NewTimeSpace News:As of 14:21 on March 13, 2026, the CSI Medical and Medical Device Innovation Index (931484) rose 0.18%. Its component stocks saw varied gains, with Intco Medical up 15.56%, Zhejiang Medicine up 3.87%, Tebao Bio up 1.92%, Greatbatch Medical up 1.26% and Sinocell Tech up 0.89%. The Ping An CSI Medicine and Medical Device Innovation ETF(516820) rose 0.28% to a latest price of RMB 0.36. In the longer term, as of March 12, 2026, the ETF had a cumulative increase of 2.29% in the past week. (The stocks listed above are only index components and do not constitute any specific investment recommendation.)

In terms of liquidity, the Ping An CSI Medicine and Medical Device Innovation ETFrecorded an intraday turnover rate of 0.93% with a trading volume of RMB 17.2371 million. As of March 12, it had an average daily trading volume of RMB 51.4338 million in the past year.

In terms of scale, the latest scale of the Ping An CSI Medicine and Medical Device Innovation ETFreached RMB 1.843 billion. (Data source: Wind)

In terms of capital flows, the Ping An CSI Medicine and Medical Device Innovation ETFsaw a net capital outflow of RMB 8.6135 million on the latest trading day. Over the past 14 trading days, it has registered net inflows on 8 days, attracting a total of RMB 14.4159 million in capital with an average daily net inflow of RMB 1.0297 million. (Data source: Wind)

Data showed that leveraged funds have continued to build positions in the ETF. Its latest margin purchase volume stood at RMB 3.1345 million, with the latest margin balance reaching RMB 77.0509 million. (Data source: Wind)

As of March 12, the net asset value (NAV) of the Ping An CSI Medicine and Medical Device Innovation ETFhad risen 5.91% in the past year. In terms of earnings capacity, as of March 12, 2026, since its inception, the ETF has achieved a maximum monthly return of 27.10%, a longest streak of rising months of 3 months with a cumulative gain of 18.70% during the streak, and an average monthly return of 5.70% in rising months. As of March 12, 2026, the ETF had an annualized excess return of 2.05% over the benchmark in the past year.

In terms of drawdown, as of March 12, 2026, the ETF's maximum drawdown year-to-date was 8.94%, with a drawdown of 0.09% relative to the benchmark.

In terms of fees, the Ping An CSI Medicine and Medical Device Innovation ETFhas a management fee rate of 0.50% and a custodian fee rate of 0.10%.

In terms of tracking accuracy, as of March 12, 2026, the ETF had a tracking error of 0.030% in the past month.

From a valuation perspective, the latest price-to-earnings ratio (PE-TTM) of the CSI Medical and Medical Device Innovation Index, which is tracked by the Medical Innovation ETF, was only 26.68 times, at the 10.42% quantile of the past year. This means the valuation was lower than that in more than 89.58% of the time over the past year, standing at a historically low level.

The Ping An CSI Medicine and Medical Device Innovation ETFclosely tracks the CSI Medical and Medical Device Innovation Index. The index selects 30 securities of listed companies with sound profitability, certain growth potential and R&D innovation capabilities from the medical and health industry as its samples, reflecting the overall performance of securities of listed companies in the medical and medical device sector that feature both profitability and growth potential.

Data showed that as of February 27, 2026, the top 10 weight stocks of the CSI Medical and Medical Device Innovation Index (931484) were WuXi AppTec, Mindray Medical, Hengrui Medicine, Aier Eye Hospital, Pientzehuang, Zhejiang NHU, Huadong Medicine, Pharmaron Beijing, Elsie Biotech and Dong'e Ejiao, accounting for a total of 63.75% of the index weight. (The stocks listed above are only index components and do not constitute any specific investment recommendation.)

FOUNDER SECURITIES stated that traditional imaging equipment manufacturers are entering the AI diagnosis track through external mergers and acquisitions, and the "hardware equipment + intelligent algorithms" model is expected to become an effective path to break the charging bottleneck of AI diagnosis and accelerate its penetration in hospitals.

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