To The Moon

I think the US$20 billion FY2028 revenue target is a positive signal, especially because Marvell $Marvell Technology(MRVL)$ has raised its target again, driven by AI data centres, custom silicon and interconnect. To me, this shows management is seeing stronger demand ahead rather than just short-term AI hype. However, I would not chase the stock purely because guidance was raised. At around US$287, expectations are already high, so I want to see actual customer orders, revenue growth and margins catching up. Guidance is encouraging, but execution matters more. Personally, I remain bullish on AI semiconductors, but I would rather accumulate on meaningful pullbacks than FOMO after a strong rally. If Marvell keeps raising guidance and delivers the

For me, the 2026 midterms are worth watching, but I would not invest based purely on which party wins. What matters more is how policies around AI, semiconductors, tariffs, energy, healthcare, financial regulation and crypto could change. AI and semiconductor stocks are especially interesting as technology, trade and data-center infrastructure become increasingly connected. I would not assume the election alone will determine market direction. With valuations elevated and Treasury yields high, I will pay closer attention to earnings, inflation and interest rates. Political headlines may create short-term volatility, but strong fundamentals should matter more over the longer term. Personally, I will focus on companies I understand rather than predict every election headline. I would rather

I would choose ①. I think AI is more likely to strengthen the moat of leading SaaS companies that already control enterprise data, workflows and customer relationships. Replacing these systems is much harder than simply generating code or building an app. For companies like $Salesforce.com(CRM)$ and $ServiceNow(NOW)$ , AI agents could become a new monetization layer rather than a direct threat. I am especially interested in whether customers are willing to pay more for AI-driven automation and whether this can translate into meaningful incremental ARR. That said, I would not ignore the longer-term risk. If AI eventually lea

I think the more fragile assumption is the idea that AI-related memory and hard-drive shortages will stay tight for years. Toshiba’s expansion shows that high prices can eventually bring more supply, so I would be cautious about assuming today’s pricing power will last indefinitely. I am still more comfortable with AI compute, where $NVIDIA(NVDA)$ , $Advanced Micro Devices(AMD)$ and $Broadcom(AVGO)$ continue to benefit from strong infrastructure demand. However, valuations are high, so expectations also need to stay realistic. I am also watching long-term yields closely. Even with October rate-hike odds falling, the 10-year yield remains above 5%, which could p

I would rather own the index while selectively holding the strongest names. The Nasdaq hitting a record shows strong tech leadership, but the narrow market also means higher concentration risk. I am still bullish on the long-term AI trend, but I do not want to chase momentum blindly. I am watching semiconductors and AI infrastructure closely, but I prefer confirmation over headlines. I would rather wait for pullbacks and scale in gradually than make a large move after a strong rally. My approach remains DCA and adding gradually. The market can stay strong even when leadership is narrow, but I want to see broader participation before becoming more aggressive. For me, consistency and patience matter more than catching every short-term move.

For me, my answers are: 1A, 2B, 3C, 4B, 5A, 6B, 7B, 8B, 9C, 10B. I am quite familiar with ETFs, but leveraged ETFs are where I pay much more attention to daily resets, volatility and compounding. I would not treat TQQQ or SOXL like a simple long-term ETF. My biggest takeaway is that ETF investing is not just about picking the right index. Fees, leverage, interest rates, concentration and volatility can all change the outcome significantly. I prefer using ETFs according to their purpose, while staying disciplined and avoiding FOMO. @Tiger_comments @TigerClub @TigerStars

I think this list shows AI is becoming much broader than GPUs. $NVIDIA(NVDA)$ and $Taiwan Semiconductor Manufacturing(TSM)$ remain core beneficiaries, while I am also watching $Lumentum(LITE)$ , $CrowdStrike Holdings, Inc.(CRWD)$ , $Fortinet(

My stock nickname is "XXX" — “The Memory Monster from Idaho” 👹💾🇺🇸 The clue is in the name: a US-based memory and storage company, with DRAM, NAND and HBM all riding the AI boom. "XXX" recently delivered record FY2026 results and guided for another record year, so the “monster” seems to be getting stronger. There are plenty of memory monsters out there, but only one is my US-listed “Memory Monster from Idaho”. 😎 Please guess the "XXX" stock!

I do not treat analyst upgrades and downgrades as direct buy or sell signals. What matters to me is why the rating changed, especially whether it is fundamentals or valuation. A good company can still be a poor investment if too much optimism is already priced in. $Netflix(NFLX)$ and $Target(TGT)$ stand out to me because both show how better risk-reward can emerge when expectations become more reasonable. $Moderna, Inc.(MRNA)$ is a good reminder that strong prospects do not always make a stock attractive at its current valuation. I will continue doing my own homework rathe

I find the $Broadcom(AVGO)$ -Anthropic deal interesting because it shows how AI infrastructure financing is evolving. Vendor financing does not automatically mean demand is fake, but it makes me question how much spending is backed by genuine cash flow. For me, demand quality matters more than the size of AI orders. A large compute commitment backed by strong revenue is very different from one that keeps expanding through debt and financing. If AI usage grows fast enough, financing simply accelerates the buildout. I will watch Broadcom, $NVIDIA(NVDA)$ and the hyperscalers closely, especially infrastructure commitment