I’m broadly aligned with Wall Street’s bullish AI view, but I don’t think every upgrade means it’s time to chase. I’m watching $NVIDIA(NVDA)$ , $Broadcom(AVGO)$ , $Micron Technology(MU)$ and $Advanced Micro Devices(AMD)$ most closely, with earnings growth and cash flow being the key factors. I’m particularly interested in Micron Technology because AI demand is increasingly a memory and HBM story, not just a GPU story. Broadcom(AVGO) also looks attractive with its custom AI accelerators and networking exposure. Overall, I think the AI cycle is spreading across chips, memory, networking and cloud infrastructure. The bigg

I’d go with A) Copper & Mining. $BHP Billiton(BHP)$ , $Southern Copper Corp(SCCO)$ and $Freeport-McMoRan(FCX)$ are benefiting from structural demand from electrification, grid expansion and AI data centers, while limited supply growth keeps the long-term copper story attractive. Among them, I’d pick FCX for its strong copper exposure and Grasberg production growth. That said, I wouldn’t aggressively chase

I find $Microsoft(MSFT)$ Microsoft’s AI strategy the most convincing because it is already turning AI investment into visible revenue through Azure and Copilot. Alphabet $Alphabet(GOOGL)$ is also attractive with its diversified Search, Cloud and Gemini strategy, but I think AI monetization and ROI will matter more than simply spending the most. I believe the late-July selloff was partly amplified by forced hedge-fund liquidation, but valuation and crowded positioning were also important factors. Strong earnings alone may not be enough when future growth is already priced in. I remain cautiously bullish on AI, especially if Jackson Hole and the Fed signal a more supportive rate environment. Personally,

For me, $NVIDIA(NVDA)$ is the clear standout from this week’s earnings list. Strong EPS expectations and continued AI infrastructure demand make it difficult to ignore. I’m watching not only whether NVDA beats EPS, but also whether its forward guidance can justify the high expectations already priced into the stock. I’m particularly interested in how Nvidia’s margins hold up as memory and component costs rise. If it can maintain strong profitability despite higher input costs, that would reinforce my bullish long-term view and highlight its pricing power across the AI ecosystem. I’d rather accumulate NVDA gradually than chase a big move around earnings. Short-

I’m watching the STI closely after last week’s 0.95% decline. Gold-related strength stood out & I remain bullish on gold as safe-haven demand continues to support precious metals. The index holding above 5,650 is also encouraging and suggests that downside momentum has not fully taken control. For the week ahead, Singapore CPI and the final Q2 GDP figure are the key data points I’ll be watching. On the stock side, GLD Singapore (GSD) remains my main focus, while SIA (C6L) is also worth watching as its S$0.29 final and special dividend is paid out. I’m particularly interested in whether gold momentum can continue to outperform while broader equities remain volatile. Overall, I’m staying cautiously optimistic and will continue looking for selective opportunities rather than chasing the

$ServiceNow(NOW)$ I'm continuing to DCA into ServiceNow ($NOW) because I still believe the long-term fundamentals remain much stronger than the short-term price action suggests. ServiceNow is no longer simply an IT workflow company—it is positioning itself as an AI control tower for enterprises, connecting AI, data, security and workflows on a single platform. Its Q2 2026 results reinforced that thesis, with subscription revenue growing 24.5% year over year and remaining performance obligations reaching $29 billion. What gives me confidence is that the AI story is increasingly translating into real commercial adoption. ServiceNow AI crossed $1 billion in annual contract value in Q2, while agentic AI deployments increased significantly. The com

I think Samsung’s challenge isn’t whether it can build 2nm, but whether it can turn that technology into stable yields, major orders and repeat customers. $Taiwan Semiconductor Manufacturing(TSM)$ ’s real moat is its ecosystem and execution, not simply node leadership. Samsung needs strategic AI customers to trust it with multiple generations of chips. I’m most bullish on HBM and advanced packaging for the next AI cycle. $SK hynix(SKHY)$ is already converting AI demand into profits, cash flow and shareholder returns, which makes its position particularly attractive. For me, SK hynix is the proven AI-memory winner, while Samsung is the potential turnaround story. If Samsung can regain major foundry custom

$Direxion Daily Semiconductors Bull 3x Shares(SOXL)$ I'm continuing to add to my SOXL position during this semiconductor pullback. I'm not trying to catch the exact bottom—I'm positioning for what I believe could be a near-term rebound. Technically, the pullback toward the 200-day EMA is important to me. This long-term trendline has historically acted as a key support area, and if buyers step in around here, the current weakness could turn into another higher-low rather than a deeper breakdown. Fundamentally, I still believe the semiconductor story remains strong. AI infrastructure, data centers, high-performance computing and memory demand continue to provide structural support for the sector. A correction doesn't necessarily change that lon

I didn’t attend the event myself, but I can already tell from this recap that it was a really fruitful and practical session. I especially liked the Property OTP analogy because it makes options much easier to understand and removes some of the fear around derivatives. The biggest takeaway for me is that options are not simply about predicting whether a stock goes up or down. Understanding Theta, IV, intrinsic and extrinsic value, and the different strategies is just as important. The IV Crush example around earnings was particularly useful because it shows how even getting the direction right doesn’t guarantee a profit. Overall, this recap gave me a much clearer picture of how options can be used for different market conditions, from generating income to protecting a portfolio. I didn’t

What stood out to me most is that the late-July tech selloff wasn’t simply about weak earnings. Big Tech delivered strong results, but the market was looking ahead at AI CapEx, rates and positioning. Strong earnings don’t always mean higher stock prices. I also found the AI CapEx comparison across Big Tech very useful. I’m increasingly focused on whether massive AI spending can actually translate into revenue, margins and sustainable returns, rather than simply chasing companies with the biggest spending plans. My biggest takeaway is the importance of “situational awareness.” Earnings, macro data, AI CapEx and market positioning can all interact at once. Understanding what the market has already priced in is just as important as understanding the fundamentals.

When I first started investing, the hottest stock everyone seemed to be talking about was $GameStop(GME)$ . It was impossible to ignore the incredible volatility, the retail-investor frenzy, and the short squeeze that turned the stock market into a global conversation. GME really opened my eyes to how powerful market sentiment, momentum, and retail participation can be. It was also a reminder that the stock market isn't always about fundamentals in the short term—emotion and crowd psychology can move prices dramatically. Looking back, GameStop was definitely one of the stocks that made my early investing journey memorable. 🚀📈 $GameStop(GME) was my answer! 🐯

I think the 25% residual-value guarantee is both the foundation and the biggest risk of the deal. It gives lenders confidence to finance massive GPU deployments, but the real question is whether these chips will still have meaningful value when the loans mature in 3–5 years. I’m encouraged by the fact that older $NVIDIA(NVDA)$ GPUs like the A100 are still being used, while CUDA keeps extending the useful life of existing hardware. But unlike cars or aircraft, there isn’t a mature secondary market for obsolete GPUs, so depreciation risk remains difficult to price. For me, the structure is bullish for AI infrastructure in the near term, but I wouldn’t treat the

Berkshire ending 14 straight quarters of net selling is definitely worth watching. It could be an early sign that the most cautious money in the market is starting to regain confidence. I don’t see it as an all-out bullish signal, but capital is clearly rotating back into AI, semiconductors and infrastructure. CoreWeave, SMCI and Lumentum also show that investors are increasingly looking beyond quarterly revenue and focusing on backlogs, long-term contracts and future cash flows. The big question now isn’t whether money is coming back — it’s which companies can actually turn that capital spending into sustainable profits. Valuations still matter, especially after the strong AI rally we’ve already seen. For me, this is a reason to stay invested but remain selective, rather than chase every

I think the market is moving early rather than simply getting it wrong. The $NVIDIA(NVDA)$ story has shifted from “how strong is AI demand?” to “where is the money funding that demand?” That uncertainty naturally hits leveraged optical names like $COHERENT(COHR)$ and $Lumentum(LITE)$ first. I don't think AI demand is broken yet. I’m watching actual orders, cash flow and funding much more closely, especially for companies like $

I would choose $Alphabet(GOOG)$ . Google Cloud’s strong growth, expanding margins and huge backlog show that its massive AI spending is starting to translate into real revenue. I also like the TPU story because it gives Alphabet another potential AI infrastructure advantage beyond relying entirely on Nvidia. For the downgrades, I can understand the argument on PLTR and CRWD. I still think both are excellent businesses, but when valuations become extremely demanding, even strong execution may not be enough to drive further upside. I’d rather wait for a meaningful pullback than chase them after such strong runs. Overall, my strategy is buy quality growth at a reasonable valuation, not quality at any price. GOOG looks more attractive to me today, wh

If I had to choose between Target and Estée Lauder after earnings, I’d lean toward $Estee Lauder(EL)$ . The 16% jump is significant, but the results suggest its turnaround may finally be gaining traction. Improving China demand and strong fragrance growth from Tom Ford and Le Labo give me more confidence in its recovery. I also like $Target(TGT)$ setup, with stronger traffic, digital sales growth and a raised full-year outlook. However, part of the EPS strength came from tariff refunds, so I’d like to see more evidence that earnings can continue improving without one-off benefits. For me, EL has more upside potential, while

I’m staying cautious on long-duration bonds for now. A 30-year yield above 5.3% is attractive, but oil prices, inflation concerns, weaker foreign demand and heavy Treasury supply could keep long-term yields elevated. I’d rather wait for more clarity from the Fed minutes and the Iran situation before locking in rates. For my portfolio, higher yields also mean pressure on high-duration growth and AI stocks because future earnings are discounted at a higher rate. However, I don’t see this as a reason to abandon AI or semiconductors. I’d continue DCA selectively and keep some cash ready for further pullbacks. For now, I prefer short-duration bonds or cash, while watching for signs that yields have peaked. If the 30-year moves significantly higher but inflation starts cooling, I’d be more comf

$Direxion Daily Semiconductors Bull 3x Shares(SOXL)$ I'm still averaging up my position in $SOXL$ despite the recent pullback and correction because I see it as a reset within the broader semiconductor uptrend, rather than a reason to abandon my thesis. The recent weakness has brought down some of the overheated sentiment around AI and semiconductors, but the underlying demand story remains strong. AI infrastructure, data centers, high-performance computing and memory continue to require enormous amounts of semiconductor capacity, and I believe the long-term cycle still has plenty of room to run. The correction is actually one of the reasons I'm more comfortable adding gradually. After the strong rally earlier, valuations and expectations had

$Palantir Technologies Inc.(PLTR)$ I continue to average up my position in $Palantir(PLTR)$ because I'm investing in the long-term AI story, not simply chasing the recent price momentum. Palantir has built a strong position at the intersection of AI, data analytics and enterprise software, with its platforms becoming increasingly important for companies and governments looking to turn AI into real-world applications. For me, the key is that Palantir is not just an AI "story" — it has an established business, recurring customers and a platform that can potentially scale significantly as AI adoption accelerates. Another reason I'm comfortable averaging up is the company's execution. Palantir continues to demonstrate strong demand for its AI cap

I’d pick A — a company I like that’s down 30% from its high. I’d rather take advantage of a meaningful pullback in a company whose fundamentals and long-term story remain intact than chase a stock simply because it’s making new highs. For me, names like $NVIDIA(NVDA)$ , $Tesla Motors(TSLA)$ and $Micron Technology(MU)$ can become especially interesting after a correction. A 30% drawdown doesn’t automatically mean the thesis is broken; sometimes it creates a much better risk/reward entry point,