- Model Name: CSI 500 Enhanced Portfolio; Model Construction Idea: The model aims to outperform the CSI 500 index by selecting stocks with higher expected returns based on quantitative strategies[2][58] - Model Construction Process: The model uses a quantitative strategy to select stocks from the CSI 500 index. The portfolio's performance is evaluated based on its excess return over the CSI 500 index. The specific construction process involves selecting stocks with higher expected returns and adjusting the portfolio weights accordingly[58][61] - Model Evaluation: The model has shown a significant excess return over the CSI 500 index, indicating its effectiveness in enhancing returns[58][61] - Model Name: CSI 300 Enhanced Portfolio; Model Construction Idea: The model aims to outperform the CSI 300 index by selecting stocks with higher expected returns based on quantitative strategies[2][65] - Model Construction Process: The model uses a quantitative strategy to select stocks from the CSI 300 index. The portfolio's performance is evaluated based on its excess return over the CSI 300 index. The specific construction process involves selecting stocks with higher expected returns and adjusting the portfolio weights accordingly[65][66] - Model Evaluation: The model has shown a significant excess return over the CSI 300 index, indicating its effectiveness in enhancing returns[65][66] - Factor Name: Value Factor; Factor Construction Idea: The value factor aims to capture the excess returns of stocks that are undervalued relative to their fundamentals[2][70] - Factor Construction Process: The value factor is constructed by ranking stocks based on their valuation ratios, such as price-to-book (P/B) and price-to-earnings (P/E) ratios. Stocks with lower valuation ratios are considered undervalued and are given higher weights in the factor portfolio[70][76] - Factor Evaluation: The value factor has shown high excess returns, indicating its effectiveness in capturing the returns of undervalued stocks[70][76] - Factor Name: Residual Volatility Factor; Factor Construction Idea: The residual volatility factor aims to capture the excess returns of stocks with lower idiosyncratic risk[2][70] - Factor Construction Process: The residual volatility factor is constructed by ranking stocks based on their residual volatility, which is the volatility of the stock's returns unexplained by market movements. Stocks with lower residual volatility are given higher weights in the factor portfolio[70][76] - Factor Evaluation: The residual volatility factor has shown high excess returns, indicating its effectiveness in capturing the returns of low-risk stocks[70][76] - Factor Name: Non-linear Size Factor; Factor Construction Idea: The non-linear size factor aims to capture the excess returns of stocks with specific size characteristics that are not linearly related to market capitalization[2][70] - Factor Construction Process: The non-linear size factor is constructed by ranking stocks based on their non-linear size characteristics, which may include measures such as the square or cube of market capitalization. Stocks with specific size characteristics are given higher weights in the factor portfolio[70][76] - Factor Evaluation: The non-linear size factor has shown significant negative excess returns, indicating its ineffectiveness in capturing the returns of stocks with specific size characteristics[70][76] Model Backtest Results - CSI 500 Enhanced Portfolio, Excess Return: 46.94%, Maximum Drawdown: -4.99%[58][61] - CSI 300 Enhanced Portfolio, Excess Return: 31.61%, Maximum Drawdown: -5.86%[65][66] Factor Backtest Results - Value Factor, Excess Return: High[70][76] - Residual Volatility Factor, Excess Return: High[70][76] - Non-linear Size Factor, Excess Return: Significant Negative[70][76]

Economic News - The Ministry of Commerce aims to fully release the dividends of institutional opening-up by promoting pilot measures that meet the urgent needs of enterprises and the public, with a total of 77 pilot measures to be replicated nationwide [2] - The Ministry of Industry and Information Technology will intensify efforts to rectify disorderly competition in the photovoltaic industry, requiring companies to report cost prices and warning of penalties for selling below cost [2] - The State Taxation Administration reported that tax reductions and refunds for technological innovation and manufacturing reached 636.1 billion yuan in the first five months of the year [2] - The National Development and Reform Commission has completed the annual central investment allocation for the water conservancy sector by the end of June, increasing support for various water projects [2] Company News - Seres Group announced that its AITO Wenjie automobile has achieved cumulative deliveries of 700,000 units [6] - Yanghe Distillery is focusing on low-alcohol products to align with trends towards youthfulness and lower alcohol content [6] - Fuyuan Pharmaceutical received a drug registration certificate for a local anesthetic cream, indicating progress in its product pipeline [6] - Samsung Medical's subsidiary was recommended as a candidate for a major tender project worth approximately 306 million yuan [6] - Whirlpool expects a significant increase in net profit for the first half of 2025, projecting a rise of about 559% year-on-year [6] Industry Research - The solid-state battery industry is accelerating, with major lithium battery companies announcing advancements in solid-state battery technology, aiming for higher energy densities and improved safety [18][19] - Solid-state batteries are expected to benefit from new application fields, particularly in eVTOL and humanoid robots, due to their superior performance compared to traditional lithium batteries [19] - The solid-state battery supply chain is gaining attention, with government support and industry advancements pushing the technology towards commercialization [19][21] - The mainstream development direction for solid-state batteries is the sulfide solid electrolyte system, which is favored for its high ionic conductivity and stability [20] - Investment opportunities are emerging in companies with leading solid-state battery technology and those involved in the supply chain, such as Guoxuan High-Tech and relevant material manufacturers [21][22]

Investment Rating - The industry investment rating is "Positive" (维持) [6] Core Viewpoints - The report is optimistic about the development of the electricity market, which brings new opportunities for the electricity system [3] - The transition from passive reliance on natural conditions to active participation in market operations is a core variable for optimizing economic efficiency in the industry [8] - The report highlights the importance of electricity market trading capabilities, especially in regions like Xinjiang and Inner Mongolia, where new projects will rely heavily on market transactions [8] Summary by Relevant Sections - **Electricity Market Development**: The report emphasizes the positive outlook for the electricity market, driven by reforms that enhance market participation and efficiency [3][8] - **New Energy Projects**: New energy projects in regions like Xinjiang and Inner Mongolia are expected to shift from subsidy-dependent models to market-driven mechanisms, with specific pricing structures outlined for different project types [8] - **Software and Hardware Opportunities**: The report suggests focusing on companies involved in software applications for electricity trading and hardware that supports market transactions, recommending specific companies for investment [8] - **Active Value Creation**: The shift from passive to active value creation in the new energy sector is expected to unlock significant investment opportunities, with several companies identified as potential beneficiaries [8]

Quantitative Models and Construction 1. Model Name: Heston Model - **Model Construction Idea**: The Heston model is used to calculate the implied volatility of near-month at-the-money options, serving as a market fear index. Implied volatility reflects market participants' expectations of future volatility [8]. - **Model Construction Process**: The Heston model is a stochastic volatility model where the variance of the asset price follows a mean-reverting square-root process. The model is defined by the following equations: $ dS_t = \mu S_t dt + \sqrt{v_t} S_t dW_t^1 $ $ dv_t = \kappa (\theta - v_t) dt + \sigma \sqrt{v_t} dW_t^2 $ Here: - \( S_t \): Asset price - \( v_t \): Variance - \( \mu \): Drift rate - \( \kappa \): Mean reversion speed - \( \theta \): Long-term variance - \( \sigma \): Volatility of variance - \( W_t^1, W_t^2 \): Correlated Wiener processes [8] 2. Model Name: Multi-Sector Timing Model (Scissor Difference Strategy) - **Model Construction Idea**: This model uses the difference in the number of bullish and bearish signals among sector constituents to construct a timing strategy. If no bullish or bearish signals are present, the scissor difference is set to zero. The model aims to outperform sector indices [16]. - **Model Construction Process**: - Count the number of bullish and bearish signals for each sector's constituent stocks daily. - Compute the scissor difference as the difference between bullish and bearish signals. - If both counts are zero, the scissor difference is set to zero. - Construct a timing strategy based on the scissor difference ratio [16]. - **Model Evaluation**: The model historically outperformed all sector indices, demonstrating excellent backtesting performance [16]. --- Model Backtesting Results 1. Heston Model - **Implied Volatility Results**: - SSE 50: 11.85% (down 0.88% WoW) - SSE 500: 14.35% (down 1.59% WoW) - CSI 1000: 18.06% (down 0.42% WoW) - CSI 300: 12.64% (down 0.73% WoW) [10] 2. Multi-Sector Timing Model - **Sector Outperformance**: The model outperformed all sector indices, achieving a 100% success rate in backtesting [16]. --- Quantitative Factors and Construction 1. Factor Name: Shape-Based Timing Signals - **Factor Construction Idea**: Shape-based signals are derived from historical K-line patterns, including bullish patterns (e.g., "Golden Needle Bottom," "Rocket Launch," "Manjianghong") and bearish patterns (e.g., "Hanging Line," "Paradise Line," "Dark Cloud Cover"). These patterns indicate potential price reversals [24]. - **Factor Construction Process**: - Identify specific K-line patterns based on predefined criteria. - Evaluate the historical performance of these patterns in predicting price movements. - Use the patterns to generate timing signals for individual stocks [24]. - **Factor Evaluation**: Bullish patterns like "Golden Needle Bottom" and "Rocket Launch" demonstrated strong positive predictive power [24]. --- Factor Backtesting Results 1. Shape-Based Timing Signals - **Signal Statistics**: - Positive signals: 2,699 occurrences, with an average future high-point success rate of 28.25% - Negative signals: 3,525 occurrences, with an average future low-point success rate of 71.88% [13] 2. Sector Timing Signals - **Bullish Sectors**: Home Appliances, Comprehensive, Communication, Textile & Apparel, Consumer Services, Transportation, Petrochemicals [19] 3. Stock-Specific Signals - **Consecutive Bullish Signals**: - 5-day signals: Stocks like Kailong Co. and Shipu Testing [21] - 4-day signals: Stocks like Jiangnan Chemical, Beijing-Shanghai High-Speed Railway, and Nandu Property [22][23] - **Special Bullish Patterns**: - Stocks like Retired Longyu ("Arrow on the String") and Suotong Development ("Manjianghong") [25][26] 4. Broker Gold Stock Signals - **Highlighted Stocks**: BYD, Feilihua, Wancheng Group, Sichuan Road & Bridge, Wolong Electric Drive, Lansheng Co., PetroChina, Dongpeng Beverage [29][33]

- The report primarily focuses on the weekly performance of the equity market, highlighting the resilience of the A-share market amidst global trade policy fluctuations and the rising prominence of technology and new consumption sectors [13][14][18] - It mentions the issuance of multiple quantitative products, including A500 Index Enhanced and Sci-Tech Composite Index Enhanced funds, which aim to enrich the market's product offerings [13][72][73] - The report tracks the weekly net inflow and outflow of funds across various ETF categories, showing significant movements in wide-base indices, industry-specific ETFs, and thematic ETFs [42][43][46] - Quantitative models such as the "Cinda Financial Engineering Industry Rotation Strategy" are referenced, which monitor marginal changes in holdings by high-performing funds to identify over-allocated and under-allocated sectors [37][38][41] - The report provides detailed fund flow data, including top-performing sectors like electronics, communication, and non-bank finance, as well as sectors with significant outflows such as automobiles, machinery, and pharmaceuticals [60][65][67]

Investment Rating - The industry investment rating is "Positive (Maintain)" [6] Core Viewpoints - The report highlights the steady advancement of the "Electricity AI Agent" and the activation of new pilot projects for the new power system, focusing on innovative technologies and models to drive breakthroughs in construction [9] - The dual deep coupling of AI and electricity is expected to enhance resource allocation efficiency and foster a collaborative development environment for the "energy-computing" ecosystem [9] Summary by Sections Industry Overview - The report discusses the establishment of pilot projects for the new power system, emphasizing the exploration of new technologies and models in typical cities [9] - Key focus areas include grid-type technology, system-friendly renewable energy stations, intelligent microgrids, and virtual power plants [9] Investment Recommendations and Targets - Suggested companies to focus on include: - "Electricity AI Agent" application segment: Dongfang Electronics (000682, Not Rated), Guoneng Rixin (301162, Accumulate), Zhiyang Innovation (688191, Not Rated), State Grid Xintong (600131, Not Rated), Teradyne (300001, Buy), and Anke Rui (300286, Buy) [9] - AI server power supply segment: Magmi (002851, Not Rated), Zhongheng Electric (002364, Not Rated), Hewei Electric (603063, Not Rated), Oulu Tong (300870, Not Rated), Kehua Data (002335, Not Rated), and Keda (002518, Not Rated) [9] - AIDC power supply segment: Jinpan Technology (688676, Buy), Mingyang Electric (301291, Not Rated), Weiteng Electric (688226, Not Rated), Liangxin Co. (002706, Not Rated), Chint Electric (601877, Not Rated), and Samsung Medical (601567, Not Rated) [9]

1. Report Industry Investment Rating No relevant content provided. 2. Core Viewpoints of the Report - This week, the equity market showed differentiation, with the BeiZheng 50 leading the gains and the small - cap value style outperforming. In terms of industries, comprehensive finance led, and national defense and military industry, medicine, agriculture, forestry, animal husbandry and fishery also performed well. The bond market declined overall, while the convertible bond market rose. The average return of active equity funds in the whole market was - 0.41%; the average return of short - term bond funds was - 0.01%, and that of medium - and long - term bond funds was - 0.03%; the average return of bond funds with equity exposure was negative, and the average return of convertible bond funds was positive [1][2]. 3. Summary According to the Directory 3.1 Market Review - The equity market was differentiated, with the BeiZheng 50 leading and the small - cap value style dominant. Comprehensive finance led the industry performance, and national defense and military industry, medicine, agriculture, forestry, animal husbandry and fishery also performed well. As of the close this week, the CSI 300 Index closed at 3840 points, down 1.08%; the Shanghai Composite Index closed at 3347 points, down 0.03%; the Shenzhen Component Index closed at 10041 points, down 0.91%; the ChiNext Index closed at 1993 points, down 1.4%. In the Hong Kong stock market, the Hang Seng Index fell 1.32%, and the Hang Seng Tech Index fell 1.46% [6]. - In terms of industry performance, comprehensive finance led with a gain of over 10%. National defense and military industry, medicine, agriculture, forestry, animal husbandry and fishery performed well, while the automobile, non - ferrous metals, power equipment and new energy sectors declined by over 2% [8]. - As of May 30, 2025, there were 5413 stocks in the A - share market, of which 3228 stocks rose this week. The number of rising stocks on the BeiZheng, ChiNext, Science and Technology Innovation Board, and Main Board was 194, 816, 343, and 1875 respectively [11]. 3.2 Key Fund Tracking 3.2.1 Active Equity - **Fund Performance**: The average return of the whole - market funds in the sample was - 0.41%. Funds with better performance were heavily invested in industries such as medicine, non - ferrous metals, and food and beverages. Among industry - themed funds, medical sector funds had the highest average return, while mid - stream manufacturing and cyclical sector funds lagged [17][20]. - **Position Estimation**: This week, the positions of ordinary stock - type funds increased slightly, while those of partial - stock hybrid funds decreased slightly. Compared with the previous week, the positions of ordinary stock - type funds increased by 0.22 percentage points, and those of partial - stock hybrid funds decreased by 0.60 percentage points. Actively managed partial - stock funds increased their allocation to cyclical and stable sectors and reduced their allocation to financial, consumer, and growth sectors [23]. 3.2.2 Bond - type Funds - **Bond Market Performance**: The bond market declined overall this week. The ChinaBond Total Wealth Index closed at 245.89, down 0.07% from last week; the ChinaBond Treasury Bond Index closed at 246.62, down 0.07% from last week; the ChinaBond Credit Bond Index closed at 223, down 0.01% from last week. The CSI Non - Pure Bond Fund Index closed at 2184.93 on Thursday, down 0.02% from last Thursday. The CSI Convertible Bond Index closed at 429.31, with a weekly increase of 0.46% and a trading volume of 277.1 billion yuan, an increase of 2.093 billion yuan from last week [29][31]. - **Fund Performance Overview**: The average return of short - term bond funds was - 0.01%, and the median was - 0.01%. The average return of medium - and long - term bond funds was - 0.03%, and the median was - 0.04%. The average return of first - tier bond funds was 0%, and the median was - 0.01%. The average return of second - tier bond funds was - 0.02%, and the median was - 0.01%. The average return of partial - bond hybrid funds was - 0.03%, and the median was - 0.02%. The average return of low - position flexible allocation funds was - 0.07%, and the median was - 0.05%. The average return of convertible bond funds was 0.28%, and the median was 0.22% [34][37][40]. 3.2.3 New - share Subscription Funds - **New - share Overview**: One new stock was listed this week, with a total raised capital of 604 million yuan. There was no break - even on the first day of listing, and the expected total入围 income was 35,400 yuan [41]. - **New - share Subscription Income Calculation**: Assuming weekly participation in offline new - share subscriptions and successful入围, the weekly new - share subscription return sequence of an 800 - million - yuan account was calculated [42]. - **Fund Company New - share Subscription Overview**: Eight fund companies with more than two new - share subscription funds were selected. This week, the new - share subscription return rate of an 800 - million - yuan account was 0.004%. The optimal scale for weekly and annual new - share subscriptions was 400 million yuan [44]. - **New - share Subscription Fund Performance**: The average return of new - share subscription funds in the sample this week was - 0.18% [46]. 3.2.4 FOF Fund Performance - The average returns of low - risk, medium - risk, and high - risk FOF funds in the sample this week were - 0.28%, - 0.88%, and - 1.45% respectively [48]. 3.2.5 QDII Funds - During the statistical period, partial - stock and index QDII funds declined by 0.71% and 0.83% on average respectively, while alternative and bond QDII funds rose by 0.02% and 0.37% on average respectively [2][49]. 3.2.6 REITs Funds - This week, REITs declined by 0.02% on average. The Huaxia TBEA New Energy REIT led the gains, rising 4.26% this week. The Huatai Suzhou Hengtai Rental Housing REIT had the highest liquidity, with a trading volume of 130.2489 million yuan this week [51].

Investment Rating - The report indicates a cautious investment rating for major broad-based indices as of May 23, 2025, with the ChiNext Index classified as "safe" and other indices categorized as "moderate" [19][22]. Core Insights - The market experienced a contraction with major indices declining during the week of May 19-23, 2025. The report highlights a rapid rotation in themes, with precious metals and automotive sectors performing well. However, the "dividend + micro-cap" strategy showed signs of short-term adjustment after reaching a yearly high, suggesting a potential decline in trading preferences [12][13]. - The report emphasizes that liquidity easing and rising risk appetite are expected to drive a rebound in A-shares in the medium to long term, with "dividend + small-cap" combinations being the preferred allocation strategy post-adjustment [12]. Summary by Sections Market Review - Major indices saw declines: Shanghai Composite Index down 0.57%, SSE 50 down 0.18%, CSI 300 down 0.18%, CSI 500 down 1.10%, CSI 1000 down 1.29%, ChiNext Index down 0.88%, and North Star 50 down 3.68% [13][14]. Valuation Analysis - As of May 23, 2025, the ChiNext Index is in the "safe" valuation percentile, while other major indices are in the "moderate" range. In terms of sector valuation, industries such as construction materials, light industry manufacturing, power equipment and new energy, defense and military, computer, and comprehensive finance are classified as "dangerous," while non-ferrous metals, utilities, home appliances, food and beverage, agriculture, non-bank financials, and transportation are deemed "safe" [19][20]. Fund Flow Tracking - The report notes that institutional interest was highest for stocks like Huichuan Technology (352 institutions), Fuchuang Precision (109), Bozhong Precision (106), Boshi Software (102), and Shengmei Shanghai (101) during the week [51]. - Southbound capital saw a net inflow of 18.96 billion HKD, with the Shanghai-Hong Kong Stock Connect contributing 19.05 billion HKD and the Shenzhen-Hong Kong Stock Connect experiencing a net outflow of 0.97 billion HKD [3]. Sector Performance - The top five performing sectors this week were comprehensive, pharmaceuticals, automotive, non-ferrous metals, and home appliances, while the worst performers included comprehensive finance, computers, electronics, machinery, and communications [15]. Institutional Research - A total of 379 institutional research activities were recorded, with the majority focused on companies listed in Shenzhen and Shanghai. The report highlights that specific object research and other types accounted for 78.36% and 8.71% of the total, respectively [42][46].

- Model Name: Volume Timing Model; Model Construction Idea: The model uses volume indicators to maintain a cautious view under the background of shrinking volume; Model Construction Process: The volume timing signal for major broad-based indices is calculated and maintained a cautious view as of May 23, 2025[1][2][22]; Model Evaluation: The model is effective in maintaining a cautious stance during periods of shrinking volume[22] - Factor Name: Upward Number Ratio of CSI 300; Factor Construction Idea: The factor calculates the proportion of stocks with positive returns in the CSI 300 index to judge market sentiment; Factor Construction Process: - CSI 300 Index N-day Upward Number Ratio = Number of CSI 300 Index constituent stocks with positive returns in the past N days / Total number of CSI 300 Index constituent stocks - The factor captures upward opportunities quickly and exits early during overheated market phases, but has limitations in avoiding downward risks[23][24][25]; Factor Evaluation: The factor is effective in capturing upward opportunities but has limitations in avoiding downward risks[24] - Factor Name: Moving Average Sentiment Indicator; Factor Construction Idea: The factor uses the eight moving average system to judge the trend state of the target index; Factor Construction Process: - Calculate the eight moving average values of the CSI 300 closing price with parameters 8, 13, 21, 34, 55, 89, 144, 233 - Assign values to the eight moving average indicator based on the interval value: -1 for intervals 1/2/3, 0 for intervals 4/5/6, and 1 for intervals 7/8/9 - When the current price exceeds the eight moving average indicator value in more than 5 cases, it indicates a bullish view on the CSI 300 index[27][31][32]; Factor Evaluation: The factor is effective in indicating the trend state of the CSI 300 index[34] - Factor Name: Cross-sectional Volatility; Factor Construction Idea: The factor measures the cross-sectional volatility of index constituent stocks to evaluate the Alpha environment; Factor Construction Process: - Calculate the cross-sectional volatility of CSI 300, CSI 500, and CSI 1000 index constituent stocks - Recent cross-sectional volatility of CSI 300 and CSI 500 index constituent stocks has decreased, indicating a worse short-term Alpha environment; CSI 1000 index constituent stocks' cross-sectional volatility has increased, indicating a better short-term Alpha environment[35][36][38]; Factor Evaluation: The factor is effective in evaluating the Alpha environment based on cross-sectional volatility[38] - Factor Name: Time Series Volatility; Factor Construction Idea: The factor measures the time series volatility of index constituent stocks to evaluate the Alpha environment; Factor Construction Process: - Calculate the time series volatility of CSI 300, CSI 500, and CSI 1000 index constituent stocks - Recent time series volatility of CSI 300, CSI 500, and CSI 1000 index constituent stocks has decreased, indicating a worse short-term Alpha environment[39][41]; Factor Evaluation: The factor is effective in evaluating the Alpha environment based on time series volatility[41] Model Backtest Results - Volume Timing Model, cautious view for all major broad-based indices as of May 23, 2025[23] Factor Backtest Results - Upward Number Ratio of CSI 300, recent ratio around 56%[24] - Moving Average Sentiment Indicator, short-term bullish view on CSI 300 index[34] - Cross-sectional Volatility, recent values for CSI 300: 1.75%, CSI 500: 2.04%, CSI 1000: 2.41%[38] - Time Series Volatility, recent values for CSI 300: 0.56%, CSI 500: 0.44%, CSI 1000: 0.27%[41]

Domestic Market Overview - The domestic market showed a strong upward trend, with the Shanghai Composite Index closing at 3387.57 points, up 0.21%, and the Shenzhen Component Index closing at 10294.22 points, up 0.44% [1][5][10] - Among the 30 first-level industries, 13 sectors saw gains, with coal, non-ferrous metals, and electric equipment & new energy leading the increases, while comprehensive finance, electronics, and media experienced significant declines [1][5][10] - The total trading volume of the A-share market reached 12144 billion, slightly up from the previous day [1][5][10] Overseas Market Overview - The three major U.S. stock indices all closed lower, with the Dow Jones down 1.91%, the S&P 500 down 1.61%, and the Nasdaq down 1.41% [2][5] - Major technology stocks, including Tesla and Apple, fell over 2%, and most Chinese concept stocks also declined, with iQIYI down over 8% and Baidu down over 4% [2][5] News Highlights - The Financial Regulatory Bureau and eight other departments jointly issued measures to support financing for small and micro enterprises, focusing on increasing financing supply and reducing costs [3][12] - Chengdu is promoting the development of a duty-free economy, aiming to establish duty-free shops within the year [3][15] - China and ASEAN countries have completed negotiations for the upgraded version of the China-ASEAN Free Trade Area 3.0, which includes nine new chapters [3][18][19] - The U.S. is attempting to globally ban advanced computing chips from China, which has drawn criticism from Chinese officials [3][16][17]