Group 1 - The market is currently pricing in hawkish expectations from Kevin Walsh, which may be overestimated, and further validation is needed from his actions and statements [2][24] - The domestic AI investment is still in its early stages, with significant differences in cycles compared to overseas investments, which are experiencing a surge in capital expenditure [2][22] - The micro liquidity environment in the domestic market remains favorable, and there are expectations for policy support, indicating a potential for a spring market rally [2][27] Group 2 - The long-term growth trend remains dominant, with expectations for continued outperformance in growth sectors, particularly in electronics, insurance, media, machinery, communication, chemicals, and real estate chains [3][30] - The current style switch is characterized as a small cycle level relative return convergence, with historical data indicating that such convergence typically lasts around 40 trading days [3][43] - The emotional cycle is currently in an upward phase, which supports a risk-on sentiment and a preference for growth investments [3][38] Group 3 - The recent global risk asset adjustments have shown resilience in the A-share market, despite pressures from tightening dollar liquidity and renewed concerns over AI narratives [10][22] - The anticipated spring market rally is expected to be supported by policy expectations and capital inflows, particularly in the period leading up to the National People's Congress [27][29] - The growth style is expected to outperform in the medium term, while the recent style switch is viewed as a tactical adjustment rather than a fundamental shift [24][30]

- The report does not contain any specific quantitative models or factors, nor their construction, evaluation, or backtesting results. The content primarily focuses on market performance, style indices, valuation, and other financial metrics without detailing any quantitative models or factors[1][2][3]

本文字数：2511，阅读时长大约4分钟 作者 | 第一财经 魏中原 2026.02. 08 2月首周，A股市场风格显著切换，科技板块遭遇深度调整。当周，电子、通信行业领跌两市，其中 电 子 行 业 总 市 值 跌 去 约 8900 亿 元 。 龙 头 股 更 是 放 量 杀 跌 ， 重 创 板 块 情 绪 ， 中 际 旭 创 （ 300308.SZ ） 、 新 易 盛 （ 300502.SZ ） 周 跌 幅 均 超 13% ， 寒 武 纪 （ 688256.SH ） 单 周 重 挫 17.63%，股价创2025年8月末以来新低。 与之形成鲜明对比的是，白酒、地产等防御性板块逆势走强，贵州茅台（600519.SH）周内涨 8.14%，保利发展（600048.SH）创下年内股价新高。 市场人士分析，临近春节长假，资金避险情绪升温，叠加科技股前期涨幅透支估值，投资者正从高波 动赛道转向业绩确定性更强的领域，反映出市场对估值合理性的审慎重估与对稳健收益的追求。 科技赛道全线降温，资金放量出逃 多重因素共振导致科技回调 本轮科技股的深度回调并非偶然，而是多重因素共同作用的结果。从时间节点、外部环境到内在估 值，科技板块 ...

Core Viewpoint - The A-share market experienced a significant style switch in the first week of February, with the technology sector undergoing a deep adjustment while defensive sectors like liquor and real estate showed resilience [1][4]. Group 1: Technology Sector Performance - The technology sector faced a comprehensive pullback, with the electronic industry market capitalization dropping by approximately 890 billion yuan, and leading stocks like Zhongji Xuchuang and Xinyi Sheng seeing weekly declines exceeding 13% [1][2]. - The electronic industry recorded a trading volume of 313.9 billion yuan, marking a new high for the year, while the industry index fell by 5.22% and the communication sector by 6.94% [2][3]. - The ChiNext 50 index, representing the technology sector, experienced its largest weekly decline since November 2025, with a drop of 5.76% [2]. Group 2: Market Dynamics and Investor Behavior - The market's risk appetite for technology stocks has notably decreased, with many stocks retreating 20% to 30% from their recent highs, indicating a significant sell-off [3][4]. - The upcoming Spring Festival led to increased risk aversion among investors, prompting them to shift from high-volatility sectors to those with stronger earnings certainty [1][4]. - High valuations in the technology sector, with the electronic industry's price-to-earnings ratio at 69.76, have created substantial internal adjustment pressure [4][5]. Group 3: Factors Influencing the Adjustment - Multiple factors contributed to the technology sector's deep pullback, including seasonal trading patterns, high valuations prompting profit-taking, and increased market volatility due to external macroeconomic conditions [4][5]. - The anticipation of rising interest rates in the U.S. has negatively impacted technology stock valuations, as indicated by market reactions to Federal Reserve signals [5][6]. - The shift of funds from technology stocks to defensive sectors like liquor and real estate suggests a phase of market style transition, with investors seeking stability amid uncertainty [6].

证券研究报告 A股策略周报: 节前博弈与长期布局如何权衡？ 证券分析师 陈 骁 投资咨询资格编号：S1060516070001 郝思婧 投资咨询资格编号：S1060521070001 请务必阅读正文后免责条款 2026年2月8日 1 ※ 核心观点|节前博弈与长期布局如何权衡？ 1 近期动态|政策跟踪：国常会研究促进有效投资措施，虚拟货币监管政策收紧 资料来源：商务部，市场监管总局，中国政府网，央行，国家药监局，证监会，工信部，平安证券研究所 3 近一周重要政策梳理 日期 部门/会议 会议/文件/行动 主要内容 2026/2/2 商务部等九单位《2026"乐购新春"春节特别活动方 案》 涵盖"好吃""好住""好行""好游""好购""好玩"六方面内容。活动时间为2月15至23日春节9天假期， 旨在打造全域联动、全民乐享的春节消费盛宴。 2026/2/2 市场监管总局等 十部门 《低空经济标准体系建设指南（2025 年版）》 重点围绕低空航空器、低空基础设施、低空空中交通管理、安全监管和应用场景五大核心领域，建立"四维融 合"标准供给体系，要求到2027年体系基本建立。 2026/2/3 国务院 《中共中央 国务院 ...

炒股就看金麒麟分析师研报，权威，专业，及时，全面，助您挖掘潜力主题机会！ 来源：华金证券 炒股就看金麒麟分析师研报，权威，专业，及时，全面，助您挖掘潜力主题机会！ 来源：华金证券 春节前A 股短期走势对节后行情可能有一定影响。2010 年以来的16 年中，有9次春节前5 个交易日内上 证综指走强（弱）而节后1 个交易日上证综指下跌（上涨）；有12 次节前5 个交易日内上证综指涨跌与 节后5 个交易日内涨跌同向。 春季行情未完，春节期间风险可能有限，可持股过节。（1）今年春节期间经济和盈利预期可能改善。 一是春节出行、消费数据可能偏好。二是今年春节地产销售可能有所回暖：首先，低基数效应下今年春 节期间地产销售同比增速可能有所回升；其次，各地刺激地产销售的政策预期较强，春节假期期间地产 销售可能延续回暖趋势。（2）春节期间流动性可能维持宽松。一是春节期间宏观流动性可能维持宽 松：首先，海外方面，2 月11 日美国1 月CPI 数据将公布，2 月17 日美国零售数据将披露，预计美元指 数可能继续维持低位震荡，海外对国内流动性宽松的掣肘有限；其次，国内方面，春节前流动性季节性 紧张下央行可能加大净投放力度。二是春节前 ...

Quantitative Models and Factors Summary Quantitative Models and Construction Methods Model Name: Volume Timing Model - **Model Construction Idea**: The model uses volume signals to determine market timing[12] - **Model Construction Process**: - The model evaluates the volume timing signals for major indices as of February 6, 2026, and maintains a cautious view[24] - **Model Evaluation**: The model is currently signaling a cautious outlook for all major indices[24] Model Name: Momentum Sentiment Indicator - **Model Construction Idea**: The model uses the number of stocks with positive returns within an index to gauge market sentiment[24] - **Model Construction Process**: - Calculate the proportion of stocks in the CSI 300 index with positive returns over the past N days - The formula is: $ \text{CSI 300 Index N-day Upward Stock Proportion} = \frac{\text{Number of stocks with positive returns in the past N days}}{\text{Total number of stocks in the index}} $[24] - **Model Evaluation**: The indicator can quickly capture upward opportunities but may miss out on gains during sustained market exuberance and has limitations in predicting downturns[25] Model Name: Moving Average Sentiment Indicator - **Model Construction Idea**: The model uses the eight moving average system to determine the trend state of the CSI 300 index[32] - **Model Construction Process**: - Calculate the eight moving average values for the CSI 300 index closing prices with parameters 8, 13, 21, 34, 55, 89, 144, 233 - Assign values to the moving average indicator based on the moving average interval values - The formula is: $ \text{Indicator Value} = \begin{cases} -1 & \text{if interval value is 1/2/3} \\ 0 & \text{if interval value is 4/5/6} \\ 1 & \text{if interval value is 7/8/9} \end{cases} $[32] - **Model Evaluation**: The recent CSI 300 index is in a non-prosperous sentiment interval[32] Model Backtesting Results Volume Timing Model - **Signal**: Cautious for all major indices[24] Momentum Sentiment Indicator - **Current Value**: The indicator is above 60%, indicating high market sentiment[25] Moving Average Sentiment Indicator - **Current Value**: The CSI 300 index is in a non-prosperous sentiment interval[32] Quantitative Factors and Construction Methods Factor Name: Cross-sectional Volatility - **Factor Construction Idea**: The factor measures the cross-sectional volatility of index constituent stocks to assess the Alpha environment[36] - **Factor Construction Process**: - Calculate the cross-sectional volatility for the CSI 300, CSI 500, and CSI 1000 index constituent stocks - The formula is: $ \text{Cross-sectional Volatility} = \sqrt{\frac{1}{N-1} \sum_{i=1}^{N} (R_i - \bar{R})^2} $ where $ R_i $ is the return of stock i, and $ \bar{R} $ is the average return[37] - **Factor Evaluation**: The short-term Alpha environment has deteriorated, but the quarterly view shows a good Alpha environment for the CSI 300 and CSI 1000 indices[36] Factor Name: Time-series Volatility - **Factor Construction Idea**: The factor measures the time-series volatility of index constituent stocks to assess the Alpha environment[37] - **Factor Construction Process**: - Calculate the time-series volatility for the CSI 300, CSI 500, and CSI 1000 index constituent stocks - The formula is: $ \text{Time-series Volatility} = \sqrt{\frac{1}{T-1} \sum_{t=1}^{T} (R_t - \bar{R})^2} $ where $ R_t $ is the return at time t, and $ \bar{R} $ is the average return[40] - **Factor Evaluation**: The recent week shows an improvement in the Alpha environment for all indices[37] Factor Backtesting Results Cross-sectional Volatility - **CSI 300**: - Last quarter average: 2.17% - Last quarter percentile (2 years): 70.99% - Last quarter percentile (1 year): 74.07% - Last quarter percentile (6 months): 65.64%[37] - **CSI 500**: - Last quarter average: 2.48% - Last quarter percentile (2 years): 48.41% - Last quarter percentile (1 year): 53.97% - Last quarter percentile (6 months): 56.35%[37] - **CSI 1000**: - Last quarter average: 2.63% - Last quarter percentile (2 years): 66.53% - Last quarter percentile (1 year): 68.92% - Last quarter percentile (6 months): 66.14%[37] Time-series Volatility - **CSI 300**: - Last quarter average: 0.96% - Last quarter percentile (2 years): 58.02% - Last quarter percentile (1 year): 60.91% - Last quarter percentile (6 months): 47.94%[40] - **CSI 500**: - Last quarter average: 1.27% - Last quarter percentile (2 years): 50.00% - Last quarter percentile (1 year): 57.94% - Last quarter percentile (6 months): 60.32%[40] - **CSI 1000**: - Last quarter average: 1.22% - Last quarter percentile (2 years): 63.35% - Last quarter percentile (1 year): 71.31% - Last quarter percentile (6 months): 66.93%[40]

证券研究报告 | 策略专题研究 | 中国策略 策略专题研究 报告日期：2026 年 02 月 05 日 涨价品种出现分化，券商景气度高增 ——行业景气度跟踪报告（2026 年 2 月） 核心观点 上游周期品中，前期涨价品种出现一定程度的分化。从周环比数据看，有色金属中仅 黄金价格出现上涨，白银和其他工业金属出现不同程度的下行，石油石化、基础化工 等细分品种价格亦出现一定回落。双焦价格回暖。TMT 中，半导体销售周期上行行业 景气度不减。下游消费品中，飞天茅台当年散装价格环比上行，支撑白酒走强。金融 地产方面，两市成交额放大，两融余额处于高位，彰显券商景气高增。 ❑ 上游周期 1）有色金属：价格出现分化，comex 黄金价格周环比上行；2）煤炭：煤炭开采 和洗选 PPI 同比增速修复，双焦价格回暖；3）石油石化：石油和天然气开采业 PPI 下行，原油价格承压 ❑ 中游周期 1）钢铁：铁矿石和螺纹钢价格周环比上行；2）基础化工：主要品种价格下行； 3）建筑材料：行业景气度仍处于相对低位；4）交通运输：海运业务走低，快递 业务增速放缓。 ❑ 中游制造 1）轻工制造：建材家居景气度下行，白卡纸价格处于低位。2）汽车： ...

Fund Size Statistics - The top three equity ETF types by fund size change are: Scale Index ETF (¥15.406 billion), Cross-border Industry Index ETF (¥6.624 billion), and Strategy Index ETF (¥5.384 billion) [9] - The bottom three equity ETF types by fund size change are: Theme Index ETF (-¥26.004 billion), Cross-border Scale Index ETF (-¥1.807 billion), and Cross-border Theme Index ETF (¥0.203 billion) [9] - The top three equity ETF products by fund size change are: CSI 500 ETF (¥2.832 billion), Chemical ETF (¥2.386 billion), and HuShen 300 ETF (¥2.229 billion) [9] - The bottom three equity ETF products by fund size change are: Communication ETF (-¥30.885 billion), Non-ferrous Metals ETF (-¥3.932 billion), and Gold Stock ETF (-¥2.963 billion) [13] Market Outlook - The macro timing model for February 2026 has a score of 0, indicating a historical 78.57% probability of the full A index rising in the following month, with an average increase of 3.37% [23] - A-shares are expected to experience a short-term volatile market, influenced by liquidity from overseas markets and the recent AI bubble discussions affecting tech growth stocks [23] - The recommendation is to adopt a balanced ETF allocation strategy due to the anticipated short-term fluctuations in the market [60]

证券研究报告·宏观报告·宏观周报 金融产品周报 20260207 海外市场流动性有企稳迹象，情绪或会好转 2026 年 02 月 07 日 [Table_Summary] 基金规模统计：（2026.2.2-2026.2.6） 市场行情展望：（2026.2.9-2026.2.13） 基金配置建议： 证券分析师 芦哲 执业证书：S0600524110003 luzhe@dwzq.com.cn 证券分析师 唐遥衎 执业证书：S0600524120016 tangyk@dwzq.com.cn 相关研究 《商品流动性冲击之后，哪些品种被 "错杀"？》 2026-02-04 《黄金 ETF，2026 年 1 月复盘与 2 月 展望》 2026-02-03 东吴证券研究所 1 / 20 请务必阅读正文之后的免责声明部分 [Table_Tag] ◼ 权益类 ETF 基金规模变化统计：规模变化排名前三名的权益类 ETF 类 型分别为：规模指数 ETF（154.06 亿元），跨境行业指数 ETF（66.24 亿 元），策略指数 ETF（53.84 亿元）；规模变化排名后三名的权益类 ETF 类型分别为：主题指数 ETF（-260 ...