[Table_Title] 研究报告 Research Report 7 Dec 2025 中国策略 China Strategy 政策窗口临近，市场反弹动能有望延续 Policy Window Approaching, Market Rebound Momentum Likely to Continue 周林泓 Amber Zhou 李加惠 Jiahui Li, CFA [Table_yemei1] 观点聚焦 Investment Focus [Table_summary] (Please see APPENDIX 1 for English summary) 上周我们认为市场整固后有望延续反弹，科技修复仍有空间。本周港股与 A 股市场缩量震荡后于周五拉升，市场开 始关注中国政策窗口；有色金属受国际金属价格大涨带动表现最强，科技中以算力为代表的相关个股也表现相对 活跃。 下周市场将面临三大关键事件：政治局会议、中央经济工作会议以及美联储议息会议，市场波动可能加大。周五 市场已开始提前交易政治局会议释放宽松货币政策与积极财政政策信号的预期。同时，市场对政策支持长期资金 入市的预期进一步升温，周五金管总局正式下 ...

Quantitative Models and Construction Methods 1. Model Name: Industry Mainline Model (Relative Strength Index, RSI) - **Model Construction Idea**: The model aims to identify leading industries by calculating their relative strength index (RSI) over different time frames[1][9] - **Model Construction Process**: 1. Use primary industry indices as configuration targets, totaling 31 primary industries 2. Calculate the price changes over the past 20, 40, and 60 trading days for all industries, obtaining the cross-sectional rankings of these changes, then normalize all rankings to get RS_20, RS_40, and RS_60 3. Calculate the average of these three rankings to get the final industry relative strength index: $$ RS = \frac{RS_{20} + RS_{40} + RS_{60}}{3} $$ 4. If an industry shows an RS signal greater than 90% before the end of April, it is likely to be a leading industry for the year[9] - **Model Evaluation**: The model effectively identified leading industries in 2024, such as coal, power and utilities, home appliances, banks, oil and petrochemicals, communications, non-ferrous metals, agriculture, forestry, animal husbandry, and fishery, and automobiles[1][9] 2. Model Name: Industry Rotation Model (Prosperity-Trend-Crowding Framework) - **Model Construction Idea**: The model uses a three-dimensional framework of prosperity, trend, and crowding to recommend industry allocations[1][2][6] - **Model Construction Process**: 1. Define two industry rotation schemes: "strong trend-low crowding" and "high prosperity-strong trend" 2. Allocate industry weights based on the framework: Media 16%, Agriculture, Forestry, Animal Husbandry, and Fishery 15%, Non-bank Financials 12%, Computers 12%, Home Appliances 9%, Coal 9%, Building Materials 7%, Banks 7%, Light Industry Manufacturing 7%, Retail 6% 3. Recommend ETFs tracking indices such as CSI Steel, CSI Agriculture, Securities Companies, Communication Equipment, CSI Media, Sub-segment Chemicals, CS Artificial Intelligence, Animation Games, Sub-segment Machinery, All Information, Building Materials, etc.[2][6][15] - **Model Evaluation**: The model performed well in 2025, with an excess return of 16.4% relative to the CSI 800 index and 4.2% relative to the Wind All A index[2][6][18] 3. Model Name: Left-Side Inventory Reversal Model - **Model Construction Idea**: The model aims to capture the reversal of industries in distress by analyzing sectors with low inventory pressure and long-term analyst optimism[24] - **Model Construction Process**: 1. Identify sectors currently or previously in distress with potential for inventory replenishment 2. Analyze sectors with low inventory pressure and long-term analyst optimism 3. Recommend sub-sectors such as cloud services, other light industries, oil service engineering, components, agricultural chemicals, animal husbandry, consumer electronics, special materials, and biomedicine[24][25] - **Model Evaluation**: The model achieved an absolute return of 25.4% in 2025, with an excess return of 5.4% relative to the industry equal weight index[24][27] Model Backtest Results 1. Industry Mainline Model (RSI) - **Absolute Return**: Various industries showed significant returns after the RSI signal appeared, such as banks (32.1%), communications (24.0%), home appliances (25.8%), and automobiles (12.8%)[10][12] 2. Industry Rotation Model (Prosperity-Trend-Crowding Framework) - **Annualized Return**: 21.7% - **Excess Annualized Return**: 13.8% - **Information Ratio (IR)**: 1.5 - **Maximum Drawdown**: -8.0% - **Monthly Win Rate**: 67% - **Excess Return in 2023**: 7.3% - **Excess Return in 2024**: 5.7% - **Excess Return in 2025**: 4.2%[13][14] 3. Left-Side Inventory Reversal Model - **Absolute Return in 2023**: 13.4% - **Excess Return in 2023**: 17.0% - **Absolute Return in 2024**: 26.5% - **Excess Return in 2024**: 15.4% - **Absolute Return in 2025**: 25.4% - **Excess Return in 2025**: 5.4%[24][27]

Core Insights - The report suggests that the "spring surge" market is expected to start earlier, driven by the gradual implementation of US-China policy expectations, with a focus on growth sectors [1][9] - The upcoming Federal Reserve's interest rate cut in December is anticipated to be a key factor for market sentiment, alongside the political bureau meeting and economic work conference in December, which are expected to set the tone for next year's policies [1][9] - The report emphasizes that growth style has historically outperformed value style during the spring surge periods, with growth style ranking first in 10 out of 21 years analyzed [1][21][22] Market Overview - The A-share market is currently experiencing a mixed upward trend, with the ChiNext index leading gains, supported by favorable policies and market sentiment [9] - The manufacturing PMI for November was reported at 49.2%, indicating a slight recovery but still in the contraction zone, highlighting the need for further policy support [9][13] - The report notes that the market is expected to continue its upward trajectory next year, supported by valuation and profit stabilization, with a bullish outlook for the A-share market [1][9] Industry Insights - The report identifies a clear differentiation in industry performance, with resource and technology sectors leading gains, while consumer and low-risk preference sectors lag behind [19] - The adjustment of risk factors for insurance companies is expected to lower capital costs for equity investments, particularly benefiting high-growth sectors like the STAR Market [1][19] - The launch of the Doubao mobile assistant is seen as a significant turning point for mobile interaction modes, potentially driving a wave of device upgrades in the next 1-3 years [1][28][29] Investment Recommendations - The report recommends focusing on stocks within the CSI Dividend Low Volatility 100 index, particularly those not included in the CSI 300, as they are expected to benefit the most from the recent adjustments in risk factors [1][19] - The AI sector is highlighted as a key area for investment, with expectations of continued growth driven by advancements in AI applications and ecosystem development [1][30][34]

Investment Rating - The industry investment rating is "Accumulate (Maintain)" [1] Core Insights - The report discusses the issuance of the "Guidelines for Performance Evaluation Management of Fund Management Companies (Draft for Comments)", aimed at standardizing performance evaluation and compensation management in the fund industry, promoting sustainable development [4] - Key changes in performance evaluation include: 1) Strengthening performance assessment with profit ratios linked to multiple indicators 2) Requiring at least 30% of the annual performance compensation for executives to be invested in the company's funds, and at least 40% for fund managers 3) Implementing a salary reduction for fund managers who underperform by 10% against benchmarks over three years with negative profit margins [4] - The guidelines emphasize long-term performance metrics, with at least 80% of the weight on three-year or longer investment returns for fund investment performance indicators [4] - The report highlights the regulatory consistency in public fund reforms, with the China Securities Regulatory Commission (CSRC) reinforcing the need for a performance and compensation system centered on fund investment returns [4] Summary by Sections - **Performance Evaluation Changes**: The new guidelines increase the proportion of performance-linked compensation for executives and fund managers, with a focus on long-term investment performance [4] - **Regulatory Environment**: The report indicates a continued commitment from regulators to reform the public fund industry, ensuring that performance assessments are closely tied to long-term results [4] - **Industry Development**: The guidelines aim to bind employee incentives to long-term fund performance, fostering a healthier industry environment [4]

Market Overview - A-shares exhibited a trend of shrinking volume and fluctuations from December 1 to 5, with the Shanghai Composite Index rising by 0.37%, the Shenzhen Component Index increasing by 1.26%, and the ChiNext Index up by 1.86% [1] - The overall sentiment in the A-share market showed a structural characteristic of "index stabilization and recovery, shrinking trading volume, moderate leverage funding increase, and weakening southbound capital" [1] - The average stock price across the A-share market increased by 0.72% [1] Sector Performance - The commercial aerospace sector stood out this week, with stocks in this area experiencing significant upward movement and becoming a focal point for capital [1] - CICC noted that the global commercial aerospace sector is thriving, driving a continuous increase in rocket launch demand, suggesting investors pay close attention to developments in this field [1] IPO Highlights - The listing of Moore Threads, a leading domestic full-function GPU company, attracted significant market attention, with its share price soaring over 425% on the first day of trading, setting multiple historical records in the A-share market [2] - The closing price of Moore Threads was 600.5 yuan per share, resulting in a profit of approximately 243,100 yuan for investors who subscribed to one lot, marking the highest profit on the first day of an A-share IPO [2] Market Outlook - Guolian Minsheng anticipates that the spring market rally typically begins between late December and mid-January, with the median start point being 11 trading days before the holiday [2] - According to招商证券, the end of the year and the beginning of the new year will see an increase in incremental capital, making December a prime time for positioning [2] Policy and Economic Indicators - The market is approaching a policy window in December, with expectations for the "14th Five-Year Plan" recommendations to be implemented, and an expansion in the scale of special bonds anticipated [3] - The upcoming Federal Reserve meeting on December 10 is expected to influence market liquidity, with a potential rate cut anticipated [3] - Key economic data releases in December include import and export figures, CPI and PPI data, and financial indicators such as new RMB loans and social financing scale [4][5][6][7]

- The **cyclical analysis model** suggests that despite previous market adjustments and a short-term upward channel breakdown, the monthly upward trend since early 2024 may still persist. This conclusion is supported by comparing the current market structure with the 2017 December trend using **Chan theory** and the **thermometer indicator** for similarity analysis[6] - The **trend strength factor** indicates that since the end of November, the oversold rebound has significantly improved the multi-moving average alignment, leading to a notable recovery in upward trend strength. This supports the view of a moderately positive market outlook[6] - The **industry divergence indicator** has dropped to historically low levels in recent years. Historical data shows that during bull markets or upward trends, low levels of industry divergence often correspond to local lows or even significant bottoms, which is a key basis for maintaining a positive outlook for December[6] - The **four-wheel drive model** signals are relatively dispersed, with notable performances in large-cap value, small-cap growth, technology, and high-dividend sectors. Specific signals on Thursday and Friday highlighted opportunities in non-bank financials, China New Materials, and defense sectors[6][15]

Market Overview - The A-share market from December 1 to December 5, 2025, showed varied performance with the top three broad indices being Shenzhen Dividend (+0.79%), ChiNext (+0.54%), and Shanghai 50 (+0.28%) while the bottom three were Wind Micro-Pan Index (-1.20%), Sci-Tech 50 (-0.80%), and Sci-Tech Composite Index (-0.75%) [13] - The performance of style indices ranked middle value (+1.65%), mid-growth (+1.49%), and cyclical (+0.93%) at the top, while consumer (-0.97%), small-cap growth (-0.75%), and growth (-0.59%) were at the bottom [15] - Among the Shenwan first-level industry indices, non-ferrous metals (+2.42%), non-bank financials (+2.24%), and machinery (+2.10%) led, while media (-4.67%), beauty care (-2.41%), and computers (-2.35%) lagged [18] Market Outlook - The macro timing model for December 2025 scored -2, indicating a historical probability of adjustment for the Wind All A Index, but any potential adjustment space is expected to be limited [24] - The market is anticipated to continue a bottoming phase with weak rebounds, particularly in the non-ferrous metals and communications sectors, but trading volume is decreasing, indicating weak buying and selling intentions [24] - Caution is advised for micro-pan directions as historical data shows weak performance in December, and recent high-level stocks have shown unusual movements [24] Fund Allocation Recommendations - A balanced and slightly aggressive ETF allocation is recommended based on the current market conditions [64] - The report suggests that the market may remain in a range-bound oscillation, necessitating patience for a larger-scale rebound [62] Risk Warnings - The model is based on historical data, which may become ineffective in the future [68] - There is a risk of macroeconomic performance falling short of expectations [68] - Unexpected macro events could significantly impact market conditions [68]

Core Insights - The report indicates that the current market is experiencing a prolonged period of low trading volume, which is not necessarily a bearish signal in a bull market. Historical data shows that low trading volumes often coincide with market lows during bull markets [2][10][11] - The report highlights the significance of the year-end effect, particularly the cross-year market trend, which may start in December 2025. Historical patterns suggest that if the index is low, the cross-year rally tends to start earlier and with greater magnitude [3][18][21] - It is anticipated that there will likely be a cross-year market rally in 2026, with December 2025 serving as a potential window for positioning. The macroeconomic outlook is weak, providing room for more robust growth policies to emerge [23][24] Market Changes - The report notes that all major A-share indices rose this week, with the ChiNext 50 index increasing by 2.58% and the ChiNext index by 1.86%. In contrast, sectors such as media and real estate saw declines [32] - The report mentions that the net inflow of southbound funds (Hong Kong Stock Connect) totaled 10.303 billion yuan this week, indicating continued interest in A-shares [34] Investment Recommendations - The report suggests focusing on sectors such as non-bank financials, electric power equipment, and machinery, which are expected to benefit from a potential bull market. The non-bank financial sector is highlighted for its low valuation and potential for significant returns as resident funds flow in [30][31] - The report emphasizes the importance of monitoring policy changes and economic data, as these factors will influence market dynamics and investment opportunities in the coming months [24][25]

Quantitative Models and Construction Methods - **Model Name**: PB-ROE-50 **Model Construction Idea**: The model is based on the combination of Price-to-Book ratio (PB) and Return on Equity (ROE) to select stocks with high profitability and reasonable valuation[23] **Model Construction Process**: The PB-ROE-50 portfolio is constructed by selecting stocks with the top 50 combined scores of PB and ROE. The portfolio is rebalanced periodically, and adjustments are made based on the stock universe of different indices such as CSI 500 and CSI 800[23] **Model Evaluation**: The model demonstrates positive excess returns in specific stock pools, indicating its effectiveness in capturing value and profitability factors[23] - **Model Name**: Block Trade Portfolio **Model Construction Idea**: The model is based on the principle that stocks with higher block trade transaction ratios and lower 6-day transaction amount volatility tend to perform better subsequently[29] **Model Construction Process**: The portfolio is constructed by selecting stocks with high block trade transaction ratios and low 6-day transaction amount volatility. The portfolio is rebalanced monthly[29] **Model Evaluation**: The model captures the information embedded in block trades, but its performance varies depending on market conditions[29] - **Model Name**: Private Placement Portfolio **Model Construction Idea**: The model is based on the event-driven strategy of private placements, considering factors such as market capitalization, rebalancing cycles, and position control[35] **Model Construction Process**: The portfolio is constructed using the announcement date of private placements as the event trigger. Stocks are selected based on their market capitalization and other factors, and the portfolio is rebalanced periodically[35] **Model Evaluation**: The model's performance is influenced by regulatory changes and market sentiment, showing mixed results in different periods[35] --- Model Backtesting Results - **PB-ROE-50 Model** - CSI 500: Weekly excess return 0.76%, absolute return 1.71%; YTD excess return 2.84%, absolute return 27.48%[24] - CSI 800: Weekly excess return 0.21%, absolute return 1.40%; YTD excess return 15.39%, absolute return 36.63%[24] - All Market: Weekly excess return -0.09%, absolute return 0.68%; YTD excess return 18.22%, absolute return 43.75%[24] - **Block Trade Portfolio** - Weekly excess return -0.16%, absolute return 0.61%; YTD excess return 39.03%, absolute return 69.06%[30] - **Private Placement Portfolio** - Weekly excess return -2.30%, absolute return -1.55%; YTD excess return -5.43%, absolute return 15.00%[36] --- Quantitative Factors and Construction Methods - **Factor Name**: Profitability Factor (e.g., ROA, ROE) **Factor Construction Idea**: Measures the company's profitability and operational efficiency, such as Return on Assets (ROA) and Return on Equity (ROE)[12][13][14] **Factor Construction Process**: - ROA: Calculated as $ \text{ROA} = \frac{\text{Net Income}}{\text{Total Assets}} $ - ROE: Calculated as $ \text{ROE} = \frac{\text{Net Income}}{\text{Shareholder's Equity}} $ **Factor Evaluation**: Profitability factors generally show positive returns, especially in CSI 300 and CSI 500 stock pools[12][14] - **Factor Name**: Valuation Factor (e.g., PB, PE, EP) **Factor Construction Idea**: Reflects the valuation level of stocks, such as Price-to-Book ratio (PB), Price-to-Earnings ratio (PE), and Earnings Yield (EP)[12][14][16] **Factor Construction Process**: - PB: Calculated as $ \text{PB} = \frac{\text{Market Price per Share}}{\text{Book Value per Share}} $ - PE: Calculated as $ \text{PE} = \frac{\text{Market Price per Share}}{\text{Earnings per Share}} $ - EP: Calculated as $ \text{EP} = \frac{\text{Earnings per Share}}{\text{Market Price per Share}} $ **Factor Evaluation**: Valuation factors like PB and EP show significant positive returns in multiple industries[21] - **Factor Name**: Momentum Factor (e.g., 5-day Reversal, 1-month Momentum) **Factor Construction Idea**: Captures the trend-following or reversal behavior in stock prices over short-term periods[12][14][16] **Factor Construction Process**: - 5-day Reversal: Measures the return reversal over the past 5 days - 1-month Momentum: Measures the cumulative return over the past month **Factor Evaluation**: Momentum factors show mixed performance, with some negative returns in specific stock pools[12][14][16] - **Factor Name**: Liquidity Factor (e.g., Turnover Rate, Transaction Amount Volatility) **Factor Construction Idea**: Reflects the liquidity characteristics of stocks, such as turnover rate and transaction amount volatility[12][14][16] **Factor Construction Process**: - Turnover Rate: Calculated as $ \text{Turnover Rate} = \frac{\text{Trading Volume}}{\text{Total Shares Outstanding}} $ - Transaction Amount Volatility: Standard deviation of transaction amounts over a specific period **Factor Evaluation**: Liquidity factors generally show positive returns, especially in the CSI 500 and liquidity 1500 stock pools[12][14][16] --- Factor Backtesting Results - **Profitability Factors** - ROA: Weekly return 1.43% (CSI 300), 0.78% (CSI 500), 1.01% (Liquidity 1500)[12][14][16] - ROE: Weekly return 1.32% (CSI 300), 0.94% (CSI 500), 0.71% (Liquidity 1500)[12][14][16] - **Valuation Factors** - PB: Weekly return 0.67% (CSI 300), 0.77% (CSI 500), 1.06% (Liquidity 1500)[12][14][16] - EP: Weekly return -0.37% (CSI 300), 0.17% (CSI 500), 0.84% (Liquidity 1500)[12][14][16] - **Momentum Factors** - 5-day Reversal: Weekly return -1.25% (CSI 300), -0.48% (CSI 500), -1.44% (Liquidity 1500)[12][14][16] - 1-month Momentum: Weekly return 0.45% (CSI 300), 0.59% (CSI 500), 1.20% (Liquidity 1500)[12][14][16] - **Liquidity Factors** - Turnover Rate: Weekly return 0.75% (CSI 300), 1.68% (CSI 500), 0.84% (Liquidity 1500)[12][14][16] - Transaction Amount Volatility: Weekly return 0.47% (CSI 300), 1.01% (CSI 500), 0.56% (Liquidity 1500)[12][14][16]

- The report does not contain any quantitative models or factors for analysis[1][2][3]