The profitability of Chinese listed companies have surged significantly in the second quarter of 2026, pimarily driven by investment in artificial intelligence. This marks a sharp rebound from 2025 earnings weakness, despite continous pressure on China's equities.
In Q2 2026, mainland Chinese listed companies' profits climbed 25.7%, the strongest growth since 2021, according to Kobeissi letter. Additionally, this was the second consecutive quarter of growth after profits dropped by double digits in the fourth quarter of 2025.
Based on Wind data cited by China Securities Journal, 1,716 companies listed in Shanghai, Shenzhen and Beijing posted their first-half 2026 results as of August 23. These firms together reported 11.21 trillion yuan ($1.56 trillion) as revenue, a 11.51% jump from from the same quarter previous year. The combined net profit of these companies advanced 26.62% to 1.04 trillion yuan.
The rally was led by AI-linked companies, with earnings up 42% on Shenzhen's growth-focused ChiNext market and 370% on Shanghai's technology-focused STAR Market, significantly outpacing the broader market, Kobeissi letter.
The strong earnings recovery has yet to translate into market gains, with the CSI 300 declining 9% this quarter and the STAR 50 tanking 29%.
Why are Chinese equities lagging?
According to a report by Bloomberg, the earnings optimism may already be priced in. The STAR 50 Index jumped 76% in the quarter to June and the broader CSI 300 rallied 12%, raising the bar for further gains in the stock market.
The divergence also indicates a weak economy, with domestic demand being sluggish, the property sector underperforming and expectations for a major policy response from Beijing is very less. Additionally, the growth in earnings growth is concentrated in a certain of sectors, restraining the boost to the broader market.
Notably, strong earnings have not always translated into sustained gains, even for favoured companies such as memory-chip maker CXMT Corp. As AI-linked stocks are already near record valuations focus ihas now shifted towards whether the surge in AI spending can deliver expected results.
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