To The Moon

🌟🌟🌟My response is C:  Both Marina Bay Sands $Las Vegas Sands(LVS)$ & $Genting Sing(G13.SI)$ can benefit from bigger tourism market. Singapore is not treating this as a zero sum cage match between 2 competing properties.  Instead the Singapore government is deliberately curating a massive structural tourism expansion to scale the country's global market share. The eye watering USD 8 billion Marina Bay Sands or MBS expansion paired with Genting SGD 6.8 billion RWS 2.0 blueprint is designed to grow the total addressable market of luxury, VIP and high yield event visitors to Singapore. When Singapore introduces the infrastructure to capture massive global music tours, world class exhibitions

table 11. Visa one of my biggest holdings have been quietly compounding while everyone focus are on hyperscalers. Examples from recent data: ~31–34% in 2025/2026 periods; multi-year averages often in the high 20s to low 30s. It comfortably exceeds Visa’s cost of capital (WACC typically estimated around 8%), creating a wide positive spread and substantial economic value. This reflects Visa’s asset-light network business model: enormous operating leverage, high margins (operating margins often ~60%+), strong free cash flow conversion, and limited need for heavy capital reinvestment relative to profits. The global payments network benefits from scale, network effects, brand strength, and high switching costs—classic durable competitive advantages that support ROIC persistence

Mathematical Money | September 6, 2026 Oracle reports Q1 on Thursday. It's an odd setup going in. The stock closed Friday at $153.75, which sounds healthy until you notice it traded as high as $345.72 within the last year. It's 54% off that. And yet Barclays, Morgan Stanley and JPMorgan all raised their price targets into this print — Barclays went to $281 from $221, and the average across the top analysts is sitting around $261. So the sell-side thinks it's worth roughly 70% more than it trades, the chart says it's been cut in half, and the print lands Thursday after the close. Consensus is looking for about $19.1 billion of revenue and $1.30 of GAAP EPS. Take your pick which of those you believe. I made my choice last week. Bought three October 2027 $120 calls. How I got here In late Aug

I would trust the hold, but I am not ready to call peak rates yet. Waller has taken some pressure off, but he has not closed the door on another hike. Payrolls around the +56k consensus with wage growth easing to 3.0% would strengthen the case that the Fed can afford to wait. A much stronger jobs print, especially with hotter wages, could quickly revive the hawkish trade. More importantly, Waller himself has made August inflation the key test. So for now: September hold > hike, but peak rates still need confirmation from CPI. I would rather miss the first leg of a rally than price in the end of tightening too early.

I would take Circle for the longer-term thesis, Coinbase for the cleaner cyclical trade, and Strategy only if I specifically wanted amplified Bitcoin exposure. Strategy gives the biggest torque when BTC rallies, but that cuts both ways. At 845,050 BTC, the thesis is increasingly Bitcoin plus financing mechanics rather than an independent operating business. Coinbase is different: it benefits from activity. If $80k brings trading volumes, institutional flows and broader crypto participation back, it does not need Bitcoin itself to double. Circle is the most interesting structurally. USDC already has scale, while the September 16 Arc launch adds another layer to the moat through institutional infrastructure. Visa, Mastercard and BlackRock involvement matters, but the 21-bank stablecoin conso

B: SNOW. It is the breakout I would most want to own after a pullback because the rally has fundamental support, not just momentum. Strong earnings, accelerating product revenue and growing AI adoption give SNOW a clearer path for earnings to catch up with expectations. BE would be my second choice, but after the breakout and S&P 500 catalyst, I would wait for the excitement to cool before entering. I would be cautious with HOOD/COIN/MSTR because much of their near-term upside depends on Bitcoin holding above $80k. MSTR adds another layer of leverage on top of that. I would avoid chasing TSLA. Cybercab is a major milestone, but the valuation already assumes enormous future scale while deployment remains tiny and regulatory risk is unresolved. My ranking: SNOW > BE > crypto baske

Micron closed Friday +6.10% around $1,014, reclaiming the psychologically important $1,000 level while the S&P 500 fell. Like SNDK, MU benefited from Dell's $95B AI-server backlog and expectations for another major jump in memory contract prices. But MU has one additional risk its peers do not: Nearly 10,000 Taiwan workers are threatening strike action. The Taiwan Risk Is Real, But Not Yet a Production Problem More than 80% of surveyed union members reportedly supported strike action over bonuses and profit-sharing. That sounds alarming because Taiwan is critical to Micron's manufacturing footprint. But the distinction matters: No strike has started. Production has not stopped. For now, this remains a labour negotiation. That creates an unusual paradox. If Micron production were disrup

Iggy's Journal: A Small SGX Name With a Big Satellite Partner 5 September 2026, PM Analyst Rating Maybank Research reiterated a BUY call on Addvalue Technologies (A31), unchanged target price 34 cents, based on 30 times FY27 forecast price to sales. The call is built on two new orders totalling US$5.0 million, US$2.8 million for its Inter-Satellite Data Relay System products and US$2.2 million for its Advanced Digital Radio System products, the latter covering both design work and repeat supply to defence-technology customers. Addvalue's reported orderbook now stands at US$20.2 million. The bigger story behind the number is the Viasat partnership. Viasat plans to fold Addvalue's satellite relay terminals into its HaloNet portfolio for US government and government-supplier opportuniti

A few charts are sitting at some very interesting levels right now. $IREN Ltd(IREN)$ is the one that really stands out. After sweeping the 1H swing point, price is now testing an important point of control on the THT Volume Pro. There’s not much volume sitting above $45, which is exactly why I’m watching this level so closely. A clean move through it could turn into a much bigger breakout over the next couple of months. 🚀 $Kratos Defense & Security Solutions(KTOS)$ is taking a different path and has dropped back into a double Smart Money Zone. This is the spot where I want to see buyers show up. If the zone holds, the bounce setup is there. 👀 $Cerebras Systems(CB

The stock market closed muted this week. The $S&P 500(.SPX)$ finished flat (+0.1%) following an intra-week pullback that exceeded our bearish target of 7,642. By Thursday, weak economic data (ADP) and dovish remarks from Federal Reserve Governor Christopher Waller (who noted he would support holding interest rates steady this month if incoming inflation numbers remain favorable) sparked a relief rally. However, as I highlighted last night in my daily note, key structural elements warranted skepticism regarding continuation for today. To avoid premature moves, I rely on daily levels to validate each thesis. For today, 7,730 served as the anticipated central daily level (CDL) dictating bullish or bearish momentum. Once price broke below that lev

This week we got a peak into OpenAIs new model Astra. I thought this was an important model because it’s rumored to use a new technique called recurrent depth. In this post I want to discuss what that means and what the implications are. But first - a quick timeline of some of the larger breakthroughs in model architecture: 2017: The Transformer era. The leap here was self-attention mechanism. Before 2017 recurrent neural networks (RNNs) processed text word-by-word. The now famous paper Attention is Al You Need introduced the Transformer architecture which made parallel training possible 2018-2020: Decoder-Only Architectures. The leap here was autoregressive scaling and in-context learning. Early on transformers used a encoder-decoder setup (like BERT). OpenAI flipped this by scaling decod