分析师 缪铃凯 SAC 证书编号：S0160525060003 miaolk@ctsec.com 相关报告 证券研究报告 金融工程专题报告 / 2026.03.01 核心观点 3 月配置：关注通信、有色、电子、汽车、军工 ❖ 风格轮动解决方案：大盘股对经济繁荣的表现更加敏感，成长股能够更好地 受益于流动性宽松，再辅佐以市场情绪指标，刻画市场风险偏好与拥挤度，通 过三维度多因子打分，构建风格轮动综合打分体系。 ❖ 风险提示：因子失效风险、模型失效风险、宏观环境变动风险 请阅读最后一页的重要声明！ 1. 《节后市场反弹，指增组合小幅波动》 2026-02-28 2. 《本周科创 50 涨幅较大，指增组合调整》 2026-02-15 3. 《本周市场调整，指增组合全面回暖》 2026-02-07 ❖ 根据 2026 年 02 月 28 日的最新数据，3 月价值成长轮动策略得出的综合分 数为 6，成长风格得分较高；大小盘轮动策略得出的综合分数为 2，小盘风格 得分较高。 ❖ 行业轮动解决方案：我们构造宏观经济指标、中观基本面指标、微观技术面 指标以及交易拥挤度指标四维引擎，以 10 个指标综合打分作为行业指数轮动 综 ...

- The report discusses the performance of major domestic market indices over the past week, with the SSE 50, CSI 300, CSI 500, and CSI 1000 indices showing varying degrees of change[2] - The micro-cap stock indicator monitoring includes a rotation strategy based on the relative net value of micro-cap stocks to the "Mao Index" and the 20-day closing price slope of the Wind micro-cap stock index[2][18] - The rotation strategy is currently in a balanced configuration, with part of the positions switching back to the micro-cap stock index based on the 20-day closing price slope and the M1 indicator's 6-month moving average[2][18] - The timing and risk control for micro-cap stocks are monitored using indicators such as the volatility congestion rate and the 10-year government bond yield, which are currently within controllable risk ranges[18][19] - The report also includes a summary of the macroeconomic environment, highlighting the impact of the 2026 Central No. 1 Document on agricultural asset capitalization and the "Happy New Year Shopping" initiative to boost domestic demand[3][37] - The overseas market is experiencing a divergence between manufacturing recovery and employment decline, with AI-driven infrastructure investments in copper and power equipment being seen as opportunities[4][38] - The report suggests a barbell strategy for tactical allocation, focusing on consumer services and AI-related sectors[4][38] - The report tracks the performance of various quantitative stock selection factors, noting that value and volume-price factors performed well, while growth and consensus expectation factors showed some pullback[5][52] - The report includes detailed construction and monitoring of convertible bond selection factors, with positive performance noted for stock value and convertible bond valuation factors[5][57] - The macro timing strategy model recommends a 70% equity position for February, with strong signals from economic growth and monetary liquidity[47][48]

Group 1 - The article emphasizes the importance of understanding different types of index funds, particularly bond index funds, which are less familiar to most investors compared to stock index funds [2] - It introduces four main categories of indices: broad-based indices, strategy indices, industry indices, and thematic indices [6] Group 2 - For broad-based index investment, it is crucial to consider the balance between large-cap and small-cap stocks, noting that in 2024, large-cap stocks like CSI 300 are expected to perform well while small-cap stocks may lag [8] - A classic combination for investment is the pairing of CSI 300 with CSI 500, and potentially adding CSI 1000 for more small-cap exposure [9] - In strategy index investment, it is important to balance growth and value styles, as A-shares exhibit a rotation between these styles over time [10][11] - The article highlights that from 2019 to 2020, growth style was strong, while from 2021 to 2024, value style is expected to dominate [12] Group 3 - Industry and thematic index investments are characterized by high volatility, with broad-based indices typically experiencing 20%-30% fluctuations annually, while industry indices can see 30%-50% volatility [13] - It is recommended to limit exposure to any single industry to 15%-20% to manage risk effectively [13] - The article advises investors to select long-term themes when investing in thematic indices, citing examples of past popular themes that may no longer be relevant [13]

Report Summary 1) Report Industry Investment Rating No information provided in the given content. 2) Core Viewpoints - The rotation wind vane consists of option market sentiment and traditional capital - related parts, and their resonance forms large/small - cap strength signals. Daily long - short operations on large and small caps can be carried out according to the signals, or use IM as the underlying position and adjust style exposure when the signal indicates that small caps are weak to achieve index enhancement. The September 2025 latest rotation wind vane signal shows option sentiment 1 and capital aspect - 1, suggesting to wait and see [1]. 3) Summary by Related Content Performance of Sub - strategies from 2025/4/1 - 2025/9/4 - For the 300/1000 long - short strategy, the interval return is 8.56%, the annualized return is 20.72%, the Calmar ratio is 5.39%, and the maximum drawdown is 3.84 [2]. - For the 1000 index enhancement strategy, the interval return is 13.21%, the annualized return is 32.93%, the Calmar ratio is 6.58%, and the maximum drawdown is 5.00 [2]. - For the CSI 1000, the interval return is 13.08%, the annualized return is 32.57%, the Calmar ratio is 12.44%, and the maximum drawdown is 2.62 [2].

Quantitative Models and Construction Methods 1. Model Name: Multi-dimensional Quantitative Rotation Model: Growth-Dividend Balanced Allocation - **Model Construction Idea**: This model aims to rotate between high-growth and dividend strategies based on effective single-factor signals, providing balanced allocation between growth and dividend styles[9] - **Model Construction Process**: - At the end of each month, the model selects effective signals from single-factor tests, including term spread, social financing growth, CPI and PPI quadrants, US Treasury yields, and capital flow dynamics (ETF, insurance funds, foreign capital)[9] - Each factor provides a buy signal for either high-growth or dividend strategies, and the average score across all factors is used as the final allocation score[9] - **Model Evaluation**: The model effectively captures market rotation opportunities, with strong performance in high-growth scenarios supported by improving macroeconomic indicators[9] 2. Model Name: Large-Cap vs. Small-Cap Rotation Model - **Model Construction Idea**: This model rotates between large-cap and small-cap styles based on macroeconomic and monetary indicators, aiming to exploit relative strength and momentum effects[24][29][35] - **Model Construction Process**: - **Monetary Cycle**: - Use short-term interest rates (Shibor3M and 1-year government bond yields) to classify monetary conditions as tight or loose[29] - Buy small-cap stocks during loose monetary conditions and large-cap stocks during tight conditions[29] - **Modified Monetary Activation Index**: - Use M1 and M2 growth rates and their scissors difference to classify market conditions into four quadrants[32] - Allocate between large-cap and small-cap stocks based on the quadrant classification[32] - **Relative Strength**: - Use moving averages to capture momentum; when the small-cap relative strength index crosses above its 9-month moving average, allocate to small-cap stocks, otherwise allocate to large-cap stocks[35] - **Model Evaluation**: The model demonstrates significant outperformance in capturing large-cap and small-cap rotation opportunities, with strong sensitivity to monetary conditions and momentum effects[29][32][35] --- Model Backtesting Results 1. Multi-dimensional Quantitative Rotation Model: Growth-Dividend Balanced Allocation - **Cumulative Return**: 348.20%[6] - **Annualized Return**: 17.35%[6] - **Maximum Drawdown**: 27.08%[6] - **Annualized Volatility**: 23.14%[6] - **Annualized Sharpe Ratio**: 0.75[6] - **Calmar Ratio**: 0.64[6] 2. Large-Cap vs. Small-Cap Rotation Model - **Cumulative Return**: 158.61%[22] - **Annualized Return**: 10.67%[22] - **Maximum Drawdown**: 32.46%[22] - **Annualized Volatility**: 21.01%[22] - **Annualized Sharpe Ratio**: 0.51[22] - **Calmar Ratio**: 0.33[22] --- Quantitative Factors and Construction Methods 1. Factor Name: Term Spread - **Factor Construction Idea**: Reflects fixed-income market expectations of future economic growth; widening spreads favor high-growth styles[13] - **Factor Construction Process**: - Calculate the spread between 10-year and 1-year government bond yields[13] - Use the monthly change in the spread as a signal for growth or dividend allocation[13] 2. Factor Name: Social Financing Growth - **Factor Construction Idea**: Serves as a leading macroeconomic indicator; higher growth supports high-growth styles[13] - **Factor Construction Process**: - Measure the year-over-year growth rate of total social financing stock[13] - Use the monthly change in growth rate as a signal for allocation[13] 3. Factor Name: CPI and PPI Quadrants - **Factor Construction Idea**: Captures inflation dynamics; CPI rising faster than PPI indicates strong downstream demand, favoring high-growth styles[17] - **Factor Construction Process**: - Classify market conditions into quadrants based on the year-over-year changes in CPI and PPI[17] - Allocate based on the quadrant classification[17] 4. Factor Name: US Treasury Yields - **Factor Construction Idea**: Reflects global risk appetite; higher yields negatively impact high-growth styles[17] - **Factor Construction Process**: - Use the level and trend of US 10-year Treasury yields as a signal for allocation[17] 5. Factor Name: Capital Flow Dynamics - **Factor Construction Idea**: Measures foreign capital inflows and domestic ETF flows; higher inflows support high-growth styles[18] - **Factor Construction Process**: - Construct a composite index using the USD index, RMB offshore exchange rate, and CDS spreads[18] - Use the index trend as a signal for allocation[18] --- Factor Backtesting Results 1. Term Spread - **Latest Value**: 0.40 (up from 0.32 last month)[13] 2. Social Financing Growth - **Latest Value**: 9% YoY (up from 8.9% last month)[13] 3. CPI and PPI Quadrants - **CPI**: 0% YoY (down from 0.1% last month)[17] - **PPI**: -3.6% YoY (unchanged from last month)[17] 4. US Treasury Yields - **Latest Value**: 4.26% (high-level oscillation)[17] 5. Capital Flow Dynamics - **Foreign Capital Inflow Index**: Strengthened due to RMB depreciation and CDS spread widening[18]

Core Insights - The median excess return of index-enhanced products has significantly improved compared to last year [1] - The China Securities 1000 index-enhanced products have shown particularly outstanding excess returns, followed by the China Securities 500 index-enhanced products [1] Group 1: Market Dynamics - The strong performance of public index-enhanced products this year is attributed to two main factors: accelerated rotation among market sectors and overall activity in small-cap stocks [1] - There is a noticeable cycle of rotation between large-cap and small-cap stocks in the Chinese market, with the current small-cap advantage cycle starting in 2021 [1] Group 2: Investment Strategy - Future index profitability and growth potential should be considered for index allocation, alongside short-term factors such as valuation and market sentiment [1]

Quantitative Models and Construction Methods DTW Timing Model - **Model Name**: DTW Timing Model - **Model Construction Idea**: The model is based on the principle of similarity and the DTW algorithm, focusing on price and volume timing[1][5][14] - **Model Construction Process**: - The model examines the similarity between current index trends and historical trends, selecting several historical segments with high similarity as references[25] - It calculates the weighted average future price change and weighted standard deviation of the selected historical segments (weights are the inverse of the distance)[25] - Based on the average future price change and standard deviation, trading signals are generated[25] - The model uses the DTW distance algorithm instead of the Euclidean distance for similarity measurement, as DTW distance can better handle time series mismatches[27] - Improved DTW algorithms such as Sakoe-Chiba and Itakura Parallelogram are introduced to overcome the "over-bending" issue in traditional DTW algorithms[29][30][35] - **Model Evaluation**: The model has shown stable excess returns in general market conditions, although it faced some drawdowns during periods of sudden macroeconomic policy changes[16] Foreign Capital Timing Model - **Model Name**: Foreign Capital Timing Model - **Model Construction Idea**: The model is based on the divergence between foreign and domestic related assets[1][14] - **Model Construction Process**: - The model uses two foreign-listed assets related to A-shares: FTSE China A50 Index Futures (Singapore market) and Southern A50 ETF (Hong Kong market)[34] - It constructs two indicators from FTSE China A50 Index Futures: premium and price divergence, forming the FTSE China A50 Index Futures timing signal[34] - It constructs a price divergence indicator from Southern A50 ETF, forming the Southern A50 ETF timing signal[34] - The timing signals from both assets are combined to form the foreign capital timing signal[34] - **Model Evaluation**: The model has shown good performance with high annualized returns and low maximum drawdowns[20][23] Model Backtest Results DTW Timing Model - **Absolute Return**: 25.79% since November 2022[5][16] - **Excess Return**: 16.83% relative to CSI 300[5][16] - **Maximum Drawdown**: 21.32%[5][16] - **Absolute Return (2024)**: 23.98% on CSI 300[18] - **Excess Return (2024)**: 2.76%[18] - **Maximum Drawdown (2024)**: 21.36%[18] - **Win Rate (2024)**: 53.85%[18] - **Profit-Loss Ratio (2024)**: 2.93[18] Foreign Capital Timing Model - **Absolute Return (2024)**: 29.11% for long strategy[5][23] - **Maximum Drawdown (2024)**: 8.32% for long strategy[5][23] - **Annualized Return (2014-2024)**: 18.96% for long-short strategy, 14.19% for long strategy[20] - **Maximum Drawdown (2014-2024)**: 25.69% for long-short strategy, 17.27% for long strategy[20] - **Daily Win Rate (2014-2024)**: Nearly 55%[20] - **Profit-Loss Ratio (2014-2024)**: Both exceed 2.5[20]

Core Viewpoint - The market shows signs of recovery with small and micro-cap stocks performing better than large-cap stocks, indicating a potential shift in investment strategies towards growth sectors, particularly technology and healthcare [1][9][22]. Group 1: Market Performance - The overall market experienced a slight increase, maintaining a five-star rating [1]. - Small and micro-cap stocks saw a more significant rise compared to large-cap stocks [2][9]. - Growth styles, especially in technology themes, led the market gains [3]. - The value style showed a modest increase [4]. - Hong Kong stocks also experienced an overall rise, with the technology index leading the gains [5][6]. Group 2: Earnings and Valuation - In 2023, small-cap indices outperformed large-cap indices, reversing the trend seen in the previous year [9][12]. - The profitability of small companies has been more adversely affected by economic cycles, with the CSI 1000 index showing a nearly 18% decline in earnings for 2023 and a further 2% decline projected for 2024 [15][14]. - The price-to-earnings ratio for the CSI 1000 index has increased due to declining earnings, reaching over 50% of its 10-year average, indicating a relatively high valuation [18]. - Despite the high P/E ratio, the net asset value continues to grow, resulting in a lower price-to-book ratio, which remains within the 15-20% range of the past decade [20][21]. Group 3: Recovery Signs - In Q1 of this year, both A-shares and Hong Kong stocks showed signs of earnings recovery, with Hong Kong's Hang Seng Index reporting a 16% year-on-year increase in earnings [22][23]. - Small-cap stocks in A-shares also exhibited strong earnings growth, with the CSI 1000 index showing a 16% increase in Q1 [24]. - The technology and healthcare sectors are leading the earnings growth, contributing to the recent performance of both A-shares and Hong Kong stocks [26][27]. - If earnings continue to grow in Q2, there may be upward potential for the market [31]. Group 4: Volatility and Risks - Recent gains in small and micro-cap stocks have led to increased volatility risks, which are significantly higher than those for large-cap stocks [33]. - Historical data shows that small-cap indices can experience sharp declines, as evidenced by a drop of over 30% in January of last year [34]. - The influence of short-term capital flows on small-cap stocks is pronounced, particularly in indices like CSI 1000 and CSI 2000 [35][36]. - Changes in regulations affecting quantitative funds could further impact the volatility of small-cap stocks [38][40].

关键因素 图利 绝对差值和边际变化 重要指标 II 价值成长轮动策略 II 深圳证券交易所 ( SHENZHEN STOCK EXCHANGE 深交所ETF投资问答(42) 如何的身上了 II t FE ALKE 0 n - 编者按 - 近年来我国指数型基金迅速发展,交易型开 放式指数基金(ETF) 备受关注。为帮助广 大投资者系统全面认识ETF,了解相关投资 方法,特摘编由深圳证券交易所基金管理部 编著的《深交所ETF投资问答》（中国财政 经济出版社2024年版）形成图文解读。本 篇是第42期,一起来看看如何通过ETF构建 风格配置策略。 风格轮动是依据ETF特征进行交易的 行为，常见的风格轮动有大小盘轮动、 成长价值轮动等。风格轮动的分析框 架需要对比指数间的相对强弱，因此 预测难度更大。 II 影响风格轮动强弱的因素 II 价值和成长两类股票具有明显基本面 的差异。 价值类股票往往具备更好 的安全边际 成长类股票则可能具备更 好的盈利前景 观察风格间的相对业绩增速趋势,有 助于进行风格配置。除此之外，市场 中也有投资者通过估值指数来衡量价 值与成长之间的风格轮动。 u 大小鱼论动策略 ! 大小盘轮动通常 ...

- The DTW timing model is based on the principle of similarity and the DTW (Dynamic Time Warping) algorithm, which is a volume-price timing model[1][4][14] - The foreign capital timing model is constructed based on the divergence between foreign and domestic related assets, using four indicators reflecting foreign capital movements to generate timing signals for the A-share market[1][4][14] - The DTW timing model has shown an absolute return of 17.39% and an excess return of 17.83% relative to the CSI 300 since November 2022, with a maximum drawdown of 21.32% and a weekly win rate of over 60%[4][16] - The foreign capital timing model's long strategy has achieved an absolute return of 28.83% since 2024, with a maximum drawdown of 8.32%[4][23] - The DTW timing model uses the DTW distance algorithm instead of the Euclidean distance to measure similarity, as the DTW distance can better handle the misalignment of time series[29][30] - The DTW timing model has been improved by incorporating boundary constraints proposed by Sakoe-Chiba and Itakura to address the "pathological matching" problem of the traditional DTW algorithm[31][32][37] - The foreign capital timing strategy is based on two overseas listed assets related to A-shares: FTSE China A50 Index Futures (Singapore market) and Southern A50ETF (Hong Kong market), constructing timing signals through price divergence and premium/discount indicators[36][12] - The DTW timing model's performance in 2024 includes an absolute return of 15.68%, an excess return of 4.93%, a maximum drawdown of 21.36%, a trading win rate of 63.64%, and a profit-loss ratio of 2.64[18][19][20] - The foreign capital timing model's performance from December 30, 2014, to December 31, 2024, shows an annualized return of 18.96% (long-short) and 14.19% (long-only), with maximum drawdowns of 25.69% and 17.27%, respectively, and a daily win rate of nearly 55%[20][22][24]