TapeVector

I started investing with $20,000. This was all the money me and my wife saved in 10 years. My first stock was $LMT. I bought around $200. Price dropped. I got scared. I sold for around $10 loss. I thought this is not for me. A few weeks later I tried again. I bought $BABA. Same thing. In 2018, in Romania, I had a poor relationship with money. I did not understand risk. I did not understand volatility. I did not understand business quality. I did not understand market cycles. So I started reading. Warren Buffett. Benjamin Graham. The Intelligent Investor. Investing for Dummies. Every investing book I found. Then I started building my own system. A system for finding stocks. A system for reading charts. A system for buying weakness. A system for holding when the thesis is alive. A system for selling when the risk changes. I made bad decisions. $WYFI, bought $32, sold $18. $HIMS, bought $35, sold $20. $AUR, bought $6, sold $4. $MDAI, bought $2.30, sold $1.90. $ARBE, bought $2.20, sold $1.90. $IREN, bought $60, sold $51. I also sold too early. $NBIS at $150. $BABA at $135. $OKLO at $110. $ORCL at $125 before price went near $300. But I also found serious opportunities. $META at $101. $AMZN at $83 after split. $GOOGL at $85 after split. $COIN at $34. $MARA at $3.34. $MSTR at $135 before the 10 for 1 split. $NVDA at $139 before the 10 for 1 split. $PLTR at $21. $ARM at $101. $RKLB at $23. $TSM at $64. $AMD at $58. $BABA at $64. $NU at $3.70. $IONQ at $7.53. $OKLO at $17.90. My road was not clean. I lost money. I sold winners too early. I bought some wrong names. I got scared more than once. But the good decisions were bigger than the bad ones. Now my main account is up almost 300% in 5 years. I am still learning. I am still improving. I still make mistakes. This profile is where I will show how I think as an investor and swing trader. No fake certainty. No perfect record. No theory without skin in the game. Only process, charts, companies, entries, exits, mistakes, and lessons. I just want to share my ideas, my charts and my research.

$ASTS is and must be a triple digit stock

This is bad, I was studying $INTC for a possible initial position, but now I am reconsidering because I think I can get it under $100 🤣

@retail_mourinho I got them all, but early so I am ok, I recently cut $MSFT with an 20% gain in 4 years 🙈🤦🏻‍♂️but the rest of them are up over 50%, and I also cut $AAPL las year after I concluded that they lost the AI race.

Imagine being invested in one of these bag7 stocks

@QualCompounders $GOOGL $META

Which quality compounder would you rather own here $GOOGL, $AMZN, $MSFT, or $META?

@HunterAllen4 That is what I do not understand

@TapeVector The projects sound legit but why are we still down here

$GPUS +66% One of the hottest AI infrastructure names on the market right now. I’ve been watching $GPUS closely as it completes a full transition from Bitcoin mining into AI data centers, colocation, GPU compute, and humanoid robotics. The biggest catalyst? $GPUS announced advanced negotiations for a 20MW AI compute agreement at its Michigan campus. Management estimates the deal could generate over $1 BILLION in revenue over 20 years. If expanded to 32-52MW, the total opportunity could approach $2.5 BILLION. The Michigan campus is a massive asset: • 617,000 sq ft facility • 34.5 acres • Currently ~30MW of power capacity • Targeting 70MW within 20 months • Long-term potential of up to 340MW The company is converting over 100,000 sq ft of the campus specifically for AI infrastructure and GPU deployments. Another thing that caught my attention: $GPUS holds approximately 713.6 BTC worth about $47M plus roughly $40M in cash and restricted cash. That’s about $87M in liquid assets, representing roughly 73% of the company’s recent market capitalization. Revenue growth has also accelerated. Preliminary Q1 2026 revenue came in around $44M, up 76% YoY from approximately $25M. The company is also pursuing a unique robotics strategy through subsidiary Omnipresent Robotics. Production has begun on the first 30 OPR-R2 humanoid robots that will be deployed at the Michigan AI campus. Long-term plans call for more than 143 robots operating on-site, creating valuable real-world AI training data while supporting facility operations. Management believes AI infrastructure offers significantly higher margins than Bitcoin mining and intends to transition the Michigan site fully toward AI workloads. The bull case here is simple: AI demand continues exploding. Power is scarce. GPU capacity is scarce. Data center space is scarce. $GPUS is attempting to monetize all three while maintaining a sizable Bitcoin treasury on the balance sheet. Still a highly speculative microcap with volatility, dilution risk, and execution risk. But this is exactly the type of AI infrastructure story that retail traders have been chasing all year. Worth keeping on watch.

@HunterAllen4 I like it very much

@TapeVector A little something something

$CUE What makes Cue Biopharma different from hundreds of other biotech companies? Its entire platform is built around selective immune modulation. Most immune therapies activate or suppress broad portions of the immune system. That can create effectiveness but often comes with significant toxicity or unwanted side effects. Cue’s technology attempts to mimic the body’s natural immune signaling system. The goal: Expand and activate only the disease-relevant T cells while avoiding broad immune activation. Think precision-guided immunology. The platform is built around validated modular components that can be recombined into multiple therapies. This potentially allows: • Faster development • Lower development costs • Greater pipeline expansion opportunities Pipeline structure: CUE-100 Series • Clinical-stage oncology programs • Generated human safety and activity data • Validated the platform in patients CUE-400 Series • Regulatory T-cell induction • Designed to restore immune tolerance in autoimmune disease CUE-500 Series • Targeted B-cell depletion • Designed to selectively eliminate pathogenic B cells One of the most interesting programs is CUE-401. Preclinical data has shown: • Induction of FOXP3+ regulatory T cells • Reduction of inflammatory pathways • Durable efficacy in autoimmune disease models • Favorable tolerability in animal studies The company has also validated the platform through major partnerships including: • Boehringer Ingelheim • ImmunoScape Rather than betting on a single drug, investors are effectively getting exposure to a broader precision immunology platform spanning oncology, autoimmune disease and allergy. That’s what makes the story interesting. @TheFlowShark This is a paid post. Not financial advice. DISCLAIMER 🔗 tinyurl.com/ye2yj2nr Sector Peers: $NTLA $IOVA $BNTX $VKTX $CRSP $EDIT $BEAM $SANA $XBI $HIMS $NUVB $UNH $MRNA $MRK $OSCR $CLOV

@HunterAllen4 Totally worth the post great post and yes the company is interesting.

@TapeVector I have very mixed feelings but it was worth sharing the info bro $BURU same situation I feel like maybe but idk

@HunterAllen4 Great post here bro

$CUE +8% Why are biotech investors watching this one? The catalyst calendar is packed for H2 2026. CUE-221 (formerly Ascendant-221) This may be the most important near-term catalyst. Cue recently acquired exclusive global rights outside Greater China. The asset is already in Phase 2 development. Targets: • Chronic spontaneous urticaria (CSU) • Food allergy What makes it unique? Unlike traditional anti-IgE therapies, CUE-221 has a dual mechanism. It can: • Neutralize circulating IgE • Potentially suppress future IgE production through CD23 signaling Earlier studies showed: • Durable IgE suppression • Strong basophil inhibition • Encouraging safety profile • Clinical responses in CSU patients Upcoming: • China Phase 2 data readout in H2 2026 • Potential U.S. IND amendment • Potential global Phase 2b food allergy trial CUE-401 Another major catalyst. A bifunctional IL-2 / TGF-beta fusion protein designed to restore immune tolerance. Recent preclinical data showed: • Generation of antigen-specific regulatory T cells • Reduction of pathogenic immune responses • Activity in autoimmune gastritis models • Activity in graft-versus-host disease models • Durable responses after treatment Upcoming milestones: • IND submission planned H2 2026 • First-in-human Phase 1 study expected by year-end Additional catalyst: Boehringer Ingelheim collaboration • First optimization milestone achieved • $7.5M already received • Up to $345M milestone opportunity remains Add in the new CEO, stronger balance sheet, expanding pipeline and multiple upcoming data readouts and it’s easy to see why biotech investors are keeping this name on watchlists. Small cap biotech remains high risk, but there are several potential value-inflection events ahead. @TheFlowShark This is a paid post. Not financial advice. DISCLAIMER 🔗 tinyurl.com/ye2yj2nr Sector Peers: $NTLA $IOVA $BNTX $VKTX $CRSP $EDIT $BEAM $SANA $XBI $HIMS $NUVB $UNH $MRNA $MRK $UNH $OSCR $CLOV

@HunterAllen4 Thanks,

@TapeVector Great post bro

The market improved, but leadership is still selective. My market journal, not financial advice. I updated my relative strength dashboard. This is not a buy list. This is my market structure map. The system shows where relative strength is concentrated. It shows which stocks are acting better than their benchmarks. It shows which sectors and themes are producing candidates. It also shows why some names pass and why others fail. I looked at both tabs: Dashboard Charts: fast visual read. Analysis Dashboard: evidence layer. Last refresh: 2026-06-16 Current dashboard pulse: 488 total candidates 145 trade ready 54 setup watch 289 research only 87 A leaders 88 B candidates Average swing score: 60.4 Top sector: SMH The first read: Market structure is better. Trade ready names are strong. A and B quality candidates are both meaningful. Average swing score is above 60. That tells me the market has real pockets of strength. But the leadership is not broad and equal. It is still concentrated. Top sector and theme pockets by quality: SOXX: 45 names Avg swing 74.0 XAR: 8 names Avg swing 71.4 SMH: 94 names Avg swing 71.2 CIBR: 5 names Avg swing 69.3 DTCR: 28 names Avg swing 65.6 XLK: 31 names Avg swing 65.2 ITA: 14 names Avg swing 63.6 WGMI: 9 names Avg swing 62.6 XLI: 77 names Avg swing 62.1 XLB: 44 names Avg swing 60.7 My read: Semiconductors still lead. SOXX has the best large quality pocket. SMH has the biggest leadership cluster. XAR remains strong but narrow. CIBR is interesting because the quality is high, but the sample is small. XLK is solid, but not the best pocket. XLI and XLB have breadth, but lower average quality. That matters. Count alone is not quality. A sector with many names is a leadership cluster. Not a buy signal. The reason code table is the most important diagnostic. Main reason codes: FAIL_DAILY_WEAK: 200 names PASS_TRUE_LEADER: 76 names PASS_TRADE_CANDIDATE: 69 names FAIL_WEEKLY_WEAK: 58 names FAIL_PRIMARY_20D_UNDERPERFORM: 34 names FAIL_QQQ_20D_UNDERPERFORM: 12 names WATCH_NEW_ROTATION: 10 names This tells me the market is better, but still uneven. A lot of names still fail daily strength. Some fail weekly structure. Some are not beating their own benchmark. Some are not beating QQQ. That means the dashboard is not showing an easy everything rally. It is showing selective leadership. Class distribution confirms the same thing: 170 strong theme / weak stock names 117 former leader / no entry names 88 B trade candidates 87 A true leaders 24 new rotation candidates This is a useful mix. The A and B groups are strong enough to review. But the C groups are still large. That means many names are information first. Not execution first. Top true leader and trade review names include: $ACMR $AIP $AMAT $SNDK $UCTT $LRCX $COHU $TER $ONTO 6488 $VECO $TTMI $MKSI $KLIC 4062 This list is heavily tied to semiconductors. That is the clearest message in the dashboard. Equipment. Semi process. Testing. Storage. Advanced manufacturing. The market is still pointing there. Top tactical acceleration names include: $QMCO 285A $SIVE $ARM 6981 $VATE $ALAB $BFLY $WDC $ENGS 6488 $CRS $CLOV $STX 1303 This is the now list. Strong tactical relative strength. But tactical strength is not automatic trade quality. The chart still has to confirm. New rotation watch names include: $CLOV $ARQQ $LNAI $ORBS $SCLX $HROW $TMDX $HIMS $TEM $BLZE $NTLA $NXTT $MRNA $PRCH $AVTR These are early rotation candidates. Watchlist first. Confirmation second. Execution last. The strong theme / weak stock group is also important: KEEL QBTS RGTI RTX HEI PXLW TXN CLSK HIVE XNDU SYNA LAES BZAI IONQ POET These names sit inside stronger themes. But the model is not treating the individual stock as a clean leader right now. That protects me from lazy theme buying. A strong theme does not mean every stock inside it is the right vehicle. Final market read: The market is improving. Semiconductors remain the core strength zone. SOXX and SMH still matter most. XAR, CIBR, and ITA are worth watching. WGMI and QTUM show theme strength, but stock quality is mixed. Industrials and materials have breadth, but not the same quality. Healthcare has some rotation names, but weaker overall average quality. The dashboard gives me the map. Manual chart validation still comes next. This is not a buy list. It is a relative strength screening system. Price first. Relative strength second. Theme confirmation last.

@HunterAllen4 Today is the day, I’ll give you a tag

@TapeVector Have you looked in to $TRT

$AEHR long term portfolio update. My investing journal, not financial advice. Position snapshot: Average buy price: around $93 Position role: $AEHR is a long term position for me. Not a short swing trade. This is one of my AI infrastructure and silicon photonics exposure names. Current update: Aehr received a follow on production order for its FOX-XP system from an unnamed global networking leader. The customer is developing silicon photonics transceivers for AI data centers. The system is configured for 9 wafers at the same time. Delivery is expected within 6 months. Additional orders are already forecast for 2026. My read: This is a good update. Not because it sounds like AI. Because it points to production demand. That is the key difference. $AEHR is not selling a broad AI story here. It is selling wafer level test and burn in equipment into a real silicon photonics production path. That matters. AI data centers need faster optical links. Silicon photonics transceivers need reliability testing. Wafer level burn in becomes more important when customers need scale, quality, and yield control. That is where $AEHR fits. What is proven: The customer came back with a follow on production order. The use case is tied to silicon photonics transceivers. The end market is AI data centers. The tool is moving into production configuration. What is still not proven: The customer name. The full order size. The total 2026 order volume. The fiscal 2027 revenue conversion. The long term margin profile. That is why I like the update, but I still separate the business thesis from execution proof. My plan: I am holding $AEHR in my long term account. The update strengthens the thesis. But I am not treating one order as the full story. I want to see the follow on orders convert. I want to see bookings turn into revenue. I want to see fiscal 2027 growth show up in the numbers. And I still want the chart to support any new add. Final read: Strong update. Real customer validation. Better silicon photonics evidence. More AI data center relevance. Still execution dependent. For me, $AEHR remains a long term position. Evidence first. Orders second. Execution last.

@HunterAllen4 Thanks

@TapeVector Great post bro

GlobalWafers 6488 is up around 60% since I wrote my article about it in May 2026. My investing journal, not financial advice. I am not invested. And yes, I am sorry I am not. At the time, my international portfolio was already full. That was the real constraint. But this is still a useful journal lesson. The article was not about chasing the obvious chip names. Not $NVDA . Not $AMD . Not $TSM . It was about looking one layer deeper. Before the chip, there is the wafer. No wafer. No chip. That was the thesis. GlobalWafers was not a perfect stock at that price. I did not call it cheap. My framework was watchlist. No buy for my process. But the business quality was real. Global scale. Oligopoly structure. Hard customer qualification. Strategic position upstream of the semiconductor cycle. Now the stock is up around 60%. I missed the trade. But I did not miss the lesson. Sometimes the boring input layer gives the cleaner cycle read. The goal is not to own every right idea. The goal is to build the process that keeps finding them. Evidence first. Valuation second. Decision last.

$SOFI at a key level, will it break or maybe it will go back and make an double top and then go lower. Nobody knows, maybe just the CEO. $FINX

@StockPatternPro I feel for you, I have 4 dogs and two are very old

Hey everyone I need to take some time off to deal with the sudden loss of my 13 year old rescue baby Judy who I just had to put down. I'm forever heartbroken.

@fundmyfund @bodoxstocks yeah totally

@TapeVector @bodoxstocks buy 9s sell 12s

$ONDS has fallen back to the orange box @bodoxstocks hates the orange box more than even the blue box

@Gubloinvestor the $XLF broke the trend line, so there are good chances that the upward continues for $HOOD $SOFI $DLO $SHOP $PGY and more

Will $Hood give up the gains tomorrow?

@Gubloinvestor Probably not, it depends on the macro, but from what I see the $FINX is starting to get it's head above the water. It might break the trendline there.