GF China Science And Technology Innovation Board Artificial Intelligence ETF (588760) Targets Third Consecutive Gain; Institutions: AI Drives Cost Reduction, Efficiency Improvement, and Industrial Restructuring

NewTimeSpace News - As of 09:51 on April 8, 2026, the GF Securities STAR AI ETF (588760) rose 4.82%, targeting its third consecutive gain, with its latest price reaching 0.74 yuan. Looking at a longer timeframe, as of April 7, 2026, the ETF has accumulated a gain of 1.29% over the past week. (The stocks listed above are solely index constituents and do not constitute specific investment recommendations.)

In terms of liquidity, the GF Securities STAR AI ETF recorded an intraday turnover rate of 3.2% and a trading volume of 75.5593 million yuan. Looking at a longer timeframe, as of April 7, the ETF's average daily trading volume reached 239 million yuan over the past year, ranking among the top 2 comparable funds.

Regarding fund size, the GF Securities STAR AI ETF has grown by 1.02 billion yuan over the past year, representing a significant increase and ranking 3rd among 11 comparable funds in terms of new asset inflows. (Data source: Wind)

In terms of fund shares, the GF Securities STAR AI ETF increased by 72 million shares over the past week, achieving substantial growth and ranking 2nd among 11 comparable funds in terms of new share additions. (Data source: Wind)

For capital flows, the GF Securities STAR AI ETF recorded a net outflow of 12.7914 million yuan in the latest session. Looking at a longer timeframe, over the past 21 trading days, 12 days saw net inflows, with a total of 317 million yuan attracted, representing an average daily net inflow of 15.0749 million yuan. (Data source: Wind)

Data indicates continued positioning by leveraged funds. The GF Securities STAR AI ETF recorded a margin purchase of 4.7673 million yuan in the latest session, with its latest margin balance reaching 99.2537 million yuan. (Data source: Wind)

As of April 7, the GF Securities STAR AI ETF has gained 47.48% over the past year, ranking among the top 2 comparable funds. In terms of return capability, as of April 7, 2026, since its inception, the ETF has achieved a maximum monthly return of 35.29%, a maximum consecutive rising period of 4 months, a maximum consecutive gain of 56.27%, a rising-to-falling month ratio of 8/6, an average monthly return of 10.91% during rising months, and a 100.00% probability of profit for historical 1-year holdings. As of April 7, 2026, the GF Securities STAR AI ETF has outperformed its benchmark by 0.28% in annualized returns over the past year, ranking among the top 2 of 6 comparable funds.

Regarding drawdown, as of April 7, 2026, the GF Securities STAR AI ETF's relative benchmark drawdown this year was 0.06%, representing the smallest drawdown among comparable funds.

In terms of fee structure, the GF Securities STAR AI ETF charges a management fee of 0.50% and a custody fee of 0.10%.

For tracking accuracy, as of April 7, 2026, the GF Securities STAR AI ETF's tracking error over the past month was 0.006%, achieving the highest tracking precision among comparable funds.

From a valuation perspective, the SSE STAR Market AI Index tracked by the ETF currently has a price-to-earnings ratio (PE-TTM) of only 124.13x, standing at the 14.57th percentile over the past year, meaning the valuation is lower than 85.43% of the time during the past year, indicating a historically low level.

The GF Securities STAR AI ETF closely tracks the SSE STAR Market AI Index, which selects 30 listed companies with relatively large market capitalizations providing basic resources, technology, and application support for artificial intelligence from the STAR Market as index constituents to reflect the overall performance of representative AI industry listed companies on the STAR Market.

Wanlian Securities noted that ByteDance, Alibaba, and Google concentrated on upgrading and releasing AI video and image generation models in early April, with technological breakthroughs focusing on three dimensions: generation quality, controllability, and cost efficiency. This round of intensive deployments marks AI video/image generation accelerating to become a new "infrastructure" for scenarios such as advertising and marketing, short videos, e-commerce content, and film and television creation, driving cost reduction and efficiency improvement in content production paradigms and industrial restructuring.

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