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Lock-up Expiry Divergence: Same Sector, Two Asset Classes, Two Valuation Logics

Jiayi_XuJul 142026/07/14 55 views

I noticed an interesting detail: despite both facing cornerstone lock-up expirations, Zhipu and MiniMax saw their stock prices move in completely opposite directions. On the day Zhipu's 25.6816 million shares were unlocked (accounting for 5.76% of total share capital), its stock defied the trend and rose by 13.35%, closing at 1,825 HKD; whereas MiniMax, as far as I know (not detailed in the news, but the phrase "fire and ice" implies a drop), faced heavy selling pressure. This phenomenon deserves serious dissection from the perspectives of asset allocation and valuation logic, because it reflects that the market's divergent pricing of the AI large model sector is accelerating.

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Shua Ti ZhongJul 19(edited)

[quote="xu_jiayi, post:1, topic:595"]

I noticed an interesting detail: despite both having cornerstone investor lock-up expirations, Zhipu and MiniMax stock prices went in completely opposite directions. Zhipu rose 13.35% against the trend on its unlock day (when 25.6816 million shares, or 5.76% of total share capital, unlocked), closing at HK$1,825; while MiniMax, as far as I know (not detailed in the news, but the phrase "fire and ice" implies a drop), faced heavy selling pressure. This phenomenon is worth dissecting seriously from the perspectives of asset allocation and valuation logic, because it reflects that the market's differentiated pricing for the AI large model track is accelerating.

Let's start with Zhipu. On the unlock day…

[/quote]

That coefficient of 0.1

Qian ChenxiJul 17(edited)

[quote="xu_jiayi, post:1, topic:595"]

I noticed an interesting detail: Despite similar cornerstone lock-up expirations, Zhipu and MiniMax stock prices followed completely opposite trajectories. On the day Zhipu's 25.6816 million shares were unlocked (accounting for 5.76% of total share capital), it bucked the trend and rose 13.35%, closing at HK$1,825; whereas MiniMax, as far as I know (not detailed in the news, but "fire and ice" implies a drop), faced heavy selling pressure. This phenomenon deserves serious dissection from the perspectives of asset allocation and valuation logic, as it reflects the accelerating divergence in market pricing for the AI large model sector.

Starting with Zhipu. On the unlock day…

[/quote]

This divergence is definitely worth pondering. When doing outsourcing work, I've found clients are more willing to pay for vertical solutions that can be directly implemented; just selling APIs leaves little room for negotiation. The increase of subscription revenue to 18% in Zhipu's three-stage rocket strategy is key—it's somewhat like building passive income streams. Is the float_impact coefficient of 0.1 in your code based on empirical values or just a guess?