★下周观点：持仓过节 周度报告——股指期货 高位题材回撤，股市切向低位 [★Ta一bl周e_复Su盘mm：a贵ry]金属与科技齐跌 股 指 期 货 本周（02/02-02/06）以美元计价的全球股市收跌。MSCI 全球指 数跌 0.14%，其中发达市场（+0.03%）>新兴市场（-1.42%）> 前沿市场（-1.77%）。印度股市涨 3.08%跑赢全球，韩国股市跌 5.06%全球表现最差。中国权益下跌，分市场看，中概股>A 股> 港股。A 股沪深京三市日均成交额 24069 亿元，环比上周（30636 亿元)缩量 6567 亿元。A 股宽基指数多数下跌，其中微盘股指数 涨 2.35%表现最好，科创 50 指数跌 5.76%表现较弱。本周 A 股 中信一级行业中共 15 个上涨（上周 10 个），15 个下跌（上周 20 个）。涨幅最大的行业为食品饮料（+4.44%），跌幅最大的 行业为有色金属（-8.46%）。利率方面，本周 10Y 国债收益率下 行，1Y 上行，利差缩小。ETF 资金流向方面，跟踪沪深 300 指 数的 ETF 份额本周减少 11 亿份，跟踪中证 500 的 ETF 份额减 少 16 亿份。 ...

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- The report constructs a "total heat" indicator by aggregating the browsing, self-selection, and click counts of individual stocks, normalized as a percentage of the total market on the same day, and then multiplied by 10,000, with a value range of [0,10000][7] - The "total heat" indicator is used as a proxy for "sentiment heat" to track the attention levels of broad-based indices, industries, and concepts[7] - The broad-based indices are divided into groups: CSI 300, CSI 500, CSI 1000, CSI 2000, and "others," with the total heat indicators of the constituent stocks summed up to obtain the heat of these indices[8] - A simple rotation strategy is constructed based on the weekly heat change rate, buying the broad-based index with the highest heat change rate MA2 at the end of each week, and staying out of the market if the "others" group has the highest change rate[12] - The rotation strategy based on the broad-based heat change rate MA2 has an annualized return of 8.74% since 2017, with a maximum drawdown of 23.5%, and a return of 5.2% in 2026[15] - The weekly heat change rate MA2 for the main broad-based indices shows that the CSI 300 had the highest increase of 3.34% compared to the previous week, while the CSI 500 had the largest decrease of 5.98%[15] - The heat change rate MA2 for the Shenwan first-level industries shows that the oil and petrochemical industry had the highest increase of 58.0% compared to the previous week, while the electronics industry had the largest decrease of -14.1%[26] - The heat change rate MA2 for the Shenwan second-level industries shows that the top five industries with the highest positive change rates are jewelry, planting, liquor II, lighting equipment II, and oil service engineering[26] - The heat change rate for concepts shows that the top five concepts with the highest positive change rates are Huawei Digital Energy, horse racing concept, duty-free shops, Huawei Euler, and pumped storage[27] - Two simple portfolios are constructed: one selects the top 10 stocks with the highest total heat from the top five concepts with the highest heat change rates each week, and the other selects the bottom 10 stocks with the lowest total heat from the same concepts[30] - The historical performance of the portfolios shows that the bottom group can achieve an annualized return of 15.71% with a maximum drawdown of 28.89%[32]

- The report discusses multiple quantitative models for market timing, including short-term, medium-term, and long-term models. These models are constructed based on price-volume, acceleration and trend, momentum, and limit-up/down perspectives. The report emphasizes the importance of combining signals from different models and periods to achieve a balanced strategy[9][11][12] - The short-term models include the "Volume Model" (neutral), "Feature Institutional Model" (neutral), "Feature Volume Model" (bearish), "Smart Algorithm CSI 300 Model" (bullish), and "Smart Algorithm CSI 500 Model" (bearish)[11][70] - Medium-term models include the "Limit-Up/Down Model" (neutral), "Up-Down Return Difference Model" (bullish for some broad-based indices), and "Calendar Effect Model" (bullish)[12][71] - The long-term model is the "Long-Term Momentum Model," which is neutral[72] - Comprehensive models such as the "A-Share Comprehensive Weapon V3 Model" and "A-Share Comprehensive CSI 2000 Model" are neutral[73] - For Hong Kong stocks, the medium-term models include the "Turnover-to-Volatility Model" (bearish), "Hang Seng Index Up-Down Return Difference Model" (neutral), and "Up-Down Return Similarity Model" (bullish)[13][74] - Backtesting results for the "Cup-and-Handle Pattern" show a weekly decline of -0.44%, outperforming the Shanghai Composite Index by 0.83%. Since December 31, 2020, the cumulative return of this pattern is 19.67%, exceeding the Shanghai Composite Index by 2.61%[43][44] - Backtesting results for the "Double-Bottom Pattern" show a weekly decline of -0.88%, outperforming the Shanghai Composite Index by 0.39%. Since December 31, 2020, the cumulative return of this pattern is 23.45%, exceeding the Shanghai Composite Index by 6.39%[43][50]

Core Viewpoint - The A-share market experienced significant fluctuations this week, primarily influenced by international gold and silver prices, leading to a shift in market hotspots from technology stocks to consumer stocks [1][3][4] Market Performance - On Monday, the Shanghai Composite Index opened at 4079.71 points, dropping to a low of 4015.75 points, marking a decline of 102.2 points or 2.48%, which is a rare occurrence of a hundred-point drop in over a year [1] - The index reached its lowest point of the week at 4002.78 on Tuesday but rebounded to a high of 4104.62 on Wednesday, ultimately closing at 4065.58 points on Friday, resulting in a weekly decline of 52 points or 1.27% [2] - The Shenzhen Composite Index also showed similar trends, with a weekly decline of 2.11%, while the ChiNext Index fell by 3.28% [2] Sector Performance - The technology sector, which had been a market favorite, showed signs of retreat, with significant declines in indices related to integrated circuits and artificial intelligence, both dropping over 9% [3] - Conversely, the consumer sector saw a resurgence, with the Consumer Index rising by 2.46% after hitting a one-year low, and other consumer-related indices, such as food and beverage, increasing by 3% [4] - The tourism index also performed well, with a rise of over 3%, indicating a potential shift in investor interest from technology to consumer stocks [4]

1. Report Industry Investment Rating No relevant content provided. 2. Core Views of the Report - Overseas asset fluctuations have been repaired. Although the fourth - quarter reports of tech giants show that cloud - computing revenue and 2026 capex expenditure guidance exceed expectations, market divergence is rising, and the previous structured market is undergoing "destructuring". At least in the first half of 2026, tech growth will maintain its momentum due to factors such as the decrease in the expectation of the Fed's marginal monetary policy easing and the potential IPO of OpenAI in the third or fourth quarter of 2026 [1][37]. - In the domestic equity market, defensive sectors like food and beverage performed well last week, followed by pro - cyclical sectors, while tech growth sectors generally showed high volatility. For convertible bonds, due to the priority of winning rate over odds, high - volatility targets with tech themes and mostly being new - issue targets make it difficult to control drawdowns and increase the difficulty of speculation. Before the holiday, it is recommended to balance risks. High - position funds should actively switch from high - to low - risk assets, and low - position funds should seize the opportunity to invest in targets with clear performance inflection points and high visibility of upward trends in 2026 [1][37][39]. 3. Summary by Relevant Catalogs 3.1. Weekly Market Review 3.1.1. Overall Decline in the Equity Market - From February 2nd to February 6th, the equity market declined overall. The Shanghai Composite Index fell 1.27% to 4065.58 points, the Shenzhen Component Index dropped 2.11% to 13906.73 points, the ChiNext Index decreased 3.28% to 3236.46 points, and the CSI 300 fell 1.33% to 4643.60 points. The average daily trading volume of the two markets decreased by 21.36% week - on - week to 23879.96 billion yuan [6][10]. - Among the 31 Shenwan primary industries, 16 industries closed up, with 3 industries rising more than 2%. Food and beverage, beauty care, power equipment, transportation, and banking led the gains, rising 4.31%, 3.69%, 2.20%, 1.90%, and 1.70% respectively. Non - ferrous metals, communication, electronics, steel, and computer led the losses, with declines of - 8.51%, - 6.95%, - 5.23%, - 3.35%, and - 3.27% respectively [16]. 3.1.2. Overall Rise in the Convertible Bond Market - From February 2nd to February 6th, the CSI Convertible Bond Index rose 0.05% to 520.79 points. Among the 29 Shenwan primary industries, 22 industries closed up, with 2 industries rising more than 2%. Social services, power equipment, transportation, national defense and military industry, and petroleum and petrochemicals led the gains, rising 4.95%, 2.95%, 1.85%, 1.76%, and 1.42% respectively. Computer, electronics, communication, non - bank finance, and non - ferrous metals led the losses, falling 4.85%, 3.06%, 2.22%, 2.13%, and 1.94% respectively [19]. - The average daily trading volume of the convertible bond market was 902.09 billion yuan, a significant decrease of 30.87 billion yuan, with a month - on - month change of - 3.31%. The top ten convertible bonds in terms of trading volume were Shangtai Convertible Bond, Naipu Convertible Bond 02, Dongshi Convertible Bond, Yanpai Convertible Bond, Shuangliang Convertible Bond, Jize Convertible Bond, Yongji Convertible Bond, Jiemei Convertible Bond, Tairui Convertible Bond, and Jialian Convertible Bond. The average trading volume of the top ten convertible bonds reached 116.84 billion yuan, and the trading volume of the top - ranked bond was 335.59 billion yuan [19]. - Approximately 54.71% of individual convertible bonds rose, about 21.73% of them had a gain in the range of 0 - 1%, and 17.54% of them had a gain of more than 2% [19]. - The overall market conversion premium rate increased, with the average daily conversion premium rate this week being 44.31%, a 1.56 - percentage - point increase from last week. By price range, except for the convertible bonds in the price range below 90 yuan, the average daily conversion premium rate quantiles of convertible bonds in other price ranges narrowed. The narrowing amplitude was the largest in the 110 - 120 yuan price range, reaching 30.31 percentage points. By parity range, except for the convertible bonds in the parity range below 90 yuan, the average daily conversion premium rates of convertible bonds in other parity ranges narrowed, with the largest narrowing amplitude of 15.41 percentage points in the 110 - 120 yuan parity range [24]. - In terms of the premium rate changes of each industry, the conversion premium rates of 12 industries widened, with 3 industries having a widening amplitude of more than 2 percentage points. Social services, household appliances, food and beverage, media, and textile and apparel led the widening, with amplitudes of 9.03, 3.54, 2.90, 1.59, and 1.27 percentage points respectively. Building materials, communication, agriculture, forestry, animal husbandry and fishery, non - bank finance, and electronics led the narrowing, with amplitudes of - 14.89, - 14.64, - 5.78, - 4.62, and - 3.81 percentage points respectively [28]. - In terms of conversion parity, the parity of 4 industries increased, with 1 industry having a widening amplitude of more than 2%. Communication, transportation, banking, and social services led the widening, with amplitudes of 16.51%, 1.19%, 0.61%, and 0.13% respectively. Non - bank finance, non - ferrous metals, building materials, automobiles, and electronics led the narrowing, with amplitudes of - 29.31%, - 15.94%, - 13.22%, - 11.74%, and - 10.64% respectively [30]. 3.1.3. Comparison of Stock and Bond Market Sentiments - From February 2nd to February 6th, the weekly weighted average change of the convertible bond market was negative, and the median was positive. The weekly weighted average change of the underlying stock market was positive, and the median was negative. In terms of trading volume, the trading volume of the convertible bond market decreased by 4.05% month - on - month and was at the 82.40% quantile level since 2022. The trading volume of the underlying stock market decreased by 22.67% month - on - month and was at the 88.20% quantile level since 2022. Both the underlying stocks and convertible bonds had a significant reduction in trading volume, and the underlying stock trading volume was at a higher quantile level. In terms of the proportion of rising and falling stocks and bonds, about 60.00% of convertible bonds closed up, and about 43.85% of underlying stocks closed up. About 64.62% of convertible bonds had a larger change than the underlying stocks. In general, the trading sentiment of the convertible bond market was better this week [34]. 3.2. Outlook and Investment Strategy - Overseas asset fluctuations have been repaired. Although the fourth - quarter reports of tech giants show that cloud - computing revenue and 2026 capex expenditure guidance exceed expectations, market divergence is rising, and the previous structured market is undergoing "destructuring". At least in the first half of 2026, tech growth will maintain its momentum due to factors such as the decrease in the expectation of the Fed's marginal monetary policy easing and the potential IPO of OpenAI in the third or fourth quarter of 2026 [1][37]. - In the domestic equity market, defensive sectors like food and beverage performed well last week, followed by pro - cyclical sectors, while tech growth sectors generally showed high volatility. For convertible bonds, due to the priority of winning rate over odds, high - volatility targets with tech themes and mostly being new - issue targets make it difficult to control drawdowns and increase the difficulty of speculation. Before the holiday, it is recommended to balance risks. High - position funds should actively switch from high - to low - risk assets, and low - position funds should seize the opportunity to invest in targets with clear performance inflection points and high visibility of upward trends in 2026 [1][37][39]. - Specific targets recommended for attention include Bo 25, Baolong, Saite, Huitian, Suli, Jianlong, Tairui, Yongjin, Zhongte, Yongxi, Dinglong, Li'ang, Shenglan Convertible Bond 02, Chaosheng, Lihe, Huachen, Tiannai Convertible Bond, etc. [1][39]. - The top ten high - rated, medium - low - priced convertible bonds with the greatest potential for parity premium rate repair next week are Liqun Convertible Bond, Bengang Convertible Bond, Lutai Convertible Bond, Lianchuang Convertible Bond, Xingye Convertible Bond, Yingfeng Convertible Bond, Guotou Convertible Bond, Nenghua Convertible Bond, Qingnong Convertible Bond, and Ziyin Convertible Bond [1][39].

Group 1 - The current stock market is in a high volatility phase, while convertible bond valuations are at historically high levels. The proportion of convertible bond holdings by public funds has increased, indicating a shift in asset allocation towards convertible bonds and other equity assets due to high expectations in the stock market and a scarcity of assets in the bond market [1][12] - The medium to long-term outlook suggests that economic recovery and industrial structural upgrades will continue, with the stock market expected to maintain a trend of oscillating upward in 2026. Convertible bond valuations are supported by allocation demand, although the potential for further increases is limited [1][12] Group 2 - The investment strategy for convertible bonds should adopt a "winning probability" mindset, recognizing that different industries will experience varying degrees of prosperity. Public funds possess strong fundamental research capabilities, allowing them to actively price convertible bonds linked to improving fundamentals. High premium rates on some convertible bonds may still yield strong excess returns if the underlying stocks are in high-growth sectors [2][13] - Caution is advised regarding specific types of convertible bonds with excessively high premium rates, particularly those with less than six months remaining until maturity and those that may trigger early redemption clauses. These bonds face risks of rapid premium compression due to their contractual limitations [2][13] Group 3 - The weekly performance of the convertible bond index showed a slight increase of 0.05%, with certain sectors like food and beverage, beauty care, and electric equipment performing well. The median price of convertible bonds across various parity ranges has risen, indicating that valuations remain at relatively high historical levels [3][17] - The influx of incremental capital into the market is expected to continue, with a likely "spring excitement" rally at the beginning of the year, focusing on technology and high-end manufacturing investment opportunities. The chemical sector is anticipated to see improvements in demand, with well-structured supply and demand dynamics in certain sub-sectors expected to perform well [3][17] Group 4 - Suggested focus areas for convertible bonds include: (1) the rising demand for overseas computing power and the acceleration of AI industrialization driven by domestic model iterations, with recommendations for bonds from companies like Ruike and Qizhong; (2) high-end manufacturing is expected to remain strong, with recommendations for bonds from companies like Yake, Daimei, Huachen, Yubang, and Tairui; (3) the "anti-involution" trend may optimize supply and demand patterns in certain industries, with a recommendation for bonds from Youfa [4][18]

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： ...

Investment Rating - The industry investment rating is "Positive" (maintained) [1] Core Viewpoints - The food and beverage sector is experiencing a strong upward trend, driven by multiple factors including policy support, trading dynamics, fundamental improvements, and external catalysts, indicating clear investment value [3][9] - The food and beverage index increased by 4.3% from February 2 to February 6, outperforming the CSI 300 by approximately 5.6 percentage points, with sub-sectors like liquor, soft drinks, and beer leading the performance [9][11] - The liquor industry is entering a new development cycle, with Guizhou Moutai's market-oriented reforms marking a significant phase, and the pricing system gradually returning to a supply-demand driven model [10] Summary by Sections Market Performance - The food and beverage index rose by 4.3%, ranking first among 28 sectors, with liquor (+5.3%), soft drinks (+4.7%), and beer (+4.5%) showing relative strength [11][12] - Individual stocks such as Huangtai Liquor, Hai Xin Food, and Ri Chen Co. saw significant gains, while *ST Yedao, *ST Chuntian, and Li Ziyuan experienced declines [11][14] Upstream Data - Some upstream raw material prices are declining, with the price of whole milk powder at $3,614 per ton, down 13.3% year-on-year, and fresh milk prices at 3.04 yuan per kilogram, down 2.9% year-on-year [15][31] - The price of pork is down 20.1% year-on-year, with live pig prices at 12.2 yuan per kilogram, reflecting a broader trend of price adjustments in the sector [21][24] Liquor Industry News - Some distributors of Moutai have sold out their first batch of flying Moutai quotas for March, indicating strong demand during the Spring Festival [36] - The Qingdao Beer production base has commenced operations, aiming to produce high-end products and achieve an annual output value of approximately 1 billion yuan [36] Investment Recommendations - Focus on leading liquor stocks such as Guizhou Moutai, Wuliangye, Luzhou Laojiao, and Shanxi Fenjiu, as well as elastic stocks like Shede Liquor and benefiting stocks like Jiu Gui Liquor [10] - In the consumer goods sector, three main lines are suggested: the snack sector, dairy products, and the restaurant supply chain, with specific companies highlighted for potential growth [10][43]