1. Report Industry Investment Rating There is no information provided in the report regarding the industry investment rating. 2. Core Views of the Report - On November 14, the convertible bond market contracted in volume and declined, with compressed valuations. The CSI Convertible Bond Index decreased by 0.58% compared to the previous day, and the trading sentiment in the convertible bond market weakened. The total trading volume of the convertible bond market was 71.351 billion yuan, a 9.71% decrease from the previous day [1]. - The convertible bond price center declined, and the proportion of high - priced bonds decreased. The overall weighted average closing price of convertible bonds was 135.02 yuan, a 0.64% decrease from the previous day. The valuation was compressed, with the 100 - yuan par - value fitted conversion premium rate at 31.82%, a 0.82 - percentage - point decrease from the previous day [2]. - In the stock market, more than half of the underlying stock industry indices declined. Among A - share markets, the top three industries with the largest declines were electronics (-3.09%), communication (-2.46%), and media (-2.16%); the top three industries with the largest increases were real estate (+0.39%), banking (+0.26%), and pharmaceutical biology (+0.17%). In the convertible bond market, 23 industries declined, with the top three industries with the largest declines being communication (-2.52%), national defense and military industry (-1.85%), and automobile (-1.66%); the top three industries with the largest increases were steel (+2.31%), environmental protection (+0.82%), and public utilities (+0.27%) [3]. 3. Summary by Relevant Catalogs Market Overview - **Index Performance**: The CSI Convertible Bond Index decreased by 0.58% compared to the previous day, the Shanghai Composite Index decreased by 0.97%, the Shenzhen Component Index decreased by 1.93%, the ChiNext Index decreased by 2.82%, the SSE 50 Index decreased by 1.15%, and the CSI 1000 Index decreased by 1.16% [1]. - **Market Style**: Large - cap value stocks were relatively dominant. Large - cap growth stocks decreased by 2.20%, large - cap value stocks decreased by 0.55%, mid - cap growth stocks decreased by 1.48%, mid - cap value stocks decreased by 1.19%, small - cap growth stocks decreased by 1.45%, and small - cap value stocks decreased by 0.85% [1]. - **Fund Performance**: The trading sentiment in the convertible bond market weakened. The trading volume of the convertible bond market was 71.351 billion yuan, a 9.71% decrease from the previous day; the total trading volume of the Wind All - A Index was 1980.382 billion yuan, a 4.13% decrease from the previous day; the net outflow of the main funds in the Shanghai and Shenzhen stock markets was 62.011 billion yuan, and the yield of the 10 - year treasury bond increased by 0.14 bp to 1.81% [1]. Convertible Bond Price and Valuation - **Convertible Bond Price**: The overall weighted average closing price of convertible bonds was 135.02 yuan, a 0.64% decrease from the previous day. The closing price of equity - biased convertible bonds was 178.79 yuan, a 1.27% decrease; the closing price of bond - biased convertible bonds was 121.53 yuan, a 0.10% decrease; the closing price of balanced convertible bonds was 130.91 yuan, a 0.31% decrease. The proportion of high - priced bonds above 130 yuan was 62.34%, a 0.75 - percentage - point decrease from the previous day. The price median was 133.72 yuan, a 0.93% decrease from the previous day [2]. - **Convertible Bond Valuation**: The valuation was compressed. The 100 - yuan par - value fitted conversion premium rate was 31.82%, a 0.82 - percentage - point decrease from the previous day; the overall weighted par value was 104.59 yuan, a 0.52% decrease from the previous day. The premium rate of equity - biased convertible bonds was 10.60%, a 1.34 - percentage - point decrease; the premium rate of bond - biased convertible bonds was 84.51%, a 0.54 - percentage - point decrease; the premium rate of balanced convertible bonds was 22.78%, a 0.24 - percentage - point decrease [2]. Industry Performance - **Underlying Stock Industry**: Among A - share markets, the top three industries with the largest declines were electronics (-3.09%), communication (-2.46%), and media (-2.16%); the top three industries with the largest increases were real estate (+0.39%), banking (+0.26%), and pharmaceutical biology (+0.17%) [3]. - **Convertible Bond Industry**: In the convertible bond market, 23 industries declined, with the top three industries with the largest declines being communication (-2.52%), national defense and military industry (-1.85%), and automobile (-1.66%); the top three industries with the largest increases were steel (+2.31%), environmental protection (+0.82%), and public utilities (+0.27%) [3]. - **Key Indicators by Sector**: - Closing price: The large - cycle sector decreased by 0.15%, the manufacturing sector decreased by 1.11%, the technology sector decreased by 1.59%, the large - consumption sector decreased by 0.64%, and the large - finance sector decreased by 0.66% [3]. - Conversion premium rate: The large - cycle sector decreased by 0.57 percentage points, the manufacturing sector decreased by 0.37 percentage points, the technology sector increased by 0.3 percentage points, the large - consumption sector decreased by 0.29 percentage points, and the large - finance sector increased by 0.051 percentage points [3]. - Conversion value: The large - cycle sector increased by 0.51%, the manufacturing sector decreased by 0.87%, the technology sector decreased by 1.74%, the large - consumption sector decreased by 0.64%, and the large - finance sector decreased by 1.01% [3]. - Pure bond premium rate: The large - cycle sector decreased by 0.23 percentage points, the manufacturing sector decreased by 1.7 percentage points, the technology sector decreased by 2.3 percentage points, the large - consumption sector decreased by 0.82 percentage points, and the large - finance sector decreased by 0.79 percentage points [4].

- The report tracks various market factors, including stock market, commodity market, options market, and convertible bond market, focusing on their weekly performance and trends[1][3][12] - **Stock Market Factors**: The report highlights the following: - **Market Style**: Small-cap stocks outperformed large-cap stocks, and value stocks outperformed growth stocks. Both small-cap and value-growth style volatilities decreased[12][14] - **Market Structure**: Industry excess return dispersion and industry rotation speed increased. The proportion of rising constituent stocks also increased, while the concentration of trading in the top 100 stocks and top 5 industries decreased[12][14] - **Market Activity**: Both market volatility and turnover rate declined[13][14] - **Commodity Market Factors**: Key observations include: - **Trend Strength**: The trend strength of agricultural products decreased, while other sectors showed minimal changes[24][31] - **Basis Momentum**: Basis momentum increased across all sectors[24][31] - **Volatility**: Volatility decreased across all sectors except agricultural products[24][31] - **Liquidity**: Liquidity declined across all sectors[24][31] - **Options Market Factors**: The implied volatility levels of SSE 50 and CSI 1000 options decreased. However, the put-call open interest ratio increased. Additionally, the skewness of both put and call options for SSE 50 rose significantly[35] - **Convertible Bond Market Factors**: The convertible bond market performed well, with the following trends: - The premium rate of bonds priced around 100 yuan increased significantly, nearing the 90th percentile of the past year[37] - The premium rate of pure debt bonds also slightly increased, while the proportion of low premium rate bonds remained stable[37] - Weekly trading volume continued to recover[37]

（来源：望京博格投基） 转自：望京博格投基 中午吃饭的时候，群里面大户惊叹的说： 结果今天化工大涨3.7%，关键价格比之前止盈的价格还要高7%，大户觉得自己卖飞了。 博格的心情比较平静的，因为后来买的绿电收益也有6%左右，化工+绿电轮动浮盈超过20%的，这个收 益还是可以接受的。 "化工涨得比创新药还多？" 看到这个，博格大概率猜到了。 博格之前私域发车抄底化工，这个大户跟车了； 化工盈利了15%之后，博格清仓止盈了，这个大户也跟车了。 博格后来又抄底绿电了，这个大户没有跟车。 "港股创新药持仓36.6万，盈利93.73% PS：算上今天的收益应该超100%了 博格一直看好创新药，在4月7日的时候，重仓买入这个ETF，之后一路上涨，累计收益率一度达到 110%。 在7月底的时候，博格还减仓了5-6万的港股创新药，计划等着创新药之后再减仓一点。 结果国庆之后开始回调又亏了不少浮盈，索性继续持有吧，等后面创新药了再减仓一些。" 年底是创新药BD大单的密集期，期望港股创新药可以继续涨。 临近发稿的时候，港股创新药涨幅为4.76%，这个涨幅比化工涨幅高多了。 再看看创新药的估值，最新市盈率为31.83倍，处于最近十年 ...

Core Viewpoint - The article discusses the launch of the "Institutional Express" ETF investment tool by Ping An Securities and Tianhong Fund, aimed at helping ordinary investors navigate the fast-changing A-share market and capitalize on investment opportunities driven by institutional investors [1][4]. Group 1: Product Overview - "Institutional Express" is designed to track institutional fund flows and preferences, identifying potential industries of interest for investors [4]. - The tool utilizes a strategy model developed by Tianhong Fund, focusing on four key institutional factors: sell-side analyst expectations, buy-side institutional research, ETF fund flows, and large orders of index constituent stocks [4]. - The model processes data through normalization to create a unified scoring system, generating "strong indices" and "rotation signals" for investment decisions [4]. Group 2: Performance Metrics - The backtesting results from October 17, 2024, to October 23, 2025, show that "Institutional Express" achieved a return of 47.40%, significantly outperforming the CSI 300 index, which returned 16.39% during the same period [8]. - The maximum drawdown for "Institutional Express" was 19.42%, compared to 13.42% for the CSI 300 index, indicating a higher risk profile [8]. Group 3: User Accessibility - The tool is designed to be user-friendly, allowing investors to easily access top industry signals and corresponding ETF products through the Ping An Securities APP [11]. - Since the launch of the ETF section in 2022, the platform has served over ten million users, continuously updating its features based on market sentiment and user feedback [11].

- The diffusion index model tracks industry rotation based on momentum principles, focusing on upward trends in industry performance. It has been monitored for four years, with notable performance in 2021 achieving excess returns of over 25% before a significant drawdown in September due to cyclical stock adjustments. In 2025, the model suggests allocating to industries such as non-ferrous metals, banking, communication, steel, electronics, and power equipment & new energy[22][23][26] - The GRU factor model utilizes minute-level volume and price data processed through GRU deep learning networks. It has shown strong adaptability in short cycles but performs less effectively in long cycles. In 2025, the model's industry rotation includes sectors like agriculture, power & utilities, basic chemicals, transportation, steel, and petrochemicals. Weekly average returns were 2.56%, with excess returns of 1.65% against equal-weighted industry benchmarks. Year-to-date excess returns stand at -4.49%[29][30][32] - Diffusion index weekly tracking shows top-ranked industries as non-ferrous metals (0.991), banking (0.931), power equipment & new energy (0.925), communication (0.92), steel (0.871), and electronics (0.864). Industries with the most significant weekly changes include power equipment & new energy (+0.083), petrochemicals (+0.082), and light manufacturing (+0.078)[23][24][25] - GRU factor weekly tracking ranks industries such as comprehensive (7.22), basic chemicals (3.37), building materials (2.7), transportation (2.36), power & utilities (1.96), and food & beverages (1.94) as top performers. Industries with notable weekly increases include power & utilities, non-bank finance, and basic chemicals[30][33][37]

Quantitative Models and Construction Methods 1. Model Name: Industry Mainline Model (Relative Strength Index, RSI) - **Model Construction Idea**: This model identifies leading industries by calculating their relative strength (RS) based on historical price performance. Industries with RS > 90% are considered potential leaders for the year [10] - **Model Construction Process**: 1. Use 29 first-level industry indices as the investment universe [10] 2. Calculate the price change over the past 20, 40, and 60 trading days for each industry index [10] 3. Rank the price changes for each period and normalize the rankings to obtain RS_20, RS_40, and RS_60 [10] 4. Compute the average of the three rankings to derive the final relative strength index: $ RS = (RS_{20} + RS_{40} + RS_{60}) / 3 $ where RS_20, RS_40, and RS_60 represent the normalized rankings of price changes over 20, 40, and 60 trading days, respectively [10] - **Model Evaluation**: The model successfully identified leading industries in 2024, such as coal, banking, and AI-related sectors, which showed strong performance during the year [10][12] 2. Model Name: Industry Rotation Model (Prosperity-Trend-Crowding Framework) - **Model Construction Idea**: This model combines three dimensions—prosperity, trend, and crowding—to recommend industry allocations. It includes two sub-strategies: "Strong Trend-Low Crowding" and "High Prosperity-Strong Trend" [7][15] - **Model Construction Process**: 1. Define prosperity as the core metric, supplemented by trend and crowding dimensions [15] 2. For the "High Prosperity-Strong Trend" strategy, focus on industries with high prosperity and strong trends while avoiding highly crowded industries [15] 3. For the "Strong Trend-Low Crowding" strategy, prioritize industries with strong trends and low crowding while avoiding low-prosperity industries [15] 4. Allocate weights to industries based on the framework, e.g., November 2025 allocation: Basic Chemicals (18%), Media (16%), Agriculture (12%), Light Manufacturing (12%), Computers (12%), Home Appliances (9%), Real Estate (9%), Retail (6%), New Energy (4%), Coal (3%) [7][15] - **Model Evaluation**: The model demonstrated strong performance, with an annualized excess return of 13.7% and an IR of 1.5. It also showed a high monthly win rate of 67% [15][22] 3. Model Name: Left-Side Inventory Reversal Model - **Model Construction Idea**: This model identifies industries in a recovery phase from distress by analyzing inventory levels and analyst expectations. It aims to capture reversal opportunities in industries with low inventory pressure and potential for restocking [29] - **Model Construction Process**: 1. Focus on industries experiencing current or past distress with signs of recovery [29] 2. Identify industries with low inventory pressure and restocking potential [29] 3. Incorporate analyst long-term positive outlooks for these industries [29] - **Model Evaluation**: The model achieved an absolute return of 27.9% and an excess return of 7.5% relative to equal-weighted industry benchmarks in 2025 (up to October) [29] --- Model Backtesting Results 1. Industry Mainline Model (RSI) - Annualized excess return: Not explicitly stated - IR: Not explicitly stated - Maximum drawdown: Not explicitly stated - Monthly win rate: Not explicitly stated - 2024 performance: Identified leading industries such as coal, banking, and AI, which showed strong performance during the year [10][12] 2. Industry Rotation Model (Prosperity-Trend-Crowding Framework) - Annualized excess return: 13.7% [15] - IR: 1.5 [15] - Maximum drawdown: -8.0% [15] - Monthly win rate: 67% [15] - 2023 excess return: 7.3% [15] - 2024 excess return: 5.7% [15] - 2025 excess return (up to October): 2.0% [15] 3. Left-Side Inventory Reversal Model - Annualized excess return: Not explicitly stated - IR: Not explicitly stated - Maximum drawdown: Not explicitly stated - Monthly win rate: Not explicitly stated - 2023 performance: Absolute return of 13.4%, excess return of 17.0% [29] - 2024 performance: Absolute return of 26.5%, excess return of 15.4% [29] - 2025 performance (up to October): Absolute return of 27.9%, excess return of 7.5% [29]

Group 1 - The report indicates that the stock market is expected to continue fluctuating around the 4000-point mark of the Shanghai Composite Index, with a notable acceleration in style and sector rotation [2][12] - It is suggested to maintain a cautious approach, focusing on opportunities in technology, new energy, and electricity sectors during the fluctuations and rotations [2][12] - The bond market is anticipated to remain in a range-bound oscillation, with insufficient momentum for sustained buying and limited downward space for interest rates [1][12] Group 2 - Recent market events include the suspension of a 24% tariff on U.S. imports, effective from November 10, 2025, which may influence trade dynamics [9] - The report highlights that the A-share market has shown strong sentiment, with various sectors such as banking, coal, electricity, and chemicals performing well [10] - The report notes that the average daily trading volume in the market has decreased to 20,124 billion yuan, reflecting a rise in cautious sentiment among investors [19]

Core Viewpoint - The recent public fund quarterly reports indicate a significant increase in the electronic industry's allocation, reaching over 25%, marking the highest single-industry allocation in the past fifteen years [2][3]. Group 1: Industry Allocation Insights - The electronic industry's allocation surpassing 25% is notable, as it reflects a trend where public funds have historically struggled to maintain allocations above 20% without subsequent market adjustments [2][5]. - Historical data shows that when public fund allocations to a single industry exceed 20%, it often leads to subsequent pressure on absolute returns, with most instances since 2010 resulting in declines in relative performance [2][5]. - The report from Huatai Securities suggests that the average duration of core asset accumulation is around ten quarters, with current electronic sector allocations slightly above this average [3]. Group 2: Market Behavior and Predictions - The analysis indicates that during periods of improved market risk, sectors with increased allocations have an 86% probability of generating excess returns in the following quarter [3]. - Historical patterns reveal that high allocations often coincide with market changes, and the peak in holdings may be driven more by industry price increases rather than active accumulation [5]. - The electronic sector's current allocation has surpassed previous historical limits, yet it is essential to monitor the underlying fundamentals for potential acceleration in growth [5]. Group 3: Contextual Analysis - The report highlights that while the current allocation in the electronic sector is high, it does not necessarily indicate an immediate need for rebalancing, as the sector may continue to perform well if the fundamentals support it [5][6]. - The analysis serves as a window into market sentiment, providing insights into which sectors are currently attracting more attention from investors [6].

- The report constructs a market style rotation solution based on macro data, including value-growth style rotation strategy and large-small cap style rotation strategy. The value-growth style rotation strategy scores higher for growth style with a comprehensive score of 6 as of October 31, 2025[6][8] - The large-small cap style rotation strategy scores higher for small cap style with a comprehensive score of 4 as of October 31, 2025[8][10] - The industry rotation solution is constructed using four dimensions: macro indicators, fundamental indicators, technical indicators, and crowding indicators, forming a comprehensive evaluation system for industry rotation[11][22] - The macro indicators divide the primary industries into five sectors: upstream cycle, midstream manufacturing, downstream consumption, TMT, and big finance, based on the second-order difference of macro growth and liquidity[13] - The fundamental indicators include historical prosperity, prosperity changes, and prosperity expectations. As of October 31, 2025, the top five industries ranked by fundamental indicators are non-bank finance, non-ferrous metals, electronics, communication, and power equipment and new energy[17] - The technical indicators include index momentum, leading stock momentum, and K-line patterns. As of October 31, 2025, the top five industries ranked by technical indicators are communication, media, banking, computer, and machinery[18] - The crowding indicators include financing inflow, turnover rate, and transaction ratio. As of October 31, 2025, the top five industries ranked by crowding indicators are power equipment and new energy, non-ferrous metals, coal, electronics, and communication[21] - The comprehensive industry rotation score, combining the four dimensions, ranks the top seven industries as banking, machinery, communication, non-ferrous metals, media, automotive, and electronics as of October 31, 2025[22][25] Model Backtest Results - Value-Growth Style Rotation Strategy: Comprehensive score of 6, growth style scored higher[6][8] - Large-Small Cap Style Rotation Strategy: Comprehensive score of 4, small cap style scored higher[8][10] Factor Backtest Results - Fundamental Indicators: Top five industries are non-bank finance, non-ferrous metals, electronics, communication, and power equipment and new energy[17] - Technical Indicators: Top five industries are communication, media, banking, computer, and machinery[18] - Crowding Indicators: Top five industries are power equipment and new energy, non-ferrous metals, coal, electronics, and communication[21] - Comprehensive Industry Rotation Score: Top seven industries are banking, machinery, communication, non-ferrous metals, media, automotive, and electronics[22][25]

Core Insights - The report highlights a significant improvement in both revenue and profit growth for the A-share market in Q3 2025, with a notable turnaround in net profit growth for non-financial sectors [3][4] - The overall revenue growth for the A-share market reached 3.7% year-on-year in Q3 2025, compared to -0.2% in Q1 and 0.4% in Q2, while non-financial sectors saw a revenue growth of 2.3% [3][4] - Net profit growth for the entire A-share market was 11.4% year-on-year in Q3 2025, a significant increase from 3.8% in Q1 and 1.4% in Q2, with non-financial sectors showing a profit growth of 3.9% [3][4] Structural Perspective - The report indicates that the performance of major broad-based indices has improved across the board, with the ChiNext and STAR Market showing the highest earnings elasticity [4][10] - In Q3 2025, the ChiNext and STAR Market reported net profit growth rates of 58.3% and 32.8% respectively, with significant quarter-on-quarter improvements [4][10] - The dual drivers of high-tech prosperity and cyclical recovery are emphasized, with sectors like media, electronics, power equipment, and defense showing substantial profit growth exceeding 30% year-on-year [4][10] Stock Price Performance - The report notes that stock prices in the real estate and construction sectors have been more active following the mid-year earnings disclosures, indicating a market expectation for sector rotation [5] - The sectors with the most notable mid-year earnings growth are concentrated in technology manufacturing and certain cyclical industries like steel and non-ferrous metals [5] - The report suggests that the market's expectation for sector rotation is strengthening, particularly in sectors with high policy expectations, such as real estate and cyclical products [5]