To The Moon

The Fed decision is the big event this afternoon, with another 25 bps hike to 3.75%–4% widely expected. A lot of that risk may already be baked into $SPDR S&P 500 ETF Trust(SPY)$ . Still, the market has plenty of reasons to stay volatile. 🇺🇸⚔️🇮🇷 Higher rates, inflation, the Japanese yen unwind and the uncertainty around the midterms are all adding pressure to the tape. That leaves room for another pullback. I’m watching $748–$750 as a possible downside zone into next month if volatility picks up. 📉 But there’s another side to the trade. $SPY is ultimately tied closely to the earnings power of the companies inside it, and corporate earnings remain extremely strong. That’s why I still see room for a move toward $780+ in Q3 and potentially $820 by

3 powerful emotions in trading: 1. TRUST Trust your process. Trust your system. Trust your edge. Trust is built through preparation, repetition and watching your edge work over hundreds of trades. 2. CONFIDENCE Confidence is believing you can execute your system properly over a long period of time. Not because every trade will work, but because you know you can consistently follow your rules. 3. ACCEPTANCE Acceptance is the hardest. Once you enter a trade, you cannot control the outcome. Your job isn’t to predict what happens next; your job is simply to execute your system. When markets keep you watching, knowing when to switch off matters too. A strong U.S. jobs report has put rates back in focus, with this week’s CPI data set to be another key market mover — keeping overnight trading fir

Here are the expected moves for Sept 14–18 as the market heads into one of the biggest weeks of the month. 📍 $SPDR S&P 500 ETF Trust(SPY)$ Close: $764.29 EM: ±$12.81 Range: $751.48 – $777.10 📍 $S&P 500(.SPX)$ Close: 7,656.98 EM: ±126.66 Range: 7,530.32 – 7,783.64 📍 $S&P 500 Mini-SPX(.XSP)$ Close: $765.70 EM: ±$12.44 Range: $753.26 – $778.14 📍 $Invesco QQQ(QQQ)$ Close: $714.88 EM: ±$15.47 Range: $699.41 – $730.35 📍 $iShares Russell 2000 ETF(IWM)$ Close: $288.89 EM: ±$6.48 Range: $282.41

I’m laying out all 8 steps of the swing strategy I want you to learn over the next 8 weeks. Each week, focus on ONE step. Don’t rush it. The goal is to build a repeatable process you can actually follow. 1️⃣ Trade with the bull market This strategy is designed for a bull market. The current cycle is still relatively young in my framework, so I want to stay focused on buying strong companies during healthy pullbacks rather than fighting the bigger trend. 2️⃣ Focus on strength Keep your watchlist concentrated around AI and companies with positive, growing revenue and EPS. Names I’m watching include: $Apple(AAPL)$ $Meta Platforms, Inc.(META)$ $Tesla Motors(TSLA)$

You don’t need 10 trades a day. You need one setup you know how to trade — and the discipline to wait for it. The results from some of the recent trades speak for themselves: 🔥 $Micron Technology(MU)$ swing — $1.08 → $11.50+ That’s a 1,000% move. 📈 $SPDR S&P 500 ETF Trust(SPY)$ calls — 500%+ 🚀 $Tesla Motors(TSLA)$ calls — $2.00 → $6.00+ 💥 $Meta Platforms, Inc.(META)$ — live trade from $1.80 → $8.00+ And now I’m watching $Advanced Micro Devices(AMD)$ . The next moon breakout could be setting up. The point isn’t to chase every move in the market. It’s to find one repeatable setup,

Last night, I live-traded $Meta Platforms, Inc.(META)$ from $1.80 to $8.00+, capturing a 500%+ return in front of thousands of traders. 🔥 Now I’m watching four setups closely. $Alphabet(GOOG)$ This is the big reversal play on my radar. The idea is a move back toward $350, with a longer swing target of $400+ if the reversal continues to develop. $350 is the first level I want to see reclaimed. $Tesla Motors(TSLA)$ TSLA is more of a continuation setup. The focus is a move back toward the $365–$370 area. Rather than chasing strength, I’m watching whether the current move can continue toward that zone. $Meta Platforms, Inc.(MET

President Trump is once again talking up the market, saying: “The stock market will go up.” But look at the stocks he owns. According to his quarterly disclosures, these 10 names are among his reported holdings: 📉 $Palantir Technologies Inc.(PLTR)$ — bought 9 times since January, up to $680K 📉 $Axon Enterprise, Inc.(AXON)$ — bought Feb. 10, $1M–$5M 📉 $NVIDIA(NVDA)$ — bought in January ($500K–$1M) and Feb. 10 ($1M–$5M) 📉 $Microsoft(MSFT)$ — bought in February, $1M–$5M 📉 $Oracle(ORCL)$ — bought in February, $1M–$5M 📉 $ServiceNow(NOW)$ — bo

Is it too late for President Trump? A massive $SPDR S&P 500 ETF Trust(SPY)$ reversal could come if Trump changes course and makes the election about one issue above all else: affordability. Six policy moves could change the trajectory: 1️⃣ Make affordability the only message Gas, groceries, rent and insurance. Every rally, every speech and every post should come back to the cost of living. Nothing else cuts through with swing voters as effectively. 2️⃣ Pause tariffs on consumer staples Temporarily pause or exempt tariffs on food, clothing, electronics and other everyday goods through year-end. Voters would feel the difference at checkout within weeks, while removing one of Democrats' strongest lines of attack. 3️⃣ Avoid a government shutdown Fu

One of the most interesting AI infrastructure themes right now has little to do with the GPUs themselves. Elon Musk recently argued that roughly 15 GW of AI compute capacity built in 2027 may not be able to turn on that same year. The reason is simple: having GPUs is not the same thing as having a functioning AI data center. You still need transformers, switchgear, wiring, cooling systems, chillers and high-speed networking. And those components are increasingly becoming the bottleneck. ⚡ 🔌 Power Infrastructure $GE Vernova Inc.(GEV)$ One of the broadest ways to play the electrification bottleneck, spanning turbines, grid equipment and switchgear. The company booked about $2.4B of data-center electrification orders in Q1 2026, according to the figur

Whether you’re up $192, $1,920, or $193,000 like me, the playbook stays the same. These are the AI names with the strongest long-term setups right now: 🔥 $NVIDIA(NVDA)$ — The core compute play. AI models depend on its silicon, while demand for accelerated computing keeps compounding. ⚡ $Broadcom(AVGO)$ — Custom AI chips + networking. Hyperscalers need both to build increasingly massive AI clusters. ☁️ $Microsoft(MSFT)$ — Azure turns AI demand into recurring enterprise revenue, backed by a software distribution network few can match. 🏛️ $Palantir Technologies Inc.(PLTR)$ — The deployment layer, turning AI capabilities int