Semiconductor

Xiaomi’s current downturn cannot be attributed solely to an “AI spending spree” narrative. Over the past year, the stock price fell steadily from a high of around HKD 60 in July 2025 to HKD 25.84 on June 11, 2026. What is truly difficult is the convergence of three factors: smartphone profits are squeezed by rising storage costs; the auto sector has moved from rapid volume growth to a stage of subsidy tapering and model switching; and AI investments have pushed the market’s patience for free cash flow further into the future.

When the A-share semiconductor and AI hardware chains surge rapidly, two extreme reactions tend to emerge: one type of person feels that missing out on gains (FOMO) is more painful than actually incurring losses, while another believes that excessive rises necessarily signal a bubble.

Both of these are too fast. In areas like semiconductors, computing power, optical modules, and storage, the industrial logic might be true. AI training and inference will indeed boost hardware demand, and domestic substitution has certainly provided narrative space and order opportunities for local companies. The problem is that just because the industrial logic holds true does not mean that the probability of investing in it now is good.

Similar market trends have occurred repeatedly in history: the liquor sector (Baijiu), new energy, pharmaceuticals, core asset grouping, and TMT. Each time, there was real logic behind it. When these sectors decline, it doesn’t necessarily mean the logic has disappeared; rather, the timing/rhythm between valuation, positioning, earnings realization, and liquidity was off.

In the previous article The end point of this semiconductor cycle is probably not in 2026, I presented my conclusion first, but deliberately did not dive too deep into the specific details of the financial reports.

What we are covering this time is the part that is most easily obscured by market sentiment: When semiconductors rise, everyone knows they are profitable; but what truly determines whether a cycle can be extended or which company can capitalize on high growth more thoroughly is often not the stock price, but rather the profit and loss statement, capital expenditure, and product investment direction during the trough.

If I must make a more specific judgment, as of May 13, 2026, I still do not pinpoint 2026 as the end of this upcycle. However, if I have to pick just one major player among the giants that is most worth watching, it would be SK hynix. Not because it hasn’t gone through a downturn—quite the opposite—but because it made the most representative strategic choices when things looked their worst in 2023.

My previous article covered the semiconductor cycle, and I feel like there’s a piece of background/context missing.

Your judgment/conclusion regarding this point—the overall direction is correct. Furthermore, I believe it is a prerequisite that is easiest to overlook when trying to understand this current semiconductor boom.

A more accurate way to put it is not that “all internet giants are fighting in the same field,” but rather: Large Models have, for the first time, brought together major players previously scattered across different domains—such as search, advertising, social media, e-commerce, office productivity, cloud computing, and content distribution—into direct competition within the same technical stack.

This technology stack includes models, computational power, inference, cloud, Agents, distribution gateways, and commercialization closed loops. Everyone’s original “moat” is different, but now we must all fill the same gap. Those who fail to do so will see their future search entry points, ad pricing, office suites, e-commerce conversion, and social traffic distribution rewritten by others.

Regarding this round of semiconductor trends, I temporarily do not see a peak in 2026.

If forced to give an initial judgment, as of May 12, 2026, I am more inclined to place the truly critical period between the second half of 2027 and the first half of 2028, rather than now. The core driver of this current uptrend—particularly in US listed storage and Korean semiconductors—is not a general recovery, but rather AI pulling HBM, DDR5, and enterprise SSD up simultaneously. If supply expansion fails, both prices and profits will rise together.

This also explains why companies like Micron, SK hynix, and Samsung seem to be “printing money” lately. The semiconductor cycle hasn’t vanished, but this time it is unlikely to collapse when demand first kicks in; rather, it is more likely to crash when capacity expansion finally catches up, and the market has already front-loaded two or three years’ worth of profit.

The most unusual aspect of this current AI market cycle is not that Nvidia has risen sharply, but that the increase in value has been transmitted throughout the entire industrial chain: first GPUs, then servers, switches, ASICs, HBM, and finally to NAND, hard drives, power, and data centers.

If it were just a concept, the market trend shouldn’t last this long. But saying that it has already formed a complete profit cycle might be premature.

I prefer to view it as a “bull market driven by certain expenditures”: cloud vendors and model companies are genuinely spending money, and upstream companies are indeed collecting revenue, which is why stocks rose first; however, terminal applications have not yet proven that these investments can reliably generate enough profit, meaning the risk of a bubble also exists.