@TheRealBirnbaum@elesbaan@amitisinvesting Completely agree.
52-week low hits a P/E of 23x, 73% below its 10-year average. $12.5B FCF guided for 2026. 3.9% FCF yield. $31.8B buyback authorization. DCF fair value: $95 to $105. The business is fine. The stock is not. July 16 earnings will tell
HYPERMARKET WATCHLIST FOR June 8, 2026
$SPY crash continuation or massive reversal
1. $TSLA — $391 Robotaxi + FSD rerating hasn't happened yet; patient money wins Jan 2027
2. $MU — $864 ATH was $1,089 just on June 3; HBM4 demand cycle just starting, buy dips
3. $DRAM — $55 Pure-play memory ETF, MU + SNDK + Samsung in one; AI memory bottleneck secular story intact
4. $AVGO — $386 Record revenue, 143% YoY AI chip growth, $100B+ FY27 guide reiterated sold off purely on no upside surprise; this is the buy
5. $DELL — $394 AI server revenue up 757% YoY; pulled from $469 ATH on macro fear, not fundamentals
6. $HPE — $49 Just posted strongest AI server quarter ever, 40% revenue growth YoY; tape is disrespecting the print
7. $NVDA — $205 52-week low $140, high $236; Jensen in South Korea closing deals while market panics
8. $IREN — $54 $NVDA owns call options at $70/share; $NVDA partnership is structural floor
9. $INFQ — $17 Quantum computing pure play, early stage; sub-$15 is an accumulation zone Jan 2028 LEAPS
10. $NOW — $112 $30B revenue target by 2030, analyst avg PT $180; beaten down SaaS with real AI monetization
11. $IBM — $305 ATH just hit June 1 at $320; quantum + hybrid cloud re-rating still early
12. $MRVL — $316 Jensen Huang saying MRVL could be a trillion-dollar company; custom ASIC moat is massively underpriced
13. $PLTR — $143 52-week range $122–$207; defense AI spend is multi-decade; dips to $130 are gifts
14. $META — $593 52-week high $796; cheapest Mag7 on forward P/E, more selling probably
15. $MSFT — $417 ATH was $539; Copilot + Azure AI monetization narrative still strongest in enterprise
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It's September 2026, stocks I bought under $20 and they exploded 1000%
1. $KEEL – Former Bitfarms. 2.2 GW pipeline. Hyperscaler leases incoming. Cheapest GW-scale AI land play (Leopold call)
2. $SATL – Satellite imagery feeds AI training + defense targeting. Fresh DoD contract proves the demand is real. $SPCX SPACEX play
3. $LAES – Every AI agent needs quantum-proof identity. SEALSQ embeds PQC in silicon. The security layer AI can't run without.
4. $POET – Optical Interposer replaces copper in AI clusters. Light moves data faster at half the energy. 800G design wins at record pace.
5. $ONDS – Wireless OS for AI-driven industrial drones. Defense + logistics demand exploding. First-mover advantage. (Trump call)
6. $CIFR – Massive power assets pivoting to HPC. Market repricing it as AI infrastructure owner, not just a crypto miner. Same as $IREN $CRWV $NBIS
7. $BTDR – AI cloud ARR up 60% MoM. 92% GPU utilization. 3 GW global capacity. Own-chip design cuts cost to near zero.
8. $CLSK – Situational Awareness fund loaded 12M+ shares. Massive power footprint waiting to flip into AI colocation. (Leopold bought)
9. $HIVE.TO – Canada's largest AI gigafactory incoming. 100K GPU build-out on 100% renewable power. $225M ARR target.
10. $NOK – Restructuring entirely around AI data center networking. $4B US bet. Optical division feeding hyperscalers directly.
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$NOW can easily triple from $125 by Jan 2027.
Remember, token use is expected to 2800% in 5 years says $GS.
So these 24 stocks can still 10x-20x:
(COMPUTE / GPU)
1. $NVDA — Every token touches a GPU. 24x tokens = 24x chip demand, full stop.
2. $AMD — MI300X gaining enterprise traction. Second GPU source as hyperscalers diversify suppliers.
3. $INTC — Gaudi AI accelerators + x86 CPUs running inference at the edge and enterprise.
(NETWORKING)
4. $ANET — AI clusters need ultra-low latency switching. 24x tokens = 24x network traffic routed.
5.$AVGO — Custom AI ASICs for hyperscalers. Token volume drives ASIC and switching orders higher.
6. $CSCO — Data center fabric and ethernet switching. Every agent call crosses Cisco infrastructure.
7. $CIEN — Optical networking backbone connecting AI data centers. Bandwidth demand scales with tokens.
(MEMORY / STORAGE)
8. $MU — HBM3E stacked on NVDA GPUs. More inference = direct memory bandwidth demand explosion.
9. $WDC — Flash storage holds model weights and KV caches. Agent scale drives NAND demand structurally.
10. $STX — Hard drives store cold AI training data. Data center storage TAM expands with every model.
(POWER / COOLING)
11. $VRT — More tokens = more heat. Liquid cooling demand explodes alongside data center power density.
12. $ETN — Electrical infrastructure for AI data centers. Power management is the #1 buildout bottleneck.
13. $GEV — Gas turbines and grid solutions powering new data center campuses requiring gigawatt-scale energy.
14. $VST — Power generator selling directly to hyperscalers. AI energy contracts already locked in long-term.
(CLOUD PLATFORM)
15. $MSFT — Azure hosts majority of enterprise agents. Token spend flows straight through its cloud margin.
16. $AMZN — AWS Bedrock is the enterprise agent backbone. More agents, more API calls, more revenue.
17. $GOOGL — TPU infrastructure + Gemini API. Every token processed on Google Cloud prints margin.
(ENTERPRISE AGENT LAYER)
18. $NOW — Enterprise agents run on its platform. Every workflow automated burns more tokens daily.
19. $CRM — Agentforce deploys AI agents across sales, service, and marketing. Per-action token billing scales.
20. $PLTR — AIP platform runs AI agents on enterprise and government data. Token volume is its revenue driver.
(AI INFRASTRUCTURE)
21. $NBIS — Pure-play AI infrastructure at ground level. Token supercycle lifts the entire compute ecosystem.
22. $SMCI — Builds GPU server racks for data centers. Every NVDA chip needs a SMCI chassis to run.
23. $DELL — AI server sales to enterprises exploding. Token growth drives hardware refresh cycles faster.
24. $ARM — Chip architecture inside every mobile and edge AI device. Royalties scale with token proliferation.
$NOW is the most undervalued right now. This is why Jensen Huang says the market has made a mistake on it.
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@mildredsfierce2 You should watch his Keynote that he did 2 weeks ago about AI at the ServiceNow Knowledge 26 Conference.
He addressed it in detail!
If you can find it on LinkedIn it’s worth the watch.