Reasons for Hynix’s sharp plunge: profit expectations were downgraded—does it still warrant a high-elasticity valuation?

TL;DR

· Citing a KIS report, a Korean media outlet says SK hynix’s forward profit forecast was cut, but the target price remains unchanged.

· Divergence in the market is focused on how much profit upside long-term HBM supply contracts will cap.

· Related underlying assets: SK hynix, Samsung Electronics, Micron, NVIDIA, KOSPI chip stocks chain.

KIS’s adjustment to its earnings model for SK hynix is prompting the market to re-evaluate the pricing foundation for AI memory trades. According to a Korean media report on July 13 citing a KIS report, SK hynix’s profits could come in below second-quarter consensus. The reasoning points to long-term pricing and supply agreements rather than weakening AI demand.

This is actually not a demand peak. KIS’s core change is not a bearish view on HBM (high-bandwidth memory) demand; rather, it believes that the way future profits will be realized needs to be re-estimated. As conveyed in the media’s cited figures, KIS cut SK hynix’s 2026 and 2027 operating profit forecasts while maintaining a 3.8 million won target price.

For investors, the question is no longer whether SK hynix can keep making money, but whether it can continue to raise profits as it did under the earlier model. AI memory remains scarce, but the scarcity premium may be getting written into pricing and capacity planning ahead of time through multi-year contracts.

Profit downgrades do not point to a demand collapse

The contradiction in this KIS adjustment is that lowered profit forecasts coexist with still-strong demand. Per the report cited by the media, KIS lowered SK hynix’s 2026 and 2027 operating profit forecasts by 9% and 11%, respectively. The second-quarter revenue estimate is 80.9 trillion won, the operating profit estimate is 60.4 trillion won, and the operating margin is close to 75%.

These figures still represent a high profitability level, and they are only broker estimates—not results officially disclosed by the company. In SK hynix’s already disclosed 2026 fiscal year Q1 results (using the same reporting basis), revenue was 52.5763 trillion won, operating profit was 37.6103 trillion won, and the operating margin was 72%.

So, this adjustment looks more like pulling an overly steep slope of forward profits back to reality, rather than concluding that the company has lost the ability to earn. Part of the market’s prior pricing came from the idea of “it can keep beating expectations,” and KIS believes that portion needs to be discounted.

Share-price pressure also can’t be attributed to just one report. A “profit downside” headline triggers selling pressure. AI chip trading itself is already crowded, and investors are starting to re-understand HBM long-contract pricing mechanics. The KIS report provides a clear explanation, but it is not the only reason.

Long contracts rewrite scarcity into cash flow

Long-term supply contracts can be understood as chipmakers and major customers agreeing in advance on the supply quantities and pricing framework for the coming years. For AI data centers, HBM is a key companion to compute hardware such as NVIDIA GPUs. Customers are willing to lock in volumes early to avoid having compute expansion constrained by memory supply.

This would change the industry’s historical cycle logic. Traditional memory profits have been highly dependent on price volatility: when demand is strong, spot prices rise quickly and manufacturers’ profits get amplified. When supply is in excess, prices fall and profitability shrinks quickly.

If the industry shifts to 3- to 5-year long-term contracts, manufacturers gain more stable orders, capacity utilization, and cash flow. The trade-off is that even if spot prices continue to rise in the future, the additional price-hike upside that firms can capture may be smoothed by contract terms.

This does not mean long-term contracts necessarily suppress all profits. Contract terms are not fully disclosed, including whether there is price elasticity, whether prices track spot prices, and whether there are advance payments or price protection—these depend on the company’s subsequent disclosures. But as long as some profit elasticity is partially locked in, analysts would likely cut their earlier, overly aggressive forward earnings assumptions.

Optimists trade demand; KIS trades elasticity

More optimistic institutions are still looking at a supercycle for AI memory. NH Investment & Securities raised its SK hynix target price to 4.1 million won in early July and expects 2026 and 2027 operating profits to be 289.4 trillion won and 470 trillion won, respectively. KB also raised its target price to 4.2 million won, emphasizing AI investment and memory shortages.

Company management’s tone has also been relatively strong. As reported by Reuters on July 10, SK hynix CEO Kwak Noh-jung expects that from a supply perspective, 2027 could be the tightest year, and customer demand may remain higher than the company’s supply capacity even after 2030.

These views do not entirely conflict with KIS. Optimists are discussing the demand curve and the industry supply-demand gap, while KIS is discussing how demand flows into the earnings-per-share model. The former asks “can it sell well?” The latter asks “if it sells well, can it still translate into profit upgrades?”

This distinction will directly affect valuation. Previously, the market was willing to pay a higher premium for SK hynix because it had both demand certainty and profit elasticity. Now long-term contracts increase certainty but may weaken elasticity. The market has to decide again how much premium should be paid for earnings visibility, and also how much premium should be subtracted from the assumption of infinitely rising profits.

The valuation anchor shifts from explosiveness to sustainability

SK hynix has not fallen behind in the AI chain. On the contrary, precisely because its position in HBM supply is important enough, major customers have even more need to lock in future capacity through long-term contracts.

But stock pricing is not only about whether the company is strong; it also includes whether that strength has already been reflected in the price. If the stock price has already priced in years of high growth and continual profit upgrades, then “realizing” the earnings model can trigger a sharp pullback.

This drop looks more like a change in the language of valuation. The market previously traded on “the scarcer the AI memory, the easier it is for prices to rise.” Now it needs to add another constraint: the more critical AI memory is, the more likely it will be locked in by long-term contracts.

For SK hynix, this is an upgrade to its business model and also a kind of valuation constraint. Long-term contracts reduce the industry’s historically severe cyclical volatility in memory, making future cash flows more predictable. But the market can’t simply equate spot shortages with endlessly increasing profit upgrades anymore.

Contract elasticity determines the boundary for the pullback

The key variable afterward is how demand flows into the income statement. If the company’s formal Q2 results come close to KIS’s estimates, and if the company confirms in its guidance that long-term contracts will smooth future price increases, the market may re-rate SK hynix from a high-elasticity growth stock to a high-certainty cyclical leader. Valuation may not collapse, but the premium structure will change.

If contract terms are more elastic than the market expects, or if higher HBM4 pricing is enough to offset the smoothing effect of long-term contracts, then this round of profit downgrades may just be a conservative calibration. Conversely, if Samsung and Micron ramp up supply faster, shortages in 2027 could be less than expected, and the downside protection provided by long-term contracts may not support the prior high valuation.

The test of this pullback is not whether investors still believe in AI memory, but which kind of AI memory company they are willing to pay for: paying a high multiple for spot-price elasticity, or paying a steadier premium for sustainable high profits locked in by multi-year contracts.

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