Investment

Bottom line first.

As of May 20, 2026, the strength of A-shares and the weakness of Hang Seng Tech are not due to one asset pool having lagging components; rather, it is a divergence between two sets of pricing logics. On May 20, 2026, the Shanghai Composite Index closed at 4162.19 points, still fluctuating near 4200; meanwhile, on its most recently available closing date of May 19, 2026, the Hang Seng Tech Index closed at 4857.46 points, which is still short of the phase historical high point of 10945.22 recorded on February 17, 2021, by 55.6%.

If your statement that the “CSI 300 ETF has matched its historical peak” refers to the most common 510300, the closing price I captured on 2026-05-20 was 4.871. This still represents about a 16.1% drawdown from the 5.807 recorded on 2021-02-10, and has not reached an all-time high. It is highly likely that various calculation bases were mixed here: Price, Net Asset Value (NAV), Adjusted NAV, Total Return Index. They look like they are the same thing, but they actually are not.

Allow me to correct a name. The “China Golden Dragon Fish Index” you mentioned usually refers to the Nasdaq Gold Dragon China Index, whose English name is Nasdaq Golden Dragon China Index, not “Golden Dragon Fish.”

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.

Regarding this problem/issue from Futu, I will state the conclusion first.

Futu Securities currently defaults to displaying cost-averaging, which is not what many people understand as simply calculating an average based only on buys and ignoring sells. Extending this concept further, Hong Kong brokers do not have a unified default methodology. If it is a holdings page aimed at Chinese retail investors, common display methods include cost-averaging, average cost, and breakeven price (or principal protection price). However, if the broker is an international firm like IBKR that places more emphasis on tax lots and statement consistency, FIFO (First-In, First-Out) is generally the default method.

When discussing domestic brokerage firms, if we refer to the most common field in A-share trading clients—the “Cost Price/Holding Cost Price”—it is more commonly focused on the diluted cost basis or break-even price, rather than simply the average purchase price. This is just because different brokerages do not have standardized naming conventions; some call it “holding cost,” others call it “diluted cost,” and some provide a separate figure for the “average purchase price.”

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.

Wuliangye’s performance fluctuation this time was not merely an ordinary dip; it directly disrupted the long-held unspoken norms within the baijiu industry. According to its 2025 annual report, the company reported full-year revenue of 40.529 billion yuan and net profit attributable to owners of 8.954 billion yuan. What is even more striking is that the company also conducted prior accounting error corrections for the first quarter, half year, and third quarter of 2025. Simply put, many figures from 2025 that initially looked impressive were later recalculated.

My judgment on this matter is straightforward: It’s not simply an “earnings crash,” but rather Wuliangye telling the market that their past approach of relying on channel pressure and reporting through future reserves can no longer be sustained.

I bought 006327 today on Alipay. I thought I would place the order before 3 PM, but what I received was based on “today’s Hang Seng Tech closing price.” The profit displayed on the page didn’t update for ages, and confirming the shares was also delayed. My first reaction was sheer shock: how is this thing actually settled/transacted? And why do I have to wait another two days?

To be honest, this misunderstanding is extremely common. Alipay has made buying and selling over-the-counter (OTC) funds look too much like placing stock orders, but fundamentally, there are two pitfalls in this matter. First, 006327 is absolutely not the Hang Seng Tech Index Fund. Second, when you buy a fund through OTC channels, the price you get is not based on an index’s real-time closing point, but rather the Net Asset Value (NAV) calculated by the fund company for that specific day. Furthermore, coupled with the