苏36
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The most valuable takeaway for me is that retail investors have structural advantages that are often overlooked. Unlike professional fund managers, we are not tied to short-term performance targets, redemption pressure or strict investment mandates. This gives us the freedom to build a portfolio around our own goals, risk tolerance and time horizon. I also found the discussion about cash, turnover and momentum particularly useful. Holding cash provides flexibility during volatility, but excessive cash can create a significant opportunity cost. At the same time, blindly “buying the dip” is not always the best strategy, especially when negative momentum continues. Ultimately, good investing is not just about picking great companies. It requires disciplined portfolio management, emotional co
@TigerClub:James Ooi's Portfolio Seminar Recap: Building and Reviewing Your Investment Portfolio
I’d pick Ivan_Gan’s view as the most actionable. Bitcoin and gold offer clear technical levels, but macro policy is still the bigger driver across asset classes. If Fed hike expectations continue to fade, liquidity-sensitive assets like QQQ and SPY could remain supported even if markets stay range-bound. That said, gold’s breakout deserves attention. A short squeeze may explain the speed of the move, but sustained strength would suggest deeper institutional demand rather than just positioning. For Bitcoin, $67K is the key confirmation level, while $57.8K remains the line bulls cannot afford to lose. Personally, I’d rather wait for the breakout than chase the middle of the range. @WallStreet_Tiger [你懂的]
Alibaba is clearly choosing growth over near-term profits. A 75% jump in capital expenditure, largely directed toward AI infrastructure, looks painful today, but the 45% growth in cloud revenue suggests the investment is beginning to generate real demand. The bigger issue is whether this spending can eventually create operating leverage. A roughly 75% decline in reported net profit shows that Alibaba’s margin structure is still under serious pressure. I would not treat Alibaba as simply a “cheap AI stock.” It is a bet on whether AI and cloud can become the next profit engine. If AI monetization accelerates, today’s margin compression could prove temporary. If growth slows, however, investors may discover that the margin floor is lower than expected. For me, Alibaba is a long-term platform
The most interesting takeaway from this earnings season is that AI demand isn’t slowing—the market is simply becoming more selective. CRWV and NBIS were rewarded because their numbers show real demand: accelerating revenue, massive backlogs, and improving profitability. SMCI also benefited because AI demand is translating directly into stronger revenue and margins. Meanwhile, COHR and CBRS tell the other side of the story. COHR delivered a strong quarter, but after a huge run-up, a simple beat was no longer enough. CBRS had impressive future commitments, yet investors focused on weak hardware revenue. That tells us where the market is heading: AI stories are cheap. AI earnings are valuable. Going forward, I’d focus less on who has the most exciting AI narrative and more on who can convert
I lean toward B. To me, this looks more like a healthy reset in expectations than the beginning of a new downcycle. After such a strong rally, memory stocks were priced for near-perfect execution, so even solid earnings and guidance weren't enough to satisfy investors. The bigger question isn't whether NAND is slowing—it's whether that weakness spreads to DRAM and HBM. So far, AI demand hasn't changed. Hyperscalers are still investing aggressively, HBM supply remains tight, and AI servers continue to require more high-performance memory. That's why I think Micron is in a different position from pure NAND players. Its AI growth is increasingly driven by DRAM and HBM rather than NAND alone. Unless we start seeing analysts cut DRAM/HBM forecasts or AI capex slows meaningfully, I'd view this
My favorite stock from this week’s list is $RKLB. I think Rocket Lab has an interesting long-term story, not only because of its launch business, but also its Space Systems segment and the potential of Neutron. The valuation is not cheap and execution risk is still high, but if the company continues to deliver, I believe the upside could be substantial. I also like $CSCO as a more established choice. AI data centers are creating strong demand for networking infrastructure, so I’ll be watching its EPS, revenue growth and management guidance closely. For dividends, $IBM stands out to me because it offers a combination of income and exposure to AI/software growth. Overall, I don’t think investors should focus only on whether EPS beats estimates. Guidance, margins, cash flow and future
For me, I’d pick Micron for the next three years — but with a much higher risk tolerance. Berkshire is the safer compounder, while Nvidia remains the core AI leader. But Micron has an interesting middle ground: it’s benefiting from the same AI spending boom, yet the market is only now starting to treat memory as strategic infrastructure rather than a commodity. The key is HBM. If AI demand keeps growing and memory supply remains tight, Micron’s earnings could surprise on the upside. That gives MU more potential upside than Berkshire, although the volatility will be much higher. So my ranking would be: MU for upside, NVDA for AI leadership, BRK for stability. The real question isn’t whether Micron can stay above $1 trillion — it’s whether AI has permanently changed the memory cycle. If the
If I had to choose, I’d rather own the “toll collector” in the memory cycle than the companies forced to absorb higher costs. The key point is that rising memory prices are no longer an isolated semiconductor story. They are spreading downstream—from smartphones to GPUs and AI infrastructure. Xiaomi’s adjusted profit fell 42.6% year over year as higher memory costs squeezed margins, while Intel’s Arc Pro B70 prices have reportedly risen sharply in some markets. That tells me pricing power currently sits upstream. But I would not blindly chase memory stocks after their huge run. The better strategy is to own the suppliers with strong pricing power, healthy balance sheets and long-term AI demand, while avoiding companies whose margins are being compressed. In short: follow the money upstrea
Alphabet Still Wins Among these four calls, I agree most with the Alphabet upgrade. The key is that Google’s AI investment is no longer just a massive spending story. Google Cloud is accelerating, margins are improving, the backlog is huge, and its in-house TPU technology could eventually strengthen both competitiveness and profitability. That gives GOOG a compelling AI re-rating opportunity. I’m more cautious on CRWD and PLTR. Both remain excellent businesses with strong growth, but their valuations already assume years of near-perfect execution. At such multiples, even a small slowdown can trigger a sharp correction. PYPL is the wildcard. The potential M&A deal could create upside, but it is fundamentally an event-driven trade rather than a pure turnaround story. My ranking: GOOG fi
SNDK can reach $2,200, but I wouldn’t chase it blindly. What makes this rally different is that the story is shifting from simply “NAND prices are going up” to better earnings visibility, supply discipline, long-term contracts and AI inference potential. If management can deliver the targeted margins and FCF while HBF becomes a real product by 2027, the market could start valuing SNDK less like a traditional cyclical memory stock. But after a 467% YTD rally, expectations are already sky-high. At this level, the risk isn’t that SNDK has a bad business—it’s that the business performs well while investors expect perfection. So I’m closer to B: bullish, but waiting for a pullback. For me, $2,200 is achievable, but the next 30–40% won’t come from hype. It has to come from real earnings growth,
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