CSOP Hang Seng Tech ETF (03033.HK) Down 1.32% After the Index Fell 11.73% in October

NewTimeSpace News: As of 9:52 on November 4, CSOP Hang Seng Tech ETF (03033.HK) fell 1.32% to a latest price of HK$3.748. The ETF has so far traded 374 million units today, with turnover of HK$1.402 billion and an average price of HK$3.754; its turnover rate is 2.538%. It has gained 1.52% week to date. The net asset value per unit is HK$3.7909, and assets under management stand at HK$55.792 billion. (Note: NAV and AUM are as of November 3; the week-to-date change is based on the October 30 close of HK$3.692.)

Several brokerages argued in their November strategy notes on November 4 that with the Hang Seng Tech Index down 11.73% in October and volatility in tech growth names widening, the market's focus is shifting from thematic expectations to earnings delivery as valuation pressure eases and overseas rate disruptions are absorbed; Hong Kong equities' performance will depend more on earnings improvement and valuation matching. Within the AI supply chain, attention has extended from capex scale to order growth, profitability and free cash flow. On November 4, the Hang Seng Index opened down 0.32% and the Hang Seng Tech Index down 0.5%.

CSOP Hang Seng Tech ETF (03033.HK) is a passive ETF under CSOP that closely tracks the Hang Seng Tech Index. Compiled by Hang Seng Indexes, the index reflects the performance of the 30 largest companies listed in Hong Kong that are classified under the industrials, consumer discretionary, healthcare, financials and information technology sectors and are highly relevant to the technology theme, weighted by free-float market capitalisation with an 8% cap on any single constituent. The product is managed by CSOP Asset Management Limited, with a management fee of 0.99% per year.

CICC believes AI has reached a critical juncture, drawing resources from the broader economy, with both China and the United States facing a balance between capex and returns. The key to AI's next move lies in model iteration and the delivery of new business models, with coding, agents and multimodality as the main iteration threads, while AI commercialisation is moving from tool trials to deep embedding in production processes.