearing the strongest bear case.

Hi everyone, I’m looking for some feedback and critiques on my Core portfolio architecture, which is designed for aggressive long-term growth with a 10-15+ year horizon, investing from Chile.

1. The ETF Core (Global Index Base)

This is the fixed allocation for my global base:

• 70% IWDA (iShares Core MSCI World - Developed Markets)
• 20% EIMI (iShares Core MSCI Emerging Markets IMI)
• 10% SMH (VanEck Semiconductor ETF)

Why these ETFs?

• Tax Optimization: For the bulk of my base (IWDA + EIMI), I deliberately chose Ireland-domiciled (UCITS) and accumulating versions. As a Chilean investor, US-domiciled funds subject us to a heavy 30% Withholding Tax (WHT) on dividends. Irish funds cut that WHT down to 15% due to tax treaties. Since they are accumulating, the funds automatically reinvest dividends internally, accelerating compound interest without triggering quarterly tax friction or cash drag.
• The SMH Thesis: I know semiconductors are a volatile and cyclical sector, but I kept this fixed 10% tilt because my thesis goes far beyond the current AI software hype cycle. I firmly believe in the long-term growth of advanced robotics (humanoids/industrial automation) and the commercial space economy. My goal is to buy the picks and shovels of the industry—no matter who builds the robot or the satellite, everyone will eventually need the cutting-edge hardware inside SMH (NVIDIA, TSMC, ASML, etc.).

2. The Satellites (Individual Stock Picks)

Outside of the ETFs, I invest directly in high-conviction stocks, specifically targeting technological supply**-chain bottlenecks:**

• AI & Hardware Bottlenecks: I hold positions in NBIS, MRVL (Marvell), and MU (Micron), and I am actively looking for small/medium caps that control critical processes or indispensable components in the AI infrastructure chain.
• Tactical Diversification: To avoid relying solely on the pure semiconductor/AI sector, I am expanding my stock picks into commercial space exploration via Rocket Lab and exploring opportunities in Health Tech.

My questions for the community:

1. What are your general thoughts on the portfolio and the overall allocation?
2. Does anything stand out as a red flag or a blind spot (especially regarding volatility or thesis overlap between EIMI, SMH, and my individual stock picks)?

*Note: I used an AI assistant to help refine the wording and keep it concise for Reddit, but the ideas and strategy are entirely my own.

Description: Veeva Systems is a CRM & cloud computing company specializing in software for the life sciences industry. They offer a range of cloud-based applications tailored to the specific needs of these industries, including products for CRM, managing clinical trials, regulatory compliance, sales, and marketing.

Business Segments:

1. Subscription-Based Revenue:
   1. Veeva Development Cloud: This segment serves R&D teams. It involves Vault, a platform that enables content sharing with third parties while ensuring full compliance with regulations. It includes products for Vault Clinical, such as eTMF (clinical trial master file), CTMS (organize trial data), EDC (captures data), Safety Data (collects and organizes adverse event information), and RIM Submission (enables standardization of information). It also includes products for Clinical Data (electronic data capture), Vault Regulatory (supports regulatory submission workflows), and Vault Safety (pharmacovigilance).
   2. Veeva Quality Cloud: Enables life science partners to develop and manufacture products more efficiently. This includes Vault QMS (quality management systems), Quality Docs to manage regulated content, as well as lab solutions, which enable quality control to optimize batch release testing, stability study management, and environmental monitoring.
   3. Veeva Commercial Cloud: Centered around Veeva's CRM offering and supports life sciences company’s sales & marketing activities. Outside of the CRM, it involves content generation, medical products, data management, and Crossix.
   4. Veeva Data Cloud: Largely resembles IQVIA’s product suite by providing data for customer reference, real-time intelligence, and prescriber and sales data from the US market.
2. Professional Services and Support: Assistance with implementations of custom Veeva solutions as well as additional design and configuration.

PBC Identification: Veeva is the first ever public company to transition to a Public Benefit Corporation (PBC). As a PBC, Veeva must prioritize a specific social or environmental public benefit alongside generating profits. Therefore, it is legally obligated to consider the interests of stakeholders like employees and the community alongside shareholder returns. For those who prioritize companies who do things differently and value Warren Buffett’s “Institutional Imperative,” this would definitely check the box. Their public governance stance reinforces their long-term mindset.

Competitive Advantages:

• Brand Power and High Market Share: Veeva enjoys strong brand recognition and customer satisfaction within the life sciences CRM market (>80% share of life sciences CRM seats in the industry)
• Barriers to entry: Building a platform tailored to the complex needs of the life sciences industry requires industry expertise, regulatory compliance knowledge, and understanding of scientific workflows
• Switching Costs: Switching platforms in the life sciences industry can be risky due to problems that could arise in data migration, customized configurations, and user training needs.
• Intangible Assets: Veeva's deep domain expertise in the life sciences industry, strong brand recognition, established customer base, and comprehensive software suite are all valuable intangible assets

Historical Growth: Over the past decade ending in 2025, Veeva grew revenue at around 23% per year. Over the same time frame, Veeva grew free cash flow per share at over 35%, despite share dilution of nearly 1.5% per year.

Returns on Capital: Veeva has averaged ~27% ROIC over the past decade ending in 2025. The company has consistently been able to return above-average returns on capital.

Balance Sheet: The balance sheet is pristine, with zero long-term or short-term debt. They have a net cash position of over $5 Billion (depending on recent share buybacks and acquisition costs).

Cash Conversion: For subscription services, customers pay in advance (monthly, quarterly, or annually). This creates negative working capital since the company receives cash before recognizing revenue. Cash conversion (free cash flow/net income), therefore, is unusually high at 146% averaged over the past decade, although their unusually high SBC distorts their free cash flow upwards.

Pricing Power: Veeva famously did not raise prices for their software products from 2008-2021 or so. In their contracts, they implement annual price increases in line with inflation or 4%, whichever is lower. Rather than a value-extracting service provider, they aim to be a partner for their Pharma customers. This has reinforced consistency and a mutually beneficial relationship.

Risks: No company comes without risks.

• Customer Concentration Risks: In their fiscal years ended 2025, 2024, and 2023, their top 10 customers accounted for 28%, 28%, and 29% of their total revenue, respectfully.
• Operational Dependencies: Veeva has used AWS for data centers since 2017 (renewed 10 year partnership in 2025).
• Technological Disruption: VEEV operates an enterprise software platform. There is high and fierce competition amongst other technology providers for life sciences as well as CRM providers like Salesforce. Customers could, in theory, also spend capital on developing internal products tailored to their own needs.
• Customer Consolidation: Consolidation within the life sciences industry has accelerated in recent years, and this trend could continue. With fewer customers comprising a larger percentage of revenue, negotiating power against these companies dwindle.

Veeva is clearly a Quality Company that is trading down due to narrative-based reasons. On a fundamental basis, the engine keeps on chugging, and there are no signs of slowing down. Their partnership-based model and tendency to keep prices low where possible also makes it less likely that pharma clients will leave for competitors, especially given the long-term nature of existing relationships.

What do you all think about Veeva? Agree or Disagree? Other thoughts?

Portfolio from biggest to smallest:

MSFT
AMZN
CALM
BMI
GEV
TXN
BTI
ISRG
CGNX
GOOG
DG
NDSN
NFLX
IBM
NHI
CRM
POST
AME
OTGLY
EMR
PLTR
SWKS

I usually aim for undervalued high quality companies with a technical moat. I have a few odd theory’s on some. (DG being a major benefit from self driving trucks, smart factories)

Anything you wouldn’t keep in your portfolio? Aiming to beat the sp500 with less risk if a bubble pops.

Obviously we see 10 posts a day about Microsoft. Everyone talks about it being cheap. Historically Microsoft maintained a PE ratio of 25 to 32. But historically especially it did very well with its cloud business that seemed to be pushing its margins and maintaining high net profit growth rates thus justifying its high valuation.

If I were to tell you not to look in the past but assume that Microsoft will have 15-18 % net profit growth in the next 5 years. Where the data center business will be the primary profit maker but the investments too will weigh heavily on the net profits.

How would you value Microsoft then? Will you still call it cheap/ at a fair valuation/ or expensive?

TL;DR

Microsoft is not a deep-value stock in the traditional sense, but I think the market may be underestimating its long-term earnings power.

The central debate is:

> Is Microsoft’s AI CapEx cycle creating future earnings power, or permanently weakening margins and free cash flow?

The CapEx risk is real. Microsoft expects approximately $190B of capital expenditures during calendar 2026, and conventional free cash flow is currently being heavily reduced by infrastructure spending.

However, that spending is occurring alongside strong cloud and AI demand. In FY2026 Q3:

• Azure and other cloud services revenue grew 40% as reported and 39% in constant currency.
• Microsoft Cloud revenue grew 29% as reported.
• Management said Microsoft’s AI business surpassed a $37B annualized revenue run rate, up 123% year over year.

These figures show that AI infrastructure investment is already producing incremental revenue. What they do not yet prove is whether the eventual return on that capital will be attractive.

The stock does not look optically cheap on a simple earnings-yield basis. At the latest available market price of $390.49 per share as of July 3, 2026, the stock remains below my base-case DCF range. However, the reverse-DCF growth rate must be recalculated using the updated share price; the previous 6.2% result was based on a $372.75 share price and is no longer current.

That does not appear to be an especially aggressive assumption for a business with Microsoft’s competitive position, margins, enterprise distribution, and historical earnings growth.

My base-case DCF produces a fair-value range of approximately $580–$600 per share, implying roughly 49%–54% upside from the latest available price of $390.49. The result is highly sensitive to how owner earnings are defined and whether Microsoft’s AI CapEx ultimately produces attractive incremental returns.

Core Thesis

Microsoft remains one of the strongest enterprise software ecosystems in the world.

The company is deeply embedded in corporate workflows through products and platforms including:

• Microsoft 365
• Azure
• Entra and Active Directory
• Teams
• SharePoint
• OneDrive
• GitHub
• Dynamics
• Windows
• SQL Server
• Copilot and other AI services

Once an organization builds its operations around Microsoft’s ecosystem, leaving is not merely a product decision. It becomes an operational, security, compliance, integration, and business-continuity decision.

That is the moat.

Even if foundational AI models become increasingly commoditized, Microsoft still controls a major enterprise distribution and infrastructure layer.

Businesses do not simply need access to an AI model. They need:

• Identity and access management
• Security
• Compliance
• Administrative controls
• Procurement compatibility
• Integration with existing systems
• Audit trails
• Data governance
• Technical support

Microsoft already provides much of that enterprise stack.

Moat Clarification

Morningstar classifies Microsoft as a Wide Moat company.

My own internal durability screen is more conservative and currently categorizes Microsoft as having a Partial moat because the AI infrastructure cycle is creating mixed financial signals, particularly around capital intensity and free-cash-flow conversion.

I do not view those conclusions as mutually exclusive.

Morningstar’s rating is primarily a qualitative assessment of the durability of Microsoft’s competitive advantages.

My internal screen places greater weight on financial characteristics such as:

• Capital intensity
• Free-cash-flow conversion
• Incremental returns on invested capital
• Margin durability
• Reinvestment requirements

A company can retain a wide qualitative moat while temporarily screening less favorably on financial durability because its capital requirements are rising.

Why Azure Growth Matters

Azure growth is one of the most important parts of the thesis.

The AI CapEx debate is not occurring in isolation.

In FY2026 Q3, Azure and other cloud services revenue grew:

• 40% as reported
• 39% in constant currency

Management guided to 39–40% constant-currency growth for Q4.

Microsoft’s reported Azure and other cloud services category includes more than Azure alone. It also includes cloud and AI consumption services, GitHub cloud services, Nuance Healthcare cloud services, virtual desktops, and other cloud offerings.

Many AI-related workloads contribute to Azure and Microsoft’s wider cloud ecosystem, including:

• GPU training
• AI inference
• Azure OpenAI Service
• Enterprise AI applications built on Azure
• GitHub cloud services
• AI-related cloud consumption
• Infrastructure supporting Microsoft’s first-party AI products

Not all Microsoft AI revenue is reported through Azure. Products such as Microsoft 365 Copilot, GitHub Copilot, Dynamics AI offerings, LinkedIn AI products, and other first-party services may be reflected in different revenue categories.

If Microsoft were spending enormous amounts on AI infrastructure without visible demand, the investment case would be considerably weaker.

Instead, current results show that infrastructure investment is occurring alongside strong growth in Azure, Microsoft Cloud, and management’s broader AI revenue run-rate measure.

The key question is not simply:

> Is Microsoft spending too much?

The better question is:

> Is incremental AI CapEx generating enough incremental gross profit and cash flow to produce an attractive return on capital?

Current evidence suggests that the spending is producing incremental revenue.

It is still too early to conclude that the returns on the incremental capital will exceed Microsoft’s cost of capital.

Recent Operating Snapshot

Metric	FY2026 Q3 result
Revenue	$82.9B
Revenue growth	18% reported
Microsoft Cloud revenue	$54.5B
Microsoft Cloud growth	29% reported
Azure and other cloud services growth	40% reported
Azure constant-currency growth	39%
Guided Q4 Azure growth	39–40% constant currency
AI business annualized revenue run rate	More than $37B
AI annualized run-rate growth	123%
Gross margin	67.6%
Operating margin	46.3%
Net margin	38.3%
Q3 capital expenditures	$31.9B
Q3 free cash flow	$15.8B
Upcoming-quarter revenue guidance	$86.7B–$87.8B
Upcoming-quarter guided growth	13–15%

The bullish case is clear: cloud and AI demand remain strong, Azure growth is still close to 40%, and Microsoft continues to produce exceptional operating margins.

The bearish case is equally clear: cloud gross margins are under pressure, AI infrastructure is expensive, depreciation is increasing rapidly, and free-cash-flow conversion has weakened materially.

The CapEx Problem

This is the main risk.

Microsoft’s AI infrastructure build-out is enormous.

The most relevant current disclosures are:

Measure	Disclosed amount
FY2026 Q3 CapEx	$31.9B
FY2026 Q3 cash paid for property and equipment	$30.9B
First nine months of FY2026 cash property and equipment additions	$80.1B
Expected FY2026 Q4 CapEx	More than $40B
Expected calendar 2026 CapEx	Approximately $190B

Management has also said that approximately two-thirds of Q3 CapEx consisted of shorter-lived assets, primarily GPUs and CPUs.

The remaining portion was largely longer-lived infrastructure expected to support monetization over a much longer period.

The concern is straightforward:

> If CapEx permanently remains at a much higher level, does Microsoft’s free-cash-flow and margin profile permanently deteriorate?

The answer is not yet clear.

AI infrastructure requires large upfront investment. GPUs, CPUs, servers, networking equipment, land, buildings, power infrastructure, and data-center construction all have different economic and accounting lives.

The cost does not hit the income statement immediately. It is recognized over time through depreciation once assets are placed into service.

The depreciation burden is already becoming visible.

Depreciation expense	Current period	Prior-year period
FY2026 Q3	$9.0B	$5.8B
First nine months of FY2026	$24.0B	$15.7B

Quarterly depreciation therefore increased by approximately 55% year over year.

This means revenue can grow rapidly while earnings grow more slowly as the income statement absorbs the cost of the infrastructure build-out.

That does not automatically mean the business is weakening.

However, it does mean that Microsoft must generate enough incremental revenue and gross profit to compensate for:

• Depreciation
• Power and cooling costs
• Data-center operating expenses
• Replacement spending
• Lower-margin infrastructure revenue
• Potential underutilization
• Technological obsolescence

The real test is whether the incremental revenue generated by cloud and AI ultimately justifies the incremental capital investment.

Free-Cash-Flow Pressure

The current free-cash-flow figures show why the bear case cannot be dismissed.

For FY2026 Q3:

Metric	Amount
Operating cash flow	$46.7B
Cash paid for property and equipment	$30.9B
Conventional free cash flow	$15.8B
Net income	$31.8B

Conventional quarterly free cash flow was therefore approximately half of net income.

For the first nine months of FY2026:

Metric	Amount
Operating cash flow	$127.5B
Cash paid for property and equipment	$80.1B
Conventional free cash flow	$47.3B
Net income	$98.0B

That implies conventional free-cash-flow conversion of approximately 48% relative to net income.

Some of the current spending is clearly growth investment rather than maintenance CapEx.

However, investors cannot simply assume that most of the spending will disappear. AI infrastructure requires replacement cycles, and shorter-lived GPUs and CPUs may need to be refreshed much more frequently than traditional software assets.

The important unresolved issue is how much of current CapEx should ultimately be treated as:

• Temporary growth investment
• Recurring maintenance investment
• Replacement investment
• Structural infrastructure spending required to sustain revenue

Financial Quality

Microsoft’s financial profile remains exceptional despite the capital-intensity issue.

Current FY2026 Q3 profitability

Metric	FY2026 Q3
Gross margin	67.6%
Operating margin	46.3%
Net margin	38.3%
Quarterly CapEx / net income	Approximately 100%
Quarterly free cash flow / net income	Approximately 50%

Microsoft’s balance sheet is not the central concern.

At the end of FY2026 Q3, Microsoft had approximately:

• $40.3B of current and long-term interest-bearing debt
• $414.4B of shareholders’ equity

That produces a basic debt-to-equity ratio of approximately 0.10x.

Microsoft also has significant finance-lease liabilities, which should be considered in a broader adjusted leverage analysis. Even so, the central investment debate is not about solvency or access to capital.

The debate is about:

• Reinvestment intensity
• Free-cash-flow conversion
• Depreciation growth
• Asset utilization
• Replacement cycles
• Whether AI workloads have structurally lower margins than Microsoft’s traditional software businesses

Margin History

Microsoft has produced substantial margin expansion over the past decade.

Fiscal year	Gross margin	Operating margin	Net margin
2025	68.8%	45.6%	36.1%
2024	69.8%	44.6%	36.0%
2023	68.9%	41.8%	34.1%
2022	68.4%	42.1%	36.7%
2021	68.9%	41.6%	36.5%
2020	67.8%	37.0%	31.0%
2019	65.9%	34.1%	31.2%
2018	65.2%	31.8%	15.0%
2017	64.5%	30.1%	26.4%
2016	64.0%	28.6%	22.5%
2015	64.7%	19.4%	13.0%

Operating margin increased from 19.4% in FY2015 to 45.6% in FY2025.

That history is one reason I am skeptical of the claim that AI will suddenly destroy Microsoft’s economics.

However, historical margin expansion does not guarantee that AI workloads will have the same economic characteristics as Microsoft’s traditional software products.

Temporary gross-margin pressure is plausible.

A permanent collapse in company-wide operating margins is a much stronger claim and would require evidence that:

• AI infrastructure remains structurally underutilized
• Competition prevents adequate pricing
• Depreciation and replacement costs outpace revenue growth
• AI cannibalizes higher-margin software revenue
• Operating leverage fails to offset lower infrastructure margins

Valuation

Microsoft is not statistically cheap on a simple earnings-yield basis.

Measure	Value
Pretax earnings yield	5.6%
Net earnings yield	4.5%
10-year Treasury yield used in my analysis	4.5%
Pretax yield spread	1.1%
Historical 10-year earnings CAGR	20.4%

The valuation therefore depends heavily on Microsoft’s ability to continue compounding earnings and owner earnings.

My primary valuation framework is an owner-earnings DCF.

I do not place much weight on Graham-style valuation methods for Microsoft because it is not a balance-sheet-driven or asset-liquidation investment.

Base-case DCF

Assumption	Value
Latest available share price (July 3, 2026)	$390.49
Base-case DCF fair value	Approximately $580–$600
Discount rate	9%
Terminal growth rate	3%
Forecast period	10 years
Owner-earnings growth assumption	12.0%
Implied growth at current price	Requires model rerun

The exact valuation should not be taken too literally.

The result depends heavily on how owner earnings are defined, especially during a period in which reported free cash flow is being reduced by unusually large infrastructure investment.

My owner-earnings framework attempts to distinguish between:

• Maintenance CapEx
• Growth CapEx
• Depreciation
• Working-capital movements
• Recurring operating cash generation
• Temporary infrastructure investment

That distinction is inherently subjective.

The purpose of the DCF is not to claim that Microsoft is worth exactly $590 per share. It is to test whether the current valuation appears reasonable under a range of long-term growth and margin assumptions.

Reverse DCF

I find the reverse DCF more useful than the base-case DCF.

Instead of asking:

> What is Microsoft worth?

It asks:

> What level of future growth is required to justify the current share price?

At the latest available market price of $390.49 per share as of July 3, 2026, using a:

• 9% discount rate
• 3% terminal growth rate
• 10-year forecast period

The previous version of my model implied approximately 6.2% annual owner-earnings growth, but that result was calculated using a $372.75 share price. The reverse DCF must be rerun using $390.49, so I am not presenting the old implied-growth figure as current.

The updated implied-growth hurdle should be higher than the prior 6.2% estimate because the current share price is higher. Whether it remains comfortably below my 12.0% base-case assumption depends on the exact owner-earnings starting point and model structure.

However, this conclusion depends on the owner-earnings starting point. Investors who treat a larger portion of current AI CapEx as recurring or maintenance investment will calculate a lower starting level of sustainable owner earnings and therefore a less favorable implied valuation.

This is why the treatment of AI CapEx is central to the thesis.

Sensitivity Analysis

The valuation is highly sensitive to both growth and margins.

Revenue or earnings CAGR	42% margin	44% margin	46% margin
10%	$470	$505	$540
12%	$515	$555	$595
15%	$565	$600	$650
17%	$620	$660	$710

These outputs are estimates from my model rather than company guidance.

If Microsoft grows by only 10% and margins compress toward 42%, the valuation becomes much less compelling.

If Microsoft sustains low-to-mid-teens growth and company-wide operating margins remain near historical levels, the model produces materially higher values.

The largest sources of valuation uncertainty are:

• Sustainable revenue growth
• Long-term operating margins
• Maintenance CapEx
• Infrastructure replacement cycles
• Incremental returns on AI investment
• Terminal growth
• Discount rate

Bear Case

The bear case is legitimate.

I would become more bearish if:

• Azure growth slowed materially.
• Microsoft Cloud growth decelerated without a corresponding margin recovery.
• Microsoft 365 retention or pricing weakened.
• AI-native tools began replacing Office usage rather than enhancing it.
• Microsoft Cloud gross margin continued declining as AI usage scaled.
• Company-wide operating margin fell sharply and remained depressed.
• CapEx remained elevated without corresponding gross-profit growth.
• Data-center utilization fell below expectations.
• Depreciation growth persistently exceeded operating-income growth.
• AI infrastructure required faster replacement cycles than expected.
• Free-cash-flow growth failed to recover after the current build-out.
• Microsoft demonstrated revenue growth but weak incremental returns on invested capital.

The most important metric is not CapEx by itself.

It is the economic return generated by that CapEx.

A useful framework would be:

Incremental gross profit and cash flow
--------------------------------------
Incremental AI-related invested capital

Incremental revenue per dollar of CapEx is useful, but revenue alone is not enough.

The calculation must also account for:

• Gross margin
• Depreciation
• Operating expenses
• Utilization
• Power costs
• Replacement CapEx
• Asset lives
• Financing commitments

If Microsoft continues generating substantial revenue growth but the associated infrastructure produces weak incremental cash returns, the thesis would weaken materially.

Main Risks

1. CapEx overbuild

Microsoft may be overestimating long-term AI compute demand.

If capacity is underutilized, the company could be left with substantial depreciation, energy, maintenance, and replacement costs without sufficient corresponding revenue.

2. Margin compression

AI infrastructure is expensive.

GPU-heavy workloads, depreciation, networking costs, power consumption, cooling, data-center labor, and customer pricing pressure could result in structurally lower gross margins.

3. AI economics may be structurally worse

Traditional software economics are exceptionally attractive because the marginal cost of distributing an additional software license is relatively low.

AI inference has a real and recurring compute cost.

If AI products require permanently higher CapEx and cost of revenue, Microsoft may deserve a lower valuation multiple than it received during a more asset-light period.

4. Competition

Amazon, Google, Meta, OpenAI, Anthropic, Oracle, and other competitors are investing aggressively in cloud and AI infrastructure.

Competition could reduce pricing power, increase customer-acquisition costs, accelerate infrastructure spending, or commoditize portions of the technology stack.

5. Valuation risk

Microsoft is not statistically cheap.

Even an exceptional business can produce poor investment returns when purchased at a price that assumes too much future growth.

My DCF results are highly sensitive to the starting owner-earnings figure, long-term margins, CapEx treatment, and discount rate.

6. Regulatory risk

Microsoft is large enough to attract sustained regulatory and antitrust scrutiny across:

• Cloud infrastructure
• Artificial intelligence
• Productivity software
• Cybersecurity
• Digital distribution
• Gaming

Regulatory intervention could restrict bundling, partnerships, acquisitions, product integration, or cloud contracting practices.

Conclusion

Microsoft is not a deep-value stock.

However, I think the market may be too pessimistic about the company’s ability to monetize AI and preserve attractive company-wide economics over time.

My current view is:

• Microsoft’s enterprise moat remains intact.
• Azure growth shows that cloud and AI demand is already translating into incremental revenue.
• The current figures do not yet prove that Microsoft is earning attractive returns on its incremental AI capital.
• AI is more likely to reinforce Microsoft’s enterprise ecosystem than destroy it.
• Gross-margin pressure is real.
• Company-wide operating margins remain exceptionally strong.
• Free-cash-flow conversion is currently weak because of the infrastructure build-out.
• CapEx and infrastructure replacement requirements are the central risks.
• Long-term earnings power remains strong if Microsoft earns attractive incremental returns from its AI investments.
• My base-case fair value is approximately $580–$600 per share, but the result is highly sensitive to owner-earnings, growth, margin, CapEx, and discount-rate assumptions.

The debate comes down to one question:

> Is Microsoft’s AI CapEx cycle a temporary reinvestment period that strengthens its cloud and AI platform, or a permanent reset toward lower free-cash-flow economics?

I currently lean toward the first interpretation, but I think the bear case deserves to be taken seriously.

This is not financial advice. This is also my first time putting together this kind of public research post. I used AI to help organize my findings and improve some of the wording, but the research, conclusions, assumptions, and valuation work are my own.

Most of the historical financial data used in my analysis was gathered through wtbw.io, while the latest quarterly figures and management guidance were checked against Microsoft’s FY2026 Q3 filings and earnings materials.

I would like to produce more structured research like this, so constructive criticism is welcome.

Disclaimer: $GAMB holder here. I'm down about 70% on my position, although thankfully it's a relatively small one.

My impression is that the market is pricing this company as if bankruptcy is the most likely outcome.

The affiliate business is clearly performing terribly, but on the other hand the sports data segment seems to be growing nicely. They do have a significant debt load and other liabilities, but my understanding is that management expects to pay these down over the coming years using free cash flow. That seems realistic to me, yet the current valuation suggests the market doesn't believe they'll pull it off.

My investment thesis is fairly straightforward: if they make it through this year in decent financial shape and return to generating solid positive FCF and EBITDA, I could easily see the stock trading 3x higher from current levels. That doesn't seem like an unrealistic scenario to me, which is why I'm not interested in selling at these depressed prices.

I'm also very interested to see whether the sports data business (OddsJam and OpticOdds) can maintain its current growth trajectory. I'm looking forward to the August earnings report.

What I'm really looking for is someone who can explain, in detail, how this company could still end up in serious financial trouble. Am I suffering from confirmation bias or tunnel vision? Am I overlooking something important? Or is my thesis actually a reasonable one?

I'd especially love to hear from anyone with an accounting or corporate finance background who can run through the numbers and explain it in plain English. Feel free to challenge my thesis. I genuinely want to understand the bear case.