The higher FY2028 target is encouraging, but I do not think US$20B alone is enough to carry MRVL significantly higher. The key question is whether earnings can catch up with the AI narrative. I would watch AI-related revenue growth, margins and whether hyperscaler demand remains strong enough to justify the current expectations. A raised target improves confidence, but once the market prices in strong growth, execution matters more than guidance. If Marvell keeps beating estimates and raising forecasts, the rally can continue. If growth merely meets the new target, valuation could become the bigger constraint. For me: bullish on the business, but increasingly selective on the share price.

A. AI & Technology 🤖 I’ll be watching AI policy most closely, especially any changes around chip export controls, data-centre power infrastructure, AI regulation and government incentives for domestic semiconductor production. These could have significant implications for the entire AI supply chain, from Nvidia and AMD to hyperscalers, utilities and data-centre operators. Around the midterms, even shifts in expectations for future policy could move valuations before any legislation actually changes.

C for me: ⚡ Data centres, power & infrastructure. AI models may change leaders quickly, but every serious competitor still needs compute, memory, networking, cooling and electricity. That makes the infrastructure layer particularly interesting because it can benefit regardless of whether OpenAI, Meta, Anthropic or another player ultimately wins the model race. I’m also watching D closely. The scale of AI capex is becoming enormous, so eventually revenue and free cash flow must justify it. Spending hundreds of billions is bullish for infrastructure suppliers, but not necessarily for the companies writing the cheques. My preferred approach is therefore to follow the bottlenecks: GPUs → HBM → networking → cooling → power. As one constraint gets solved, capital tends to move towards the n

I’d rather own the index here. The handful of mega-cap leaders may continue outperforming, but buying them after a strong run means accepting much greater concentration and valuation risk. If earnings or guidance disappoint, the same stocks carrying the market could also lead the correction. An index lets me participate in the AI and tech rally while retaining exposure to financials, industrials, healthcare and other sectors that could take over leadership if the rally broadens. I wouldn’t completely avoid the winners, but I prefer them as part of a diversified portfolio rather than making a concentrated bet. At record highs, diversification may look boring, but I’m happy to trade some upside for less single-stock risk. 📈

The answers are: 1A, 2B, 3C, 4B, 5A, 6B, 7B, 8B, 9C, 10B For Q9, the 2× ETF rises about 20% on Day 1, then falls about 18.18% on Day 2. Starting from 100: 100 → 120 → about 98.18, resulting in a small loss despite the underlying index returning to roughly its starting point. This demonstrates volatility drag from daily resetting.

I’d separate these into earnings-backed and expectations-backed record highs. My top three are TSMC, NVIDIA and Johnson Controls. TSMC and NVIDIA remain at the heart of AI compute demand, while JCI shows how AI spending is spreading into cooling and physical data-centre infrastructure. Its $21 billion backlog is particularly attractive. I’m more cautious on Lumentum after its huge run, and on MPC and VLO because today’s exceptional refining margins may not last indefinitely. CRWD and FTNT have strong fundamentals too, but their valuations leave less room for disappointment. 🥇 TSMC 🥈 NVIDIA 🥉 JCI I wouldn’t chase a stock simply because it is making new highs. At these valuations, I want earnings, cash flow and guidance to keep justifying the price. A great company can still be a poor inves

I think the market is worried about both sides of the equation at once: future supply rising while AI demand may arrive later than expected. Toshiba’s expansion raises the possibility that today’s HDD scarcity and pricing power eventually weaken. But analysts argue the reaction may be excessive. Morgan Stanley’s industry checks suggest Toshiba’s expansion is unlikely to eliminate the HDD shortage through 2028. The bigger risk may actually be demand timing. Morgan Stanley estimates a sizeable US data-centre power shortfall through 2028. If data centres cannot get powered on schedule, customers could delay equipment deliveries, hitting memory, storage and optical suppliers before Nvidia or Broadcom. That creates an awkward combination: more supply being planned for the future, but uncertaint

For now, I’d call it a headline running ahead of the order. Musk confirmed that TSMC and Terafab are in discussions, but there is still no disclosed contract value, capacity commitment or firm timeline. That makes TSMC’s record high partly a bet on what the relationship could become rather than revenue already secured. That said, I can understand why the market likes TSMC here. If Terafab needs enormous leading-edge capacity, TSMC is difficult to avoid. Even a multi-foundry strategy could leave it as a major beneficiary. Intel is the more interesting side of the trade. Musk previously said Terafab planned to use Intel 14A, so bringing TSMC into the discussion weakens the idea that Intel has a privileged position. My verdict: positive signal for TSMC, negative negotiating signal for Intel,

I’m not chasing the S&P 500 above 7,800. 📈 Record highs alone are not a reason to sell, but valuations and market concentration make Q3 earnings especially important. I want to see whether earnings growth and guidance can justify the latest repricing, particularly across AI, memory, optical communications and power infrastructure. The easing 10-year Treasury yield is supportive, but if yields reverse higher or mega-cap guidance disappoints, the market could quickly test how much optimism is already priced in. My approach: keep DCA-ing into broad-market ETFs rather than trying to time the top, while keeping some cash ready for a meaningful pullback. I would rather add more aggressively after a correction than chase a euphoric rally. So I’m still participating, just not accelerating. Ear

I think compute is resting on the more fragile assumption. The bullish compute thesis assumes AI capex can keep growing rapidly and, more importantly, that customers will eventually generate enough economic value from AI to justify all that infrastructure. If monetisation disappoints, hyperscalers could moderate spending surprisingly quickly. Memory is cyclical and vulnerable to oversupply, but demand is increasingly tied to real hardware requirements. AI accelerators need large amounts of high-bandwidth memory, while servers still need DRAM and storage. So I see memory’s risk as more about supply, pricing and cycles, whereas compute carries a bigger valuation and AI-ROI assumption. Both can fall, but if the market starts questioning whether every extra dollar of AI capex produces adequat

If I had $10,000 to invest today, I wouldn’t try to time the perfect entry. I’d put around 50% into broad-market ETFs, 15% into quality financials/dividend stocks, 10% into gold, 15% into short-term fixed income or money-market funds, and keep 10% cash ready for opportunities. “Higher for longer” is both risk and opportunity. Expensive growth stocks and highly leveraged companies could remain under pressure, while banks, insurers and cash-generating businesses may hold up better. At the same time, higher yields make cash and short-duration bonds genuinely useful again. I’d expect rates to stay relatively restrictive until inflation is convincingly under control, so I wouldn’t rush to go all-in. But if the market fell 10–20% without a major deterioration in fundamentals, I’d gradually depl

B for me. Singapore has strong advantages in infrastructure, regulation, connectivity, capital and its ability to attract global companies and talent. That gives it a credible chance of becoming one of Asia’s major AI hubs. However, competition from China, Japan, South Korea, India and other regional economies will be intense. Singapore’s smaller population also means developing and attracting enough AI talent will be crucial. I would consider moving into an AI-related career, especially a role combining AI with my existing expertise rather than starting completely from scratch. I think AI literacy will increasingly become valuable across almost every industry, not just technology. 🤖🇸🇬

For me, the roughly S$1,900 annual tax saving alone would not justify locking S$15,300 into SRS. The bigger question is how that money is used afterwards. If it simply sits in cash earning very little, I would rather retain the liquidity. But if the SRS funds are invested in diversified ETFs for 10–20+ years, the combination of tax savings and long-term compounding becomes much more attractive. I see SRS as a tax-advantaged investment account rather than just a way to reduce this year’s tax bill. Liquidity still matters, especially for housing, emergencies and other major expenses. So I would prioritise building sufficient liquid savings first, then use SRS for long-term investing. The tax saving is a bonus; compounding is the bigger reason. 📈

I’m still working towards my 2026 investing goals, but I’m happy with the progress so far. 📈 My biggest lesson this year has been that consistency matters more than trying to predict every market move. Instead of chasing whatever is performing well, I’ve been focusing on regular investing, broad diversification and keeping enough cash on the sidelines for my other financial goals. I’ve also become much more conscious of fees, FX costs and fund structure. Small differences may not seem important today, but over 10–20 years, they can add up. For the rest of 2026, my goal is simple: keep investing consistently, avoid making emotional decisions when markets become volatile, and continue building a portfolio that I’m comfortable holding for the long term. There will always be another rally, co

🎢📈💎 , a bumpy September, but still up and holding.

A. Below 100K. My prediction is around 90K jobs added in September. The labour market does not look like it is collapsing, but hiring appears to be cooling despite relatively low layoffs. For the bonus question, I think Treasury yields move first if payrolls significantly beat expectations. A strong jobs print could quickly shift expectations towards tighter Fed policy, pushing yields and the U.S. dollar higher. Stocks, especially rate-sensitive growth and tech names, could then come under pressure as higher yields are priced in.

B. More AI infrastructure & R&D. Nvidia’s strongest advantage is its technology ecosystem, so I would prioritise reinvesting cash flow into the next generation of GPUs, networking, software and AI infrastructure. Buybacks can improve per-share metrics, but sustained R&D investment could strengthen Nvidia’s competitive position as AI technology evolves. I would still support selective buybacks or acquisitions, but innovation should remain the core priority while AI demand continues to expand.

B. Growing staking income. Reaching a large ETH ownership target is eye-catching, but I think the more important question is whether those holdings can generate sustainable returns. Staking turns ETH from a passive treasury asset into an income-producing one, potentially compounding the value of BitMine’s holdings over time. ETH price appreciation would certainly help, but staking income gives the strategy another source of returns that is not solely dependent on price going up.

If interest rates stay higher for longer, I would not sit entirely in cash waiting for the “perfect” entry. I would adjust my allocation, keep investing, and make higher yields work in my favour. The latest Fed decision reinforces this scenario. In September, the Fed raised the federal funds target range to 3.75–4.00%, while its median projection puts the policy rate at 4.1% at the end of both 2026 and 2027. Inflation is also projected to remain above the 2% target for some time. If I had $10,000 to deploy today, my allocation would look roughly like this: 📈 $5,000 – Global/U.S. equities I would continue accumulating diversified ETFs rather than trying to time the bottom. Within equities, I would favour profitable, cash-generative companies with strong balance sheets. Higher borrowing cost