Microsoft And Google Report Thursday. Payback?

BofA 2H26 survey on AI with ~300 CIOs:

$Keppel DC Reit(AJBU.SG)

Context: Keppel DC REIT is still riding on the data centre growth story, but with interest rates, borrowing costs and valuation to consider, I don’t think can just buy and hold without looking at the price.

My trade: I decided to sell my position first and free up some cash. Nothing wrong with the company, just feel that taking profit now makes sense for my portfolio. If there’s a better entry later, then I’ll consider again.

Takeaway: Sometimes don’t need to squeeze every last cent out of a stock lah. 😂 Profit is profit, no need to be greedy. I rather secure my gains first and wait for the next opportunity than get too attached to one counter.

$Alphabet - C(GOOG.US)I just set a Sell If Touched order for Google shares at my target selling price of USD 385. I still believe Google has the potential to reach this level, as the company has a strong position in the technology industry and continues to develop its AI capabilities. For me, it’s more about timing than losing confidence in the company. Of course, the stock price may fluctuate along the way, so I’ll be patient and see how the market moves. Hopefully, my target price can be reached soon! 😊

The market rewarded $Meta Platforms(META.US) for spending more and punished $Tesla(TSLA.US) for spending less, and I think that comes down to proof. Meta's revenue grew 26% to a record 64.6 billion USD and its shares rose after hours even as it lifted its capex forecast to as much as 145 billion USD, so investors can see the ad business paying for the AI push. Tesla beat on earnings but its shares reversed after it cut its 2026 capex forecast to about 20 billion USD from over 25 billion, and they were down almost 5% before the open on Thursday. A spending cut at a company priced on robots and autonomy raises doubts about those ambitions, especially with the stock trading at roughly 195 times a simple earnings run rate. My takeaway is that heavy spending is forgiven when revenue backs it up, while a valuation built on future promises has little room for any sign of retreat.

I think Tesla and Meta’s earnings show that there is no single right approach to AI spending. $Tesla(TSLA.US) cutting its capital expenditure target to around $20 billion while delivering positive free cash flow is encouraging, especially as profits declined about 43%. To me, this suggests Elon Musk is trying to balance long-term investments with financial discipline while Tesla continues developing FSD, Robotaxi, Optimus and AI infrastructure. However, I still want to see these projects translate into sustainable revenue and profits rather than relying only on future promises.

$Meta Platforms(META.US), on the other hand, is raising its capital expenditure floor to $135 billion, supported by 26% revenue growth. I understand why Mark Zuckerberg is willing to spend aggressively, as AI could strengthen advertising performance and create new growth opportunities, but the key question is whether the returns can justify such massive investments. Personally, I remain bullish on the long-term AI trend, but I prefer to judge companies by cash flow, execution and returns on invested capital. I will continue holding my Tesla position with a long-term perspective, while staying disciplined and avoiding the temptation to chase excitement around AI spending.

$NVIDIA(NVDA.US)

Context:

NVDA is trading around $218 after briefly touching $222.

Beyond the AI stock rebound, NVIDIA’s Vera Rubin announcements at GTC Berlin and Google Cloud’s adoption plans stand out. They show NVIDIA expanding beyond GPUs into a broader AI computing ecosystem.

My Trade:

I’m still holding NVDA. Short-term price swings haven’t changed my long-term outlook.

My confidence comes from NVIDIA’s innovation and growing customer adoption, though competition and AI spending remain key risks.

Takeaway:

NVDA has taught me that patience comes from understanding what I own.

I focus more on real-world adoption than daily price movements. Product launches create excitement, but actual customer deployment builds lasting value.

$Alphabet - C(GOOG.US)Recently, I noticed that Google shares have been declining, mainly due to concerns about heavy AI spending, increasing competition, and whether these investments can generate sufficient returns in the future. However, I still believe Google has strong long-term potential because of its established search business, Google Cloud, and continuous development in AI technology. Although the share price may remain volatile in the short term, I hope the upcoming earnings results will provide more confidence to investors. For now, I will continue monitoring the market patiently instead of making any rushed decisions. 😊📈

An eight-day slide unwinds crowded leverage, reflecting AI capex anxiety rather than deteriorating demand fundamentals. With the quiet period limiting Fed commentary and forward earnings holding firm, disciplined buyers should capitalize on this valuation washouts before hyperscaler earnings validate ongoing infrastructure spending.

Where is the AI capex going?

$Microsoft(MSFT.US)

Background: Microsoft rose 4% last Friday and crashed through the resistance lines finally.

My trade: At $397, I'm not buying Microsoft as a cheap value stock. I'm paying for continued Azure/AI growth and the strength of the Microsoft 365 ecosystem.

Takeaway: I would hold the $397 position and let it compound.

The entry is good enough that I wouldn't be eager to sell simply because MSFT has already recovered. The target price is $600.

Software runs in the hardware. Hardware is necessary too. Though hardware has its lifespan, maintenance plays a part as well. Replace hardware may seem to be the best if already use it for many years. However, take care of it matters.

For me, this looks like more than a short-term rotation. With the 10-year Treasury above 5%, investors are becoming more selective toward companies with heavy capex and distant cash flows. That explains why semiconductors can face pressure even while long-term AI demand remains strong.

I also think software deserves more attention as AI monetization becomes easier to measure. Companies like PLTR and MSFT can potentially turn AI into higher revenue and free cash flow without the same infrastructure burden. The key question is shifting from whether AI makes money to which part of the AI stack captures the profits.

Personally, I would not simply sell SOXX and buy IGV after one sharp move. I still believe chips are essential to AI, so I prefer accumulating quality names gradually while watching rates, credit spreads, and earnings. For me, cash flow will increasingly separate the winners from the stories.