Group 1 - The public fund investment strategy shows robust growth in both scale and number, with active equity funds achieving an average return of 29.69% in 2025, outperforming major indices [2][23][27] - The top three sectors for active equity fund holdings are technology, manufacturing, and cyclical industries, indicating a strong focus on growth-oriented sectors [2][28] - The market outlook for 2026 suggests continued structural opportunities in A-shares, with technology growth remaining a key theme, while Hong Kong stocks are seen as undervalued [2][3] Group 2 - The index fund market has reached a historical high in both scale and number, with total assets amounting to 6.14 trillion yuan, reflecting a significant increase of 32.27% from the previous year [2][37][40] - The ETF segment dominates the index fund market, accounting for 76.10% of total assets, with a notable increase in industry-themed ETFs [2][38][40] - The performance of thematic funds, particularly in technology, has been outstanding, with technology-themed funds achieving an average return of 44.06% in 2025 [2][27][28]

估值有支撑，关注"更高阶"低估 证券研究报告 固收定期报告 / 2025.11.26 核心观点 相关报告 1. 《城投 2026，风偏分化？》 2025- 11-25 2. 《2026 年度策略：经济 K 型复苏，股债 K 型交易》 2025-11-24 3. 《信用 | 年末或有一定波动 》 2025- 11-23 请阅读最后一页的重要声明！ 分析师 孙彬彬 SAC 证书编号：S0160525020001 sunbb@ctsec.com 分析师 隋修平 SAC 证书编号：S0160525020003 suixp@ctsec.com 分析师 李浩时 SAC 证书编号：S0160525080002 lihs@ctsec.com 联系人 郑惠文 zhenghw01@ctsec.com 联系人 柳婧舒 liujs@ctsec.com ❖ 2026 推动转债走强的"固收资产荒"以及"权益高景气"或延续。一 方面，转债整体股性处于历史高点。基于我们 2026 年年度策略的观点，我们 认为 2026 年股债双牛依然可以期待，权益有较大的想象空间，强权益或成为 2026 年转债表现最重要的支撑。另一方面，结合长端利率保持低 ...

Quantitative Models and Construction Methods 1. Model Name: Diffusion Index Model - **Model Construction Idea**: The model is based on the principle of price momentum, aiming to capture upward trends in industries and sectors[22][23] - **Model Construction Process**: The diffusion index is calculated for each industry based on its price momentum. The model ranks industries by their diffusion index values and selects the top-performing industries for portfolio allocation. The model has been tracking out-of-sample performance since 2021, with adjustments made monthly or weekly based on updated diffusion index rankings[22][23] - **Model Evaluation**: The model has shown strong performance in capturing industry trends during momentum-driven markets but struggles during market reversals[22][36] 2. Model Name: GRU Factor Model - **Model Construction Idea**: This model leverages minute-level price and volume data processed through a GRU (Gated Recurrent Unit) deep learning network to generate industry factors for rotation strategies[37] - **Model Construction Process**: The GRU model uses historical price and volume data as input to train a deep learning network. The network identifies patterns and generates factors that are used to rank industries. The top-ranked industries are selected for portfolio allocation. The model is updated weekly to reflect changes in the rankings[30][31][37] - **Model Evaluation**: The GRU model performs well in short-term trading environments but has shown limited effectiveness in long-term scenarios. It is also sensitive to extreme market conditions[37] --- Backtesting Results of Models 1. Diffusion Index Model - **Weekly Average Return**: -5.50% - **Excess Return over Equal-Weighted CSI First-Level Industry Index**: -0.42% - **November-to-Date Excess Return**: -1.13% - **Year-to-Date Excess Return**: 1.22%[26][22][23] 2. GRU Factor Model - **Weekly Average Return**: -4.71% - **Excess Return over Equal-Weighted CSI First-Level Industry Index**: 0.35% - **November-to-Date Excess Return**: 2.92% - **Year-to-Date Excess Return**: -2.74%[35][30][31] --- Quantitative Factors and Construction Methods 1. Factor Name: Diffusion Index - **Factor Construction Idea**: The diffusion index measures the momentum of industries by analyzing price trends and ranks industries based on their momentum[22][23] - **Factor Construction Process**: The diffusion index is calculated for each industry using price momentum data. Industries are ranked based on their diffusion index values, and the top-ranked industries are selected for portfolio allocation. The index is updated weekly or monthly to reflect changes in industry momentum[22][23] - **Factor Evaluation**: The factor effectively captures upward trends in industries but may underperform during market reversals[22][36] 2. Factor Name: GRU Industry Factor - **Factor Construction Idea**: The GRU industry factor is derived from minute-level price and volume data processed through a GRU deep learning network to identify patterns and rank industries[37] - **Factor Construction Process**: The GRU model processes historical price and volume data through a deep learning network. The network generates factors that are used to rank industries. The top-ranked industries are selected for portfolio allocation, with updates made weekly[30][31][37] - **Factor Evaluation**: The factor is effective in short-term trading environments but less so in long-term scenarios. It is also sensitive to extreme market conditions[37] --- Backtesting Results of Factors 1. Diffusion Index Factor - **Weekly Average Return**: -5.50% - **Excess Return over Equal-Weighted CSI First-Level Industry Index**: -0.42% - **November-to-Date Excess Return**: -1.13% - **Year-to-Date Excess Return**: 1.22%[26][22][23] 2. GRU Industry Factor - **Weekly Average Return**: -4.71% - **Excess Return over Equal-Weighted CSI First-Level Industry Index**: 0.35% - **November-to-Date Excess Return**: 2.92% - **Year-to-Date Excess Return**: -2.74%[35][30][31]

Market Liquidity Overview - R007 increased from 1.4945% to 1.4952%, a rise of 0.07 basis points, while DR007 decreased from 1.4673% to 1.4408%, a drop of 2.65 basis points. The spread between R007 and DR007 widened by 2.72 basis points [9] - The net outflow of funds this week was 40.114 billion yuan, with net inflow decreasing by 23.562 billion yuan compared to last week. Fund supply was 53.787 billion yuan, while demand was 93.901 billion yuan [11] Industry Sector Liquidity Tracking - All sectors in the CITIC first-level industry index experienced declines, with the comprehensive sector showing the most significant drop of 9.47%. The power equipment and new energy, as well as basic chemicals sectors, also saw slight declines [16] - The defense industry received the highest net inflow of leveraged funds at 0.507 billion yuan, while the electronics sector experienced the most significant net outflow of 10.594 billion yuan [18] Style Sector Liquidity Tracking - The style indices generally fell, with the cyclical and growth styles leading the decline at 6.02% and 5.73%, respectively. The growth style was the most active, accounting for 54.58% of the average daily trading volume [33] - The main funds in the style sectors showed a predominant trend of reduction, with the stable style seeing an increase of 0.378 billion yuan, while the growth style saw a reduction of 31.3 billion yuan [32]

- The report discusses the "Volume Timing Signal" model, which indicates a cautious view for all indices as of November 21, 2025[24][25] - The "Number of Rising Stocks in the CSI 300 Index" sentiment indicator is used to gauge market sentiment by calculating the proportion of stocks with positive returns over a certain period[25][26] - The "Number of Rising Stocks in the CSI 300 Index" timing tracking involves smoothing the indicator over two different periods to capture its trend, with a bullish view when the short-term line is above the long-term line[27][28][29] - The "Moving Average Sentiment Indicator" uses the eight moving averages system to assess the trend state of the CSI 300 Index, assigning values based on the position of the moving average range[33][34][35] - The "Moving Average Sentiment Indicator" shows that the CSI 300 Index is currently in a non-prosperous sentiment range as of November 21, 2025[33][36][37] Model Backtest Results - Volume Timing Signal: All indices show a cautious view as of November 21, 2025[24][25] - Number of Rising Stocks in the CSI 300 Index: The indicator has recently declined, with the proportion of rising stocks slightly above 50%, indicating cooling market sentiment[25][26] - Number of Rising Stocks in the CSI 300 Index Timing Tracking: Both the fast and slow lines are declining, with the fast line below the slow line, indicating a cautious view for the near future[27][28][29] - Moving Average Sentiment Indicator: The CSI 300 Index is in a non-prosperous sentiment range as of November 21, 2025[33][36][37] Factor Construction and Evaluation - Cross-sectional volatility: The recent week saw a decline in cross-sectional volatility for CSI 300 and CSI 500 index constituents, indicating a deteriorating short-term alpha environment, while the CSI 1000 index constituents saw an increase, indicating an improving short-term alpha environment[2][38] - Time-series volatility: The recent week saw a decline in time-series volatility for CSI 300 index constituents, indicating a deteriorating alpha environment, while the CSI 500 and CSI 1000 index constituents saw an increase, indicating an improving alpha environment[2][39][40] Factor Backtest Results - Cross-sectional volatility: - CSI 300: 2.28% (recent quarter average), 83.44% (recent quarter average as a percentile of the past two years) - CSI 500: 2.44% (recent quarter average), 78.57% (recent quarter average as a percentile of the past two years) - CSI 1000: 2.60% (recent quarter average), 83.67% (recent quarter average as a percentile of the past two years)[39] - Time-series volatility: - CSI 300: 0.73% (recent quarter average), 77.23% (recent quarter average as a percentile of the past two years) - CSI 500: 0.53% (recent quarter average), 80.16% (recent quarter average as a percentile of the past two years) - CSI 1000: 0.27% (recent quarter average), 82.07% (recent quarter average as a percentile of the past two years)[42]

—— 量化市场追踪周报（2025W47） [Table_ReportTime] 2025 年 11 月 23 日 请阅读最后一页免责声明及信息披露 http://www.cindasc.com 1 证券研究报告 金工研究 [Table_ReportType] 金工点评报告 [Table_Author] 于明明 金融工程与金融产品 首席分析师 执业编号：S1500521070001 联系电话：+86 18616021459 邮 箱：yumingming@cindasc.com 吴彦锦 金融工程与金融产品 分析师 执业编号：S1500523090002 联系电话：+86 18616819227 主动权益趋势性增配电子、有色与及反内卷板块 邮 箱：wuyanjin@cindasc.com 周君睿 金融工程与金融产品 分析师 执业编号：S1500523110005 联系电话：+86 19821223545 邮 箱：zhoujunrui@cindasc.com [Table_Title] 量化市场追踪周报(2025W47)：主动权益趋势性增 配电子、有色与及反内卷板块 [Table_ReportDate] 2025 年 ...

Group 1 - The report tracks stocks, industries, and sectors that are reaching new highs, indicating market trends and hotspots [1][4][24] - As of November 21, 2025, the distance to the 250-day new high for major indices is as follows: Shanghai Composite Index 4.83%, Shenzhen Component Index 8.65%, CSI 300 6.20%, CSI 500 9.69%, CSI 1000 7.59%, CSI 2000 7.40%, ChiNext Index 12.16%, and STAR 50 Index 16.45% [5][24] - Among the CITIC primary industry indices, the sectors closest to their 250-day new highs include petroleum and petrochemicals, textiles and apparel, basic chemicals, home appliances, and steel [8][24] Group 2 - A total of 1,127 stocks reached a 250-day new high in the past 20 trading days, with the highest number of new highs in the basic chemicals, machinery, and power equipment and new energy sectors [2][13][24] - The highest proportion of new high stocks is found in the textiles and apparel, coal, and non-ferrous metals sectors, with respective proportions of 41.41%, 38.89%, and 38.71% [13][24] - The cyclical and manufacturing sectors had the most new high stocks this week, with 364 and 315 stocks respectively [15][24] Group 3 - The report identifies 15 stocks that have shown stable new highs, including Heertai, Sry New Materials, and Cangge Mining, with the manufacturing and cyclical sectors contributing the most stocks [3][20][25] - The construction industry had the highest number of new highs within the manufacturing sector, while the non-ferrous metals industry led in the cyclical sector [20][25]

市场研究部证券研究报告 2025 年 11 月 21 日 行业方面，30 个中信一级行业有 5 个行上涨，其中建 材、银行及通信涨幅居前，而煤炭、电力设备及新能 源、石油石化则跌幅较大。概念方面，摩尔线程、央 企银行及锂矿等指数表现活跃。 海外市场综述 美股三大指数全线收跌，英伟达跌超 3% 周四（11 月 20 日），美国三大股指全线收跌，道指 跌 0.84%，标普 500 指数跌 1.56%，纳指跌 2.15%。思 科跌超 3%，波音跌逾 3%，领跌道指。万得美国科技七 巨头指数跌 1.74%，英伟达跌超 3%，亚马逊跌逾 2%。 中概股普遍下跌，阿特斯太阳能跌近 19%，信也科技 跌超 14%。 新闻精要 1. 中、坦、赞三国关于携手打造坦赞铁路繁荣带的联 合声明 2. 财政部公示消费新业态新模式新场景试点城市竞 争性评审结果 3. 商务部：如日方一意孤行，中方将坚决采取必要措 施 国内市场综述 冲高回落 震荡走弱 周四（11 月 20 日）大盘冲高回落 震荡走弱。截至收 盘，上证综指收于 3931.05 点，下跌 0.4%；深成指收 于 12980.82 点，下跌 0.76%；科创 50 下跌 1.2 ...

中信建投研报表示，当前机构关注基础化工、国防军工、汽车、纺织服装、非银行金融和传媒行业，通 信行业的机构关注度从高位下降。最近一周"石油石化"、"煤炭"、"钢铁"、"轻工制造"和"非银行金 融"行业的机构关注度在提升。当前较多行业处于触发拥挤指标阈值的状态（流动性、成分股一致 性）。2025年11月看好电力及公用事业、基础化工、电力设备及新能源、电子和计算机的相对收益。黄 金、白银、铜和原油的VIX抬升，中长期依然看多黄金。 (本文来自第一财经) ...

Group 1 - The Shenzhen Growth 40 Index has shown strong performance, with a 2.50% increase, and key stocks such as Upstream Electric and Zhongcai Technology have risen significantly, indicating a robust growth trend in the market [1][3] - The top three industries represented in the Shenzhen Growth 40 Index are Power Equipment and New Energy (31.10%), Basic Chemicals (13.74%), and Communications (12.51%), highlighting the sectors driving growth [1] - Domestic power battery installation volume reached 578 GWh from January to October this year, a year-on-year increase of 42.4%, while global energy storage battery shipments grew by 90.7% in the same period, indicating a strong upward trend in the battery industry [1] Group 2 - Citic Securities predicts that global energy storage installations will reach approximately 290 GWh by 2025 and could reach 1.17 TWh by 2030, showcasing significant growth potential in the energy storage sector [2] - The domestic energy storage industry chain is gaining a competitive edge, with increasing global market share in battery cells and storage systems, supported by favorable policies that are accelerating marketization [2] - The basic chemicals sector is expected to experience a cyclical recovery driven by profit improvements, with factors such as capacity cycle recovery and policy support contributing to this trend [2] Group 3 - The top ten weighted stocks in the Shenzhen Growth 40 Index account for 69.02% of the index, with leading companies including CATL and Xinyu Technology, indicating concentrated investment in key growth firms [3]