1. Report Title and Date - The report is titled "Precious Metals High Volatility Continues, Stock Index Trends Diverge - CITIC Futures Morning Report 20260205" [1] 2. Report Industry Investment Rating - No industry investment rating is provided in the report 3. Core Views of the Report - Overseas macro: The nomination of Kevin Warsh as a candidate for the new Federal Reserve Chairman is expected to have limited impact on the market. The market views him as a hawkish figure, but it's difficult for him to implement the policy of shrinking the balance sheet. There are resistances for significant hawkish or dovish turns. Attention should be paid to the Iran-US situation and the US government shutdown [9]. - Domestic macro: The positive policy expectation remains the macro main - line. There is a growing expectation that policies in the first quarter will boost the economy to achieve a "good start" in the 15th Five - Year Plan. The policy environment is favorable. In January, both fiscal and monetary policies were proactive, and the economy showed overall stability with strong exports [9]. - Asset views: Emphasize the structural opportunities of portfolio allocation. Recommend over - allocating IC and non - ferrous metals (copper, aluminum, tin). The domestic policy expectation, loose liquidity, and inflation recovery expectation support the equity market. Treasury bonds are neutral, with better short - end opportunities. Precious metals have high short - term volatility and are recommended to be observed. Non - ferrous metals are relatively advantageous, and black commodities are volatile. Crude oil has high uncertainties [9]. 4. Summary of Relevant Catalogs 4.1 Market Data 4.1.1 Index Futures and Treasury Bonds - Index futures: The prices and various period - on - period changes of CSI 300 futures, SSE 50 futures, CSI 500 futures, and CSI 1000 futures are presented. For example, the CSI 300 futures price was 4693.6, with a daily increase of 0.2%, a weekly decrease of 0.37%, etc. [2]. - Treasury bonds: Information on 2 - year, 5 - year, 10 - year, and 30 - year treasury bond futures is given, including prices and period - on - period changes. For example, the 2 - year treasury bond futures price was 102.398, with a daily decrease of 0.02% [2]. 4.1.2 Foreign Exchange and Interest Rates - Foreign exchange: The dollar index was 97.3872, with a daily decrease of 0.23%, and the dollar intermediate price was 6.9385, with a decrease of 68 pips [2]. - Interest rates: Data on various interest rates such as the 7 - day inter - bank deposit - based pledge rate, 10Y Chinese treasury bond yield, 10Y US treasury bond yield, etc., and their changes are provided [2]. 4.1.3 Industry Index - The prices and various period - on - period changes of different industries are shown, including agriculture, forestry, animal husbandry and fishery, national defense and military industry, etc. For example, the agriculture, forestry, animal husbandry and fishery index was 5718.7165, with a daily increase of 1.39% [3]. 4.1.4 Domestic and Overseas Commodities - Domestic commodities: Information on various domestic commodities such as shipping, precious metals, non - ferrous metals, energy chemicals, and agricultural products is presented, including prices and period - on - period changes. For example, the gold price was 1143.37, with a daily increase of 4.39% [4]. - Overseas commodities: Data on overseas energy, precious metals, non - ferrous metals, and agricultural products are provided, including prices and period - on - period changes. For example, the NYMEX WTI crude oil price was 63.9, with a daily increase of 2.83% [6]. 4.2 Viewpoints on Different Asset Classes 4.2.1 Financial Assets - Stock index futures are expected to rise in a volatile manner, with the trend stabilizing and style complementing gains [10]. - Stock index options are expected to be volatile, with implied volatility continuing to decline and selling options to increase income [10]. - Treasury bond futures are expected to be volatile, as they fell across the board, and factors such as the implementation of monetary policies need to be concerned [10]. 4.2.2 Precious Metals - Gold and silver are expected to be volatile, as geopolitical conflicts have eased and the "Warsh trade" suppresses liquidity expectations [10]. 4.2.3 Shipping - The container shipping to Europe line is expected to be volatile, as spot freight rates are under pressure and shipping companies are reducing prices to attract cargo before the festival [10]. 4.2.4 Black Commodities - Steel products, iron ore, coke, coking coal, etc. are all expected to be volatile, with different influencing factors such as cost support, market sentiment, and supply and demand [10]. 4.2.5 Non - ferrous Metals - Copper, aluminum, nickel, stainless steel, etc. are expected to rise in a volatile manner, while others like zinc, lead, etc. are expected to be volatile, affected by factors such as market sentiment, supply and demand, and policies [10]. 4.2.6 Energy and Chemicals - Most energy and chemical products such as crude oil, LPG, and asphalt are expected to be volatile, affected by factors such as supply pressure, demand, and geopolitical situations. Styrene is expected to rise in a volatile manner [12]. 4.2.7 Agricultural Products - Most agricultural products are expected to be volatile, with different influencing factors. For example, cotton is expected to rise in a volatile manner, while sugar is expected to decline in a volatile manner [12].

Macro Perspective - The macro perspective indicates a bullish outlook on equity assets, a bearish outlook on bond assets, a neutral stance on gold assets, and a bullish outlook on industrial products [23][25]. - The latest scores for major asset classes are: Equity (2), Bonds (-3), Gold (0), and Industrial Products (4) [2]. Technical Perspective - The technical perspective shows a neutral view on equity assets, a bullish outlook on bond assets, a bullish outlook on gold assets, and a bullish outlook on industrial products [25]. - The technical scores for major asset classes are: Equity (0), Bonds (1), Gold (1), and Industrial Products (1) [2]. Equity Style Analysis - The macro perspective favors small-cap stocks over large-cap stocks, while both perspectives support a balanced allocation between growth and value styles [36][40]. - The latest scores for equity styles are: Large-Cap/Small-Cap (-1), Growth/Value (0) [40]. Asset Allocation Strategy - The asset allocation strategy includes a fixed weight for equities (20%), bonds (60%), commodities (10%), and cash (5%), with adjustments based on macro and technical indicators [29]. - Historical performance shows that the combination of fixed proportions with macro and technical indicators yielded an annualized return of 10.20% since 2007 [31]. Performance Metrics - The performance metrics for the asset allocation strategies indicate that controlling annualized volatility at 6% yielded a return of 10.46%, while the risk parity strategy yielded 8.29% [33]. - The historical performance of the small-cap rotation strategy shows an excess return of 2.54% since 2013 [43].

投资咨询业务资格：证监许可【2012】669号 大类资产总体反弹，能源化工小幅回落 ——中信期货晨报20260204 中信期货研究所 仲鼎 从业资格号F03107932 投资咨询号Z0021450 重要提示：本报告非期货交易咨询业务项下服务，其中的观点和信息仅作参考之用，不构成对任何人的投资建议。 我司不会因为关注、收到或阅读本报告内容而视相关人员为客户；市场有风险，投资需谨慎。 金融市场涨跌幅 | 2026-02-03 | 品种 | 现价 | 日度涨跌幅 | 周度涨跌幅 | 月度涨跌幅 | 季度涨跌幅 | 年度涨跌幅 | | --- | --- | --- | --- | --- | --- | --- | --- | | 股指 | 炉深300期货 | 4653 | 1.25 | -1. 23 | -1.23 | 1.16 | 1.16 | | | 上证50期货 | 3033 | 0. 8 | -1.33 | -1.33 | 0.26 | 0. 26 | | | 中证500期货 | 8282 | 3.71 | -0.96 | -0. 96 | 12. 48 | 12. 48 | | | 中证1000期货 | ...

- The report introduces a **macro timing model** for asset allocation, which predicts macroeconomic environments using proxy variables and selects optimal asset classes for absolute return portfolios. For Q1 2026, the model forecasts a "Slowdown" environment, with returns of 1.65% for CSI 300, 9.13% for CNI 2000, 8.61% for Nanhua Commodity Index, and 0.39% for ChinaBond Total Treasury Wealth Index[23][30] - A **macro momentum model** is constructed for monthly timing signals, considering factors such as economic growth, inflation, interest rates, exchange rates, and risk sentiment. This model is used for timing equities, bonds, and other major asset classes. Additionally, a multi-cycle gold timing strategy is built using macro, position, volume-price, and sentiment factors. For January 2026, the returns are 1.65% for CSI 300, 0.39% for ChinaBond Total Treasury Wealth Index, and 19.59% for AU9999 contract[23][30] - The **industry ETF rotation strategy** is based on a multi-factor model that incorporates historical fundamentals, expected fundamentals, sentiment, volume-price technicals, and macroeconomic factors. The strategy matches ETFs with their corresponding industry indices and selects ETFs from a benchmark pool of 23 first-level industries. For January 2026, the recommended ETFs include Guotai CSI Coal ETF, Guotai CSI Steel ETF, Guotai CSI All Securities ETF, and Huabao CSI Bank ETF, each with an initial weight of 25%[24][27][28] - The **20/80 stock-bond rebalancing strategy** driven by macro timing achieved a weekly return of 0.05% and a YTD return of 0.56%. The **stock-bond risk parity strategy** achieved a weekly return of 0.04% and a YTD return of 0.47%. When combined with the industry ETF rotation strategy, the enhanced 20/80 rebalancing strategy achieved a weekly return of 0.29% and a YTD return of 0.89%, while the enhanced risk parity strategy achieved a weekly return of 0.13% and a YTD return of 0.55%[4][30][33] - The **stock-bond-gold risk parity strategy** achieved a weekly return of 0.26% and a YTD return of 1.28%, with an annualized volatility of 2.96%, a maximum drawdown of 0.49%, and a Sharpe ratio of 6.90[4][30][35] - The **quantitative fixed-income plus strategy** includes stock-bond rebalancing models with different configurations. For the 10/90 monthly rebalancing strategy, the small-cap value style achieved a YTD return of 1.38%, while the small-cap growth style achieved 1.02%. For the 20/80 monthly rebalancing strategy, the small-cap value style achieved a YTD return of 2.60%, while the small-cap growth style achieved 1.88%. When combined with macro timing, the 20/80 monthly rebalancing strategy achieved a YTD return of 3.82% for the small-cap value style and 2.73% for the small-cap growth style. The 20/80 quarterly rebalancing strategy based on counter-cyclical allocation achieved a YTD return of 1.38% for the PB earnings + small-cap value combination and 1.02% for the PB earnings + small-cap growth combination[4][37][40]

1. Report Industry Investment Rating - There is no information about the industry investment rating in the provided content. 2. Core Viewpoints of the Report - The report aims to resolve the contradiction between "strong capital allocation willingness" and "weak differentiation in tool - end" in the commodity investment field. It turns to the under - explored macro - style Beta of commodity futures, providing a differentiated allocation path beyond traditional beta. Two distinct commodity futures long - only passive indices have been successfully developed: the Commodity Macro - Aggressive Index with a cyclical offensive attribute, and the Commodity Macro - Resilient Index with a cyclical defensive attribute. This index system based on "domain - based calibration of macro - attributes" outperforms existing commodity futures broad - based indices in long - term returns and offers lower correlations with other asset classes, filling the market gap of functional commodity allocation tools in China [1][2][80]. 3. Summary by Relevant Catalogs 3.1 Dilemma: "Tool Gap" in Asset Allocation - In the current practice of asset allocation, the commodity asset shows a stage characteristic of strong capital allocation willingness but few available indices and a high concentration of allocation tools. The total scale of domestic commodity funds (including domestic and QDII) is about 312.1 billion yuan, accounting for about 0.86% of the public - offering market. The internal variety distribution of commodity funds is highly concentrated, with the precious metal sector centered on gold accounting for over 95% of the market share. This structural imbalance has limited investors' ability to optimize the risk - return ratio of their portfolios through commodity assets [5][7]. - In contrast, overseas mature markets (taking the US as an example) have a multi - level product system with full asset - class coverage and highly functional tools. Their commodity funds have a much larger scale and a greater number of products than those in China, providing a wide range of on - exchange tools for various sectors [11]. 3.2 Breakthrough: Construction of Commodity Long - Only Indices from a New Perspective 3.2.1 Supply - and - Demand - Side Composite Macro - Indicators - **New Kinetic Energy Growth Index**: It is constructed by integrating the supply - side new - quality productivity index and the demand - side new - consumption index, which represents domestic demand, and weighting them by the inverse of volatility. On the supply side, the industries with the largest year - on - year incremental contributions in the added value of industrial enterprises above a designated size are selected as core weights, weakening traditional industries. On the demand side, sub - items with the largest year - on - year incremental contributions in total retail sales of consumer goods are retained to capture the core increment under the domestic - demand - led transformation of the Chinese economy from investment - driven to consumption - driven [19]. - **Comprehensive Inflation Index**: It is constructed by compounding the inflation indicators of the production and living ends on the supply and demand sides, weighting them by the inverse of volatility. CPI reflects the final demand of the resident end, and its trend change represents the long - term direction of China's economic transformation from investment - driven to consumption - driven. PPI focuses on the industrial production link of the supply side, reflecting the cost changes and corporate profitability of the industrial sector [21]. 3.2.2 Macro Penetration of Commodity Assets and Construction of Long - Only Indices - **Macro Domain Division and State Calibration** - **Macro Domain Division**: By regarding macro factors as style factors, using regression models for attribution testing of commodities, it is found that the industrial metal sector is positively exposed to the growth end with a cyclical offensive attribute, while the energy - chemical and agricultural product sectors are positively exposed to the inflation end, showing stronger cost - transmission and rigid - demand resilience [24]. - **State Calibration**: Instead of simply timing based on economic data fluctuations, the performance of assets in different macro - states is introduced as a sensitivity indicator. The historical return characteristics of each variety in specific macro - states (such as the growth spread after stripping inflation) are extracted as the risk budget to obtain the weights of the varieties [24]. - **Long - Only Index Construction Process and Functionality Analysis** - The construction of the long - only index is divided into four stages: data preparation and macro - scenario division, macro - factor regression and exposure calculation, asset screening, and construction of the commodity long - only index. - The Commodity Macro - Aggressive Index and the Commodity Macro - Resilient Index are constructed. The Aggressive Index has a cumulative return of 128%, an annualized return of 10.3%, a Sharpe ratio of 0.76, and a win - rate of 54.2%. The Resilient Index has a cumulative return of 40.2%, an annualized return of 4.1%, a Sharpe ratio of 0.37, and a win - rate of 51.2%. Both indices provide long - term positive returns and have lower correlations with equity and bond assets [67][71]. 3.3 Summary and Outlook 3.3.1 Summary - The report successfully develops two distinct commodity futures long - only passive indices to solve the contradiction in commodity investment. The index system based on "domain - based calibration of macro - attributes" has advantages in long - term returns and correlations with other asset classes, filling the market gap [80]. - The domestic commodity fund market has a "tool gap", while overseas markets have a more complete and functional tool system. A new quantitative framework from macro - reshaping to asset - penetration is constructed to develop these two indices [80][81]. 3.3.2 Outlook - Future research will expand globally on the tool side, extending from the domestic futures market to overseas markets to build a full - spectrum commodity allocation toolbox covering both domestic and overseas markets. - There will be a tactical advancement in methodology, shifting from "tool construction" in strategic asset allocation (SAA) to "strategy application" in tactical asset allocation (TAA) on the commodity side [82].

这两天，国际贵金属市场迎来"惊魂时刻"，金价接连失守关键整数关口，日前单日跌幅超11%；白 银更是以31.37%的断崖式下跌，创下近46年来最差单日表现。 剧烈波动之下，工商银行、建设银行等多家国有大行、国内外交易所纷纷紧急发布风险提示，调整 业务规则。金价涨跌还将辐射哪些领域？刚入手金饰的消费者，能否申请退货减少损失？ 此次暴跌并非孤立事件，同期工业金属也受到波及，铜、锡、铝等品种均出现不同程度下跌，全球 大宗商品市场陷入震荡。事实上，此轮跳水在机构端早有端倪。 上周，易方达黄金主题上市型开放式基金（LOF）公告暂停A类份额的申购及定期定额投资业务。 白银上市型开放式基金（LOF）同样"闭门谢客"，国投白银上市型开放式基金1月28日起暂停申购及定 期定额投资业务。国泰君安期货贵金属高级研究员刘雨萱指出，如果继续敞开申购，新增资金只能以极 高溢价买入，一旦溢价回落，原有份额将被摊薄，之前的持有人利益将受损。 美国芝商所集团同样于当地时间1月30日发布公告，宣布上调多个贵金属期货保证金比例。此外， 铂金和钯金期货的保证金比例也有所上调。此次保证金调整于2月2日收盘后正式生效。芝商所集团表 示，此举基于对市场波动 ...

Group 1: Federal Reserve and Economic Outlook - The nomination of hawkish Fed Chair Walsh is expected to restore the Fed's independence and support the dollar, leading to a rise in interest rates and a potential tightening of monetary policy[10] - The market anticipates a new round of tightening due to the Fed Chair nomination, with economic fundamentals showing signs of slowing down[2] - The 1Y Treasury yield decreased from 1.337% to 1.3%, while the 10Y Treasury yield fell from 1.847% to 1.811%[2] Group 2: Market Performance and Asset Allocation - The Shanghai Composite Index rose by 3.76% from 3968.84 to 4117.95, while the ChiNext Index increased by 4.47% from 3203.17 to 3346.36[2] - The NASDAQ index showed a slight increase of 0.95%, moving from 23241.99 to 23461.82, but is expected to face valuation pressure in the short term[2] - The recommendation is to overweight financial stocks while underweighting consumer stocks and U.S. equities due to tightening expectations[3] Group 3: Commodity and Currency Trends - Brent crude oil prices surged by 13.57%, from $57.42 to $65.21 per barrel, driven by geopolitical factors and Fed expectations[2] - The U.S. dollar index is on an upward trend, moving from 98.27 to 97.12, indicating a recovery in dollar strength[2] - The USD/CNY exchange rate slightly decreased from 6.99 to 6.95, reflecting a slower appreciation of the yuan[2]

Quantitative Models and Construction Methods Macro Indicator Trend Model - **Model Name**: Macro Indicator Trend Model - **Construction Idea**: Establish the relationship between macro indicators and asset performance by analyzing the trend of macro indicators and their impact on monthly asset returns[17][18] - **Construction Process**: - Use monthly moving averages of macro indicators to classify them into upward or downward trends - Apply T-test to determine whether the distribution of monthly returns of assets differs significantly under upward and downward trends - Formula: $ t = \frac{\overline{R_1} - \overline{R_2}}{\sqrt{\frac{(n_1-1)S_1^2 + (n_2-1)S_2^2}{n_1+n_2-2}(\frac{1}{n_1} + \frac{1}{n_2})}} \sim t_{n_1+n_2-2} $ - $\overline{R_1}$ and $\overline{R_2}$: Average monthly returns under upward and downward trends - $S_1$ and $S_2$: Standard deviations of monthly returns under upward and downward trends - $n_1$ and $n_2$: Number of months under upward and downward trends[17][18] - **Evaluation**: Effectively identifies macro indicators with significant impacts on asset returns[17][18] Technical Perspective Model - **Model Name**: Technical Perspective Model - **Construction Idea**: Evaluate asset trends, valuation, and fund flows using historical data and specific calculation methods[22][23][25] - **Construction Process**: - **Trend**: Use closing prices or LLT indicators to calculate trend indicators. Assign +1 for upward trends and -1 for downward trends[22] - **Valuation**: Calculate equity risk premium (ERP) as the reciprocal of PE(TTM) minus the 10-year government bond yield. Define historical 5-year percentile as: $ (Current ERP - Historical 5-year ERP Minimum) / (Historical 5-year ERP Maximum - Historical 5-year ERP Minimum) $ Assign scores based on percentile levels: +2 for >90%, +1 for 70%-90%, 0 for 30%-70%, -1 for 10%-30%, -2 for <10%[23][25] - **Fund Flows**: Calculate monthly active net inflows for indices and assess marginal changes. Assign +1 for positive changes and -1 for negative changes[26] - **Evaluation**: Provides a comprehensive view of asset trends, valuation, and fund flows[22][23][25] Fixed Proportion + Macro Indicators + Technical Indicators Combination Model - **Model Name**: Fixed Proportion + Macro Indicators + Technical Indicators Combination Model - **Construction Idea**: Adjust asset weights based on macro and technical indicators while maintaining a fixed proportion baseline[36][40] - **Construction Process**: - Set baseline weights for equity, bonds, commodities, and currency assets - Adjust weights monthly based on macro and technical indicator signals[36][40] - **Evaluation**: Balances fixed proportion allocation with dynamic adjustments for improved performance[36][40] Controlled Volatility + Macro Indicators + Technical Indicators Combination Model - **Model Name**: Controlled Volatility + Macro Indicators + Technical Indicators Combination Model - **Construction Idea**: Limit annualized volatility to 6% while dynamically adjusting weights based on macro and technical indicators[46][50] - **Construction Process**: - Use risk parity as the baseline weight - Adjust weights monthly based on macro and technical indicator signals[46][50] - **Evaluation**: Reduces volatility while maintaining competitive returns[46][50] Equity Style Rotation Models - **Model Name**: Equity Style Rotation Models (Large/Small Cap and Growth/Value) - **Construction Idea**: Adjust weights between equity styles based on macro and technical indicators[57][58] - **Construction Process**: - Set baseline weights for large/small cap and growth/value styles - Adjust weights monthly based on macro and technical indicator signals[57][58] - **Evaluation**: Captures style rotation opportunities for enhanced returns[57][58] --- Model Backtesting Results Macro Indicator Trend Model - **Annualized Return**: Not explicitly provided - **Maximum Drawdown**: Not explicitly provided - **Annualized Volatility**: Not explicitly provided Technical Perspective Model - **Annualized Return**: Not explicitly provided - **Maximum Drawdown**: Not explicitly provided - **Annualized Volatility**: Not explicitly provided Fixed Proportion + Macro Indicators + Technical Indicators Combination Model - **Annualized Return**: 10.20%[40] - **Maximum Drawdown**: 9.27%[40] - **Annualized Volatility**: 6.14%[40] Controlled Volatility + Macro Indicators + Technical Indicators Combination Model - **Annualized Return**: 10.46%[50] - **Maximum Drawdown**: 7.37%[50] - **Annualized Volatility**: 5.54%[50] Large/Small Cap Rotation Model - **Annualized Return**: 14.30%[61] - **Maximum Drawdown**: 49.10%[61] - **Annualized Volatility**: 22.30%[61] Growth/Value Rotation Model - **Annualized Return**: 14.43%[68] - **Maximum Drawdown**: 45.18%[68] - **Annualized Volatility**: 21.57%[68]

多家银行、交易所发布贵金属投资风险提示。未来市场走势如何，刚买的金饰能退吗? 这两天，国际贵金属市场迎来"惊魂时刻"，金价接连失守关键整数关口，日前单日跌幅超11% ；白银更 是以 31.37%的断崖式下跌，创下近46年来最差单日表现。 剧烈波动之下，工商银行、建设银行等多家国有大行、国内外交易所纷纷紧急发布风险提示，调整业务 规则。金价涨跌还将辐射哪些领域？刚入手金饰的消费者，能否申请退货减少损失？ 此次暴跌并非孤立事件，同期工业金属也受到波及，铜、锡、铝等品种均出现不同程度下跌，全球大宗 商品市场陷入震荡。事实上，此轮跳水在机构端早有端倪。 上周，易方达黄金主题上市型开放式基金（LOF）公告暂停A类份额的申购及定期定额投资业务。白银 上市型开放式基金（LOF）同样"闭门谢客"，国投白银上市型开放式基金1月28日起暂停申购及定期定 额投资业务。国泰君安期货贵金属高级研究员刘雨萱指出，如果继续敞开申购，新增资金只能以极高溢 价买入，一旦溢价回落，原有份额将被摊薄，之前的持有人利益将受损。 此后多家国有大行密集发声，发布贵金属业务风险提示，同时调整相关业务规则，防范市场波动带来的 风险。全球主要期货交易所持续加 ...

Core Viewpoint - In January, the global asset allocation logic shifted from valuation recovery to profit-driven, with A-shares continuing an upward trend supported by policies, funding, and valuation [1][2]. Group 1: A-share Market Performance - The A-share market showed a steady upward trend in January, with the Shanghai Composite Index rising by 3.76%, the ChiNext Index by 4.47%, and the Shenzhen Index by 5.03% by the end of January [2]. - The non-ferrous metals sector led the gains with a 22.59% increase, followed by media, oil and petrochemicals, construction materials, and basic chemicals with respective increases of 17.94%, 16.31%, 13.31%, and 12.72% [2]. Group 2: Fund Performance - Public FOFs (funds of funds) performed well, with some products achieving monthly returns exceeding 30%. For instance, the Guotai Industry Rotation A fund had a monthly return of 30.31%, while the Guotai Preferred Navigation fund reached 37.12% [3][5]. - A total of 35 FOFs had monthly performance exceeding 10%, with 4 funds surpassing 20% [3]. Group 3: Market Trends and Predictions - Analysts noted that the core drivers of asset performance in January were cross-year capital reallocation and sentiment recovery, with expectations of a "spring excitement" in the stock market in the first quarter [3][7]. - The transition from valuation-driven to profit-driven narratives in global asset allocation is expected to continue, with a focus on sectors showing clear performance improvements, particularly in technology and cyclical industries [7]. Group 4: Fund Issuance and Research Activity - The issuance of public funds accelerated in January, with a significant number of FOFs focusing on themes like technological innovation and high-end manufacturing, reflecting market interest in economic transformation opportunities [6][7]. - A total of 156 public fund institutions participated in A-share research activities in January, covering 486 stocks across 30 first-level industries, indicating high research engagement [7].