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.