ETF周报（20250714-20250718）-20250721

Report Industry Investment Rating - No relevant content provided 2. Core Viewpoints - The report analyzes the secondary - market performance of A - shares, overseas major broad - based indices, gold indices, and Nanhua Commodity Index from July 14 to July 18, 2025. It also examines the performance, fund flow, trading volume, margin trading, and new issuance of ETFs during the same period [1][2] 3. Summary by Directory 3.1 Secondary Market Overview - In the sample period, the GEM Index, Hang Seng Index, and CSI 2000 ranked high in weekly returns, at 3.17%, 2.84%, and 1.74% respectively. The PE valuation quantile of CSI 500 was the highest at 100.00%, while that of the Nikkei 225 was the lowest at 64.08% [9] - Among Shenwan primary industries, Communication, Medicine and Biology, and Automobile ranked high in returns, at 7.56%, 4.00%, and 3.28% respectively. Media, Real Estate, and Utilities ranked low, at - 2.24%, - 2.17%, and - 1.37% respectively. The industries with the highest valuation quantiles were Medicine and Biology, National Defense and Military Industry, and Steel, all at 100.00%. The industries with lower valuation quantiles were Agriculture, Forestry, Animal Husbandry and Fishery, Non - Banking Finance, and Household Appliances, at 15.70%, 34.71%, and 38.43% respectively [13] 3.2 ETF Product Overview 3.2.1 ETF Market Performance - QDII ETFs had the best average performance with a weighted average return of 3.52%, while Money Market ETFs had the worst with 0.01% [18] - ETFs related to Hong Kong stocks and ChiNext Innovation 50 performed well, with weighted average returns of 5.01% and 4.47% respectively. ETFs related to Japanese stocks and MSCI China A - share concept performed poorly, with - 0.02% and 1.02% respectively [18] - Among industry - sector ETFs, Biomedical ETFs had the best performance with a weighted average return of 4.94%, while Financial Real Estate ETFs had the worst at - 0.86% [21] - Among theme - based ETFs, Innovative Drug and Artificial Intelligence ETFs performed well, with weighted average returns of 9.98% and 6.51% respectively. Non - Banking and Bank ETFs ranked low, at - 0.80% and - 0.76% respectively [21] 3.2.2 ETF Fund Inflow and Outflow - From the perspective of different categories of ETFs, Industry - Theme ETFs had the largest net inflow of 17.28 billion yuan, while Broad - Based ETFs had the smallest at - 29.709 billion yuan [25] - From the perspective of ETF - tracking indices and their constituent stocks' listing boards, Hong Kong Stock ETFs had the largest net inflow of 10.064 billion yuan, while CSI 300 ETFs had the smallest at - 8.841 billion yuan [25] - From the industry - sector perspective, Financial Real Estate sector ETFs had the largest net inflow of 9.919 billion yuan, while Biomedical sector ETFs had the smallest at - 2.607 billion yuan [26] - From the theme perspective, Non - Banking and Chip Semiconductor ETFs had the largest net inflows of 8.229 billion and 4.319 billion yuan respectively. Artificial Intelligence and Innovative Drug ETFs had the smallest at - 3.102 billion and - 0.797 billion yuan respectively [26] 3.2.3 ETF Trading Volume - From the perspective of different categories of ETFs, QDII ETFs had the largest increase in the average daily trading volume change rate at 18.95%, while Commodity ETFs had the largest decrease at - 21.54% [31] - From the perspective of ETF - tracking indices and their constituent stocks' listing boards, ChiNext Innovation 50 ETFs had the largest increase in the average daily trading volume change rate at 26.92%, while CSI 300 had the largest decrease at - 18.76% [34] - From the industry - sector perspective, the Technology sector had the largest increase in the average daily trading volume change rate at 17.38%, while the Financial Real Estate sector had the largest decrease at - 10.68% [35] - From the theme perspective, Non - Banking and Innovative Drug ETFs had the largest average daily trading volumes in the past 5 days, at 18.604 billion and 9.440 billion yuan respectively. Artificial Intelligence and Robot ETFs had the largest increases in the average daily trading volume change rate, at 41.53% and 34.15% respectively. Non - Banking and Low - Carbon Environmental Protection ETFs had the largest decreases at - 11.87% and - 7.82% respectively [39] 3.2.4 ETF Margin Trading - In the sample period, the net margin purchase of all equity ETFs was - 927 million yuan, and the net short - selling was - 207 million yuan. Bosera Science and Technology Innovation Board Artificial Intelligence ETF had the largest net margin purchase, and Fullgoal CSI A500 ETF had the largest net short - selling [43] 3.2.5 ETF New Issuance and Listing - In the sample period, 10 funds were established and 12 funds were listed [45]