【导读】 11 月 21 日股票 ETF 市场净流入超 400 亿元，资金持续加仓 ETF 中国基金报记者 王思文 11 月 21 日（上周五）， A 股三大股指大幅回调，创业板指跌超 4% ，深证成指跌 3.41% ，上证指数跌 2.45% 。市场震荡回调，股票 ETF 迎来资金 " 抄底加仓 " 。 当日股票 ETF 资金净流入超 400 亿元。其中宽基 ETF 、人工智能 ETF 、券商 ETF 为 " 吸金 " 大户。 宽基板块获大举加仓 Wind 数据显示，截至 11 月 21 日，全市场 1262 只股票 ETF （含跨境 ETF ）总规模为 4.47 万亿元。规模缩水主要受大盘下跌影响。 记者按照区间成交均价测算发现， 11 月 21 日股票 ETF 整体净流入资金高达 407.57 亿元， " 抄底资金 " 逢低加仓。 宽基板块 " 吸金 " 十分显著。具体来看，跟踪沪深 300 指数的 ETF 单日净流入金额达 48.9 亿元、跟踪中证 500 指数的 ETF 净流入金 额达 39 亿元、跟踪科创板 50 指数的 ETF 净流入金额达 38.6 亿元、跟踪创业板指数的 ETF 净流入金额达 ...

证券ETF（512880）跟踪的是证券公司指数（399975），该指数从沪深市场中选取业务与证券市场紧密 相关的上市公司证券作为指数样本，涵盖经纪、投行、自营等业务领域，以反映证券行业相关上市公司 证券的整体表现。该指数具有较高的行业集中度和周期性特征，能够较好地体现证券行业的市场走势。 平安证券指出，证券行业近期市场景气度改善、交投活跃度维持高位，板块从估值到业绩均具备β属 性，全面受益。长期看资本市场新一轮改革周期开启，券商仍有较大发展增量空间。 （文章来源：每日经济新闻） 信达证券指出，金融整体估值偏低，牛市概率上升，非银金融的业绩弹性大概率存在。后续伴随着居民 资金加速流入，非银金融获得超额收益的确定性较高。证券板块受益于牛市的Beta效应，业绩可能有更 大弹性。监管机构鼓励ETF发展、鼓励上市公司市值管理、鼓励长期资金入市，这天然有利于证券板 块，可能会是这一轮牛市的重要暗线。 ...

债权类ETF成资金避风港。 作者 | 市值风云基金研究部 编辑 | 小白 各位老铁大家好，这里是市值风云基金研究部ETF栏目，会在每周末发布ETF基金最新的市场数据和相应指数的估值数据。今天为第八十八期。 周评总共分为3大榜单。 行业中，光伏产业大跌11.3%，领跌两市，新能源汽车大跌8.3%，港股通互联网、国证芯片、中证钢铁、有色金属、创新药等板块跌超6%。 而中证银行、中证消费、中证军工、中证传媒、家用电器相对抗跌。 下跌并不可怕，我们得留有子弹抄底。从市盈率和市净率估值水平，各大指数基本上都有显著下降，下周如果继续下跌，或许是给抄底的机会。 指数估值天梯主要发布指数的ROE、PE和PB值，当前位置与近十年相比处于低估或高估，并且提供指数当前处于历史的分位数据。 ETF上涨"英雄"榜主要发布当周规模大于5亿元的ETF的涨幅前二十名。 份额增幅榜主要看当周规模超5亿元的ETF份额增加幅度前二十名。 指数估值"天梯"榜 本周市场大跌，投资者一片哀嚎。创业板指大跌超6%，领跌宽基指数，中证500、中证1000和科创50均跌逾5%。 | | | | | | 重要行业指数估值"天梯" 榜第八十八期(2025.11. ...

点评：龙头家电ETF（159730）今日上午涨幅达到0.09%，该ETF规模为0.33亿份，半日成交金额为560.69万元，其追踪的是国证龙头家电指数。 国证龙头家电指数反映沪深北交易所中家电行业优质上市公司的市场表现。该指数将权重更多地配置在细分领域的龙头企业中，如清洁电器、厨房电器以及 家电零部件逆变器等细分领域。 | 代码 | 名称 | 现价(元) | 涨幅 (%) | 总金 | | --- | --- | --- | --- | --- | | 512880 | 证券ETF | 1.186 | -2.55 | 24. | | 588200 | 科创芯片ETF | 2.162 | -3.44 | 22. | | 512000 | 券商ETF | 0.566 | -2.58 | 11. | | 515880 | 通信ETF | 2.479 | -4.58 | 10. | | 562500 | 机器人ETF | 0.933 | -1.27 | 10. | | 512480 | 半导体ETF | 1.334 | -3.26 | 10. | | 159755 | 电池ETF | 1.027 | -4.91 | ...

【导读】昨日股票ETF资金净流入达90亿元，本周以来"吸金"近285亿元 11月20日，股票ETF整体资金净流入达90亿元，港股相关ETF资金净流入居前，多只沪深300ETF资金净流出居前。 中国银河证券基金研究中心数据显示，本周以来（11月17日—11月20日），股票ETF"越跌越买"，四个交易日合计"吸金"近 285亿元。 华夏基金ETF方面，11月20日，科创50ETF和恒生科技指数ETF单日净流入居前，分别达7.59亿元和7.06亿元；最新规模分 别达718.43亿元和464.9亿元，对应跟踪指数近一月日均成交额分别为41.75亿元和47.08亿元。此外，恒生互联网ETF资金净 流入4.63亿元，中证1000ETF和基准国债ETF分别净流入3.88亿元和2.26亿元。 相关ETF资金净流入居前 从单日资金净流入排行看，中证500ETF、科创50ETF、中证1000ETF等宽基ETF成为"吸金"主力，恒生科技ETF、中概互联 网ETF、恒生互联网ETF等港股相关ETF资金净流入居前。 | | | 11月20日资金净流入居前的股票ETF一览 | | | | | --- | --- | --- | --- ...

11月20日早盘，A股三大股指集体高开，上证指数开盘报3960.7点，涨0.35%；深证成指开盘报13215.07点，涨1.03%；创业板指开盘报3131.84点，涨 1.79%。截至发稿，A股三大股指震荡调整，上证指数跌0.09%，深证成指跌0.28%，创业板指跌0.45%。 中金公司拟换股吸收合并东兴证券、信达证券，英伟达第三财季业绩以及第四财季业绩指引均超市场预期，碳酸锂期货主力合约突破10万元/吨…… 这是市场今天关注度较高的几个消息。不过，A股上午开盘后，市场讨论最多的是中国银行。 中国银行上午上涨5.17%，盘中股价再创历史新高，最新市值突破2万亿元，为2.03万亿元，目前四大行的市值均超2万亿元。工商银行上涨1.58%，盘中股 价亦创历史新高；建设银行上涨4.73%，邮储银行上涨3.84%。证券ETF开盘大涨近2%。 券商整合提速 中金公司发布的公告称， 公司A股股票于2025年11月20日开市时起停牌，预计停牌时间不超过25个交易日。 | 证券代码 证券简称 停复牌类型 停牌起始日 停牌期间 停牌终止日 复牌日 | | --- | | ୧01992 2025/11/20 中金公司 Ａ股 停牌 ...

ETF成交方面，房地产ETF（512200）成交额环比增长255%。期指持仓方面，IM合约空头加仓数量较多，IF合约多头加仓数量较多。 龙虎榜方面，航天发展走出5连板， 获一家一线游资席位（中国银河大连黄河路）买入1.26亿， 遭三家一线游资（国泰海通证券上海 新闸路、东亚前海证券上海分公司、国泰海通证券成都北一环路）分别卖出1.88亿、1.09亿、0.93亿。多氟多遭深股通卖出2亿，遭中 金公司上海分公司席位卖出8447万，同时遭一家机构卖出6517万。 一、沪深股通前十大成交 今日沪股通总成交金额为884.40亿，深股通总成交金额为1036.15亿。 | | 沪股道( | 11月20日 | ) | | | --- | --- | --- | --- | --- | | 排名 | 股票代码 | 股票名称 | | 成交金额(亿元) | | 1 | 601138 | 工业富联 | | 14.59 | | 2 | 601600 | 中国铝V | | 9.42 | | 3 | 603986 | 兆易创新 | | 9.20 | | 4 | 600519 | 贵州茅台 | | 8.87 | | 5 | 601899 | ...

Market Overview - The market experienced fluctuations with a total trading volume of 1.71 trillion yuan, a decrease of 177 billion yuan from the previous trading day. The Shanghai Composite Index fell by 0.4%, the Shenzhen Component Index by 0.76%, and the ChiNext Index by 1.12% [1] Sector Performance - The computing power sector was active in trading, while sectors such as banking and building materials saw gains. Conversely, coal and electricity sectors faced pressure [1] Computing Power Insights - Despite the active trading in the computing power sector, many stocks opened high but closed lower. The main catalyst was NVIDIA's quarterly report, which showed revenue of $57 billion, a year-over-year increase of 62% and a quarter-over-quarter increase of 22%. The data center revenue was $51.2 billion, exceeding market expectations [2] Mergers and Acquisitions in Securities Industry - The securities industry continues to see mergers, with China International Capital Corporation planning to absorb Dongxing Securities and Xinda Securities through A-share issuance. If successful, the combined assets of the three firms will reach 1,009.583 billion yuan, with revenues of 27.39 billion yuan and net profits of 9.52 billion yuan [3] Future Outlook - The overall market sentiment remains optimistic for the upcoming year, driven by factors such as capital market reforms and policies aimed at stabilizing growth. Investors are encouraged to maintain confidence in the market [1]

Core Viewpoint - On November 12, the stock ETF saw a net inflow of 91.6 billion yuan, with popular thematic ETFs in sectors like securities, chemicals, and insurance leading the inflow, while broad-based ETFs like the SSE 50 Index and ChiNext 50 Index experienced significant outflows [2][5][10]. Group 1: Market Overview - The market opened slightly lower and experienced fluctuations, with sectors such as insurance, pharmaceuticals, and oil showing gains, while sectors like cultivated diamonds, photovoltaics, and controllable nuclear fusion faced declines [4]. - The overall scale of stock ETFs reached 4.64 trillion yuan, with thematic ETFs related to the Hong Kong market seeing substantial inflows [5]. Group 2: Fund Inflows and Outflows - The top inflowing ETFs included the Sci-Tech 50 ETF with a net inflow of 12.86 billion yuan, followed by the Securities ETF and Chemical ETF with inflows of 5.77 billion yuan and 4.43 billion yuan, respectively [9]. - Conversely, the SSE 50 ETF led the outflows with a net outflow of 8.37 billion yuan, followed by the Coal ETF and ChiNext 50 ETF with outflows of 3.37 billion yuan and 2.94 billion yuan, respectively [10]. Group 3: Fund Company Performance - E Fund's ETFs saw a net inflow of 12.5 billion yuan, with a year-to-date increase of 224.42 billion yuan [5]. - Huaxia Fund's Sci-Tech 50 ETF and Free Cash Flow ETF also reported significant inflows of 12.86 billion yuan and 2.4 billion yuan, respectively [6]. Group 4: Future Market Outlook - The market is expected to maintain rapid rotation of hotspots in the short term, particularly in the technology sector, especially AI hardware, due to high cumulative gains and fast institutional positioning [10]. - The ongoing state-owned enterprise reforms are anticipated to lead to valuation restructuring, with a favorable environment for dividend strategies in a low-interest-rate context [11].

Quantitative Models and Construction Methods 1. **Model Name**: Industry Crowding Monitoring Model **Model Construction Idea**: This model is designed to monitor the crowding levels of industries on a daily basis, specifically for the CSI Level-1 Industry Index. It identifies industries with high or low crowding levels to provide actionable insights. [3] **Model Construction Process**: The model calculates the crowding levels of industries by analyzing daily fund flows and other relevant metrics. It ranks industries based on their crowding levels, highlighting those with significant changes or extreme values. For example, the previous trading day showed high crowding levels in power equipment, basic chemicals, and environmental protection, while industries like computers, automobiles, and non-bank financials had lower crowding levels. [3] **Model Evaluation**: The model effectively identifies industries with significant crowding changes, providing valuable insights for fund allocation and risk management. [3] 2. **Model Name**: Premium Rate Z-Score Model **Model Construction Idea**: This model is used to screen ETF products for potential arbitrage opportunities by calculating the Z-score of their premium rates. [4] **Model Construction Process**: The model employs a rolling calculation of the Z-score for the premium rates of ETF products. A high Z-score indicates a potential arbitrage opportunity, while a low Z-score may signal a risk of price correction. [4] **Model Evaluation**: The model provides a systematic approach to identify ETFs with potential arbitrage opportunities, but it also warns of potential price correction risks. [4] --- Model Backtesting Results 1. **Industry Crowding Monitoring Model**: No specific numerical backtesting results were provided in the report. [3] 2. **Premium Rate Z-Score Model**: No specific numerical backtesting results were provided in the report. [4] --- Quantitative Factors and Construction Methods No specific quantitative factors were explicitly mentioned or constructed in the report. --- Factor Backtesting Results No specific backtesting results for factors were provided in the report.