Hang Seng slumped 2.6%

Strota Newsroom · Global Markets · session of 2026-10-05 · market close

Hang Seng closed at 23,972.29 on 2026-10-02, slumped 2.6% on the session and is -6.5% year-to-date. Here is what the market data shows.

Hong Kong's Hang Seng Index fell 2.6 per cent to close at 23,972.29 in its latest session, dated October 2. The drop left the index 14.29 per cent below its 52-week high of 27,968.09 and only 5.74 per cent above its 52-week low of 22,671.86. It closed below both its 50-day average of 25,279.81 and its 200-day average of 25,544.65.

The move capped a weak stretch. The index is down 5.29 per cent over the past month and 3.19 per cent over the week, though it remains 1.51 per cent higher over three months. So far this year it is down 6.47 per cent.

Other markets were mostly higher on their latest closes, which carry different dates. In the same October 2 session, the S&P 500 rose 0.73 per cent, the Nasdaq Composite 1.19 per cent and the Dow 0.49 per cent. European indices on that date were also up: the DAX 1.17 per cent, the Euro Stoxx 50 1.02 per cent, the CAC 40 0.79 per cent and the FTSE 100 0.32 per cent. The Nikkei, on a later close dated October 5, added 2.27 per cent, and the ASX 200 rose 0.44 per cent on the same date. Among Asian peers on October 2, the KOSPI rose 0.46 per cent and the TAIEX 0.25 per cent. India's Sensex and Nifty 50 closed lower on October 1, down 0.79 per cent and 0.88 per cent.

On the news, BBN Times described the fall as the steepest since March, with banks and technology shares sliding after a holiday. A futunn closing review said the index fell below the 24,000 mark as technology, large financials and mainland property names all declined. finance.biggo reported the index tumbling 2.6 per cent below 24,000 in its first October session, while a Moomoo midday note had earlier flagged a rising morning.

What the data does not establish is a single driver. It shows the size of the fall, where the index sits in its 52-week range and that the decline was broad, without attributing it to any one cause.

The numbers

Around the world (same session)

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How this article was made: Strota assembled the market data above (the index's price history, same-session peer-market moves and public headlines) and an AI model wrote the narrative strictly from that evidence — it is not permitted to add outside facts or numbers. Every figure comes from the underlying market/public data.