Investment Rating - The industry is rated as "stronger than the market," indicating an expected increase of over 10% in the industry index relative to the CSI 300 index over the next six months [18]. Core Viewpoints - The A-share market experienced slight fluctuations with financial, electric power, real estate, and electric grid equipment sectors performing well, while biopharmaceuticals, medical services, precious metals, and gaming sectors lagged [2][3][8]. - The average price-to-earnings ratios for the Shanghai Composite Index and the ChiNext Index are 14.26 times and 38.33 times, respectively, which are at the median levels over the past three years, suggesting a suitable environment for medium to long-term investments [3][17]. - The market is expected to maintain a steady upward trend in the short term, with a focus on sectors that exceed performance expectations in mid-year reports and have reasonable valuations [3][17]. Summary by Sections A-share Market Overview - On July 7, the A-share market faced resistance at 3474 points, with the Shanghai Composite Index closing at 3473.13 points, up 0.02%, while the Shenzhen Component Index fell by 0.70% [8][9]. - The total trading volume for both markets was 12,272 billion, which is above the median of the past three years [3][17]. Future Market Outlook and Investment Recommendations - The report suggests a balanced strategy to optimize portfolio structure amid market fluctuations, with a focus on financial, electric power, electric grid equipment, and household light industry sectors for short-term investment opportunities [3][17]. - The ongoing mild recovery of the Chinese economy, driven by consumption and investment, is expected to support market stability [3][17].

Core Viewpoint - The Central State-Owned Modern Energy ETF (561790) has shown positive performance, with a recent increase of 0.56% and notable gains in constituent stocks, indicating a favorable market environment for energy sector investments [3][4]. Group 1: ETF Performance - As of June 30, 2025, the Central State-Owned Modern Energy ETF has achieved a maximum monthly return of 10.03% since its inception, with a longest consecutive monthly gain of 7 months and a total increase of 23.43% [4]. - The ETF has a year-to-date maximum drawdown of 7.91%, which is relatively low compared to its benchmark [4]. Group 2: Market Activity - The ETF has an active trading environment, with an intraday turnover rate of 13.58% and a transaction volume of 6.2884 million yuan [3]. - Over the past month, the ETF has maintained an average daily transaction volume of 6.6820 million yuan, ranking first among comparable funds [3]. Group 3: Fee Structure and Tracking Accuracy - The management fee for the Central State-Owned Modern Energy ETF is 0.50%, and the custody fee is 0.10%, which are among the lowest in comparable funds [5]. - The ETF has demonstrated high tracking accuracy, with a tracking error of 0.040% over the past two months, the best among its peers [5]. Group 4: Index Composition and Valuation - The underlying index, the Central State-Owned Modern Energy Index, is currently valued at a historical low with a price-to-book ratio (PB) of 1.37, indicating strong valuation attractiveness [5]. - The top ten weighted stocks in the index account for 49.93% of the total, including major players like Changjiang Electric Power and China Nuclear Power [5].

Market Overview - The A-share market experienced a strong rally this week, with the North Securities 50 index leading the major broad-based indices with a weekly increase of 6.84% [3] - Major indices saw comprehensive gains, with the Shanghai Composite Index rising by 1.91%, the CSI 300 by 1.95%, and the ChiNext Index by 5.69% [4] Trading Sentiment - The market's strong rise was accompanied by a steady increase in trading volume, indicating improved liquidity [3] - The volume timing indicator for the North Securities 50 remains cautious, while other major indices have shifted to a bullish signal [3] Fund Flow - ETF funds showed signs of profit-taking, with an overall net outflow from equity ETFs, particularly in the Sci-Tech Innovation Board and small-cap stocks [3] - Southbound capital saw a net inflow of 28.381 billion HKD, with the Shanghai Stock Connect contributing 13.489 billion HKD and the Shenzhen Stock Connect 14.892 billion HKD [10] Valuation Metrics - As of June 27, 2025, broad-based indices such as the Shanghai Composite, CSI 300, CSI 500, and CSI 1000 are at "moderate" valuation percentiles, while the ChiNext Index is at a "safe" valuation percentile [5] - In terms of sector valuation, industries like electricity and public utilities, home appliances, food and beverage, agriculture, non-bank financials, and transportation are classified as "safe" [6] Volatility Analysis - The cross-sectional volatility of the CSI 300 and CSI 500 index constituents increased week-on-week, indicating an improved short-term Alpha environment [7] - Conversely, the cross-sectional volatility of the CSI 1000 index constituents decreased, suggesting a weakening short-term Alpha environment [7] Institutional Focus - The top five stocks attracting the most institutional attention this week were Huichuan Technology (151 institutions), Weigao Medical (144), Jingbeifang (79), AVIC Chengfei (66), and Cangge Mining (64) [9]

Market Performance - On June 27, 2025, the Shanghai Composite Index fell by 0.70%, while the Shenzhen Component Index rose by 0.34% and the ChiNext Index increased by 0.47%[3] - The total market turnover was 15,409.36 billion yuan, a decrease of 420.19 billion yuan from the previous trading day[3] - Out of 5,220 stocks, 3,429 rose and 1,791 fell[3] Sector Performance - The best-performing sectors included non-ferrous metals (up 2.21%), telecommunications (up 1.68%), and textiles and apparel (up 1.14%)[3] - The worst-performing sectors were banks (down 2.85%), electric power and utilities (down 0.99%), and retail (down 0.73%)[3] Fund Flow - On June 27, 2025, the net outflow of main funds was 269.48 billion yuan, with large orders seeing a net outflow of 163.72 billion yuan and small orders experiencing a net inflow of 282.90 billion yuan[4] - Major ETFs like the Huaxia SSE 50 ETF and the Huatai-PB CSI 300 ETF saw changes in turnover of +3.96 billion yuan and +5.13 billion yuan, respectively[4] Global Market Trends - On June 27, 2025, major Asia-Pacific indices showed mixed results, with the Hang Seng Index down 0.17% and the Nikkei 225 up 1.43%[5] - In the U.S., major indices rose, with the Dow Jones Industrial Average increasing by 0.94% and the S&P 500 rising by 0.80%[5] Risk Warning - The analysis is based on objective data and is for reference only, not constituting investment advice[6]

Domestic Market Overview - The domestic market experienced a decline, with the Shanghai Composite Index closing at 3377 points, down 0.75%, and the Shenzhen Component Index at 10122.11 points, down 1.1% [1][4] - The total trading volume of the A-share market reached 15040 billion, showing an increase compared to the previous day [1][4] - Among the 30 sectors, only 4 sectors saw gains, with notable increases in oil and petrochemicals, national defense and military, and electric power and utilities, while comprehensive finance, media, and textile and apparel sectors faced significant declines [1][4] Overseas Market Overview - The three major U.S. stock indices all closed lower, with the Dow Jones down 1.79%, the S&P 500 down 1.13%, and the Nasdaq down 1.3% [2][4] - Major technology stocks also fell, with Nvidia dropping over 2% and Facebook down more than 1% [2][4] Financial Data - The People's Bank of China reported that the social financing scale increased by 18.63 trillion yuan in the first five months, which is 3.83 trillion more than the same period last year [9][16] - As of the end of May, the broad money (M2) balance was 325.78 trillion yuan, reflecting a year-on-year growth of 7.9% [9][16] Key News - The State Council held a meeting to deploy pilot measures for the China (Shanghai) Free Trade Zone, aiming to replicate and promote these measures to enhance high-level opening-up and deep reforms [14] - The fourth China-Africa Economic and Trade Expo concluded with 176 signed projects amounting to 11.39 billion USD, marking a 45.8% increase in project numbers and a 10.6% increase in project value compared to the previous expo [18]

Quantitative Models and Construction Methods - **Model Name**: Broad-based Index Heat Rotation Strategy - **Model Construction Idea**: The model uses the weekly heat change rate (MA2) of broad-based indices to construct a rotation strategy. The idea is to buy the index with the highest heat change rate at the end of each week, or stay in cash if the "Others" group has the highest rate[7][13]. - **Model Construction Process**: 1. Calculate the total heat of constituent stocks for each broad-based index (CSI 300, CSI 500, CSI 1000, CSI 2000, and "Others") by summing up their individual heat indicators[8][11]. 2. Compute the weekly heat change rate for each group and smooth it using a 2-week moving average (MA2)[11][13]. 3. At the end of each week, invest in the index with the highest heat change rate (MA2). If the "Others" group has the highest rate, remain in cash[13]. - **Model Evaluation**: The strategy demonstrates a reasonable annualized return and manageable drawdown, indicating its potential effectiveness in capturing short-term market sentiment[16]. Model Backtesting Results - **Broad-based Index Heat Rotation Strategy**: - Annualized Return: 8.74% (since 2017)[16] - Maximum Drawdown: 23.5%[16] - 2025 YTD Return: 10.1%[16] Quantitative Factors and Construction Methods - **Factor Name**: Total Heat Indicator - **Factor Construction Idea**: The total heat indicator aggregates the attention metrics (e.g., browsing, watchlist additions, and clicks) of individual stocks, normalized as a percentage of the market total, to serve as a proxy for market sentiment[7]. - **Factor Construction Process**: 1. For each stock, calculate the sum of browsing, watchlist additions, and clicks[7]. 2. Normalize the value as a percentage of the total market activity for the same day[7]. 3. Multiply the normalized value by 10,000 to scale the indicator within the range [0, 10,000][7]. - **Factor Evaluation**: The factor effectively captures market sentiment and is used as a proxy for emotional intensity in broader market or sector-level analysis[7]. - **Factor Name**: Weekly Heat Change Rate (MA2) - **Factor Construction Idea**: This factor measures the weekly change in the total heat indicator, smoothed using a 2-week moving average, to identify trends in market sentiment[11][13]. - **Factor Construction Process**: 1. Compute the weekly change rate of the total heat indicator for each stock or group[11]. 2. Apply a 2-week moving average (MA2) to smooth the weekly change rate[11][13]. - **Factor Evaluation**: The smoothed heat change rate provides a stable and actionable signal for rotation strategies and sentiment analysis[13]. Factor Backtesting Results - **Total Heat Indicator**: - Range: [0, 10,000][7] - **Weekly Heat Change Rate (MA2)**: - CSI 300: +7.76% (highest among broad-based indices for the week)[16] - "Others" Group: -3% (lowest among broad-based indices for the week)[16] - **Concept Heat TOP/BOTTOM Portfolios**: - BOTTOM Portfolio Annualized Return: 15.71%[33] - BOTTOM Portfolio Maximum Drawdown: 28.89%[33] - 2025 YTD Return for BOTTOM Portfolio: 21.1%[33]

Quantitative Models and Construction Methods 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 [7]. - **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 process - \( \mu \): Drift rate of the asset price - \( \kappa \): Rate of mean reversion - \( \theta \): Long-term variance - \( \sigma \): Volatility of volatility - \( W_t^1, W_t^2 \): Two Wiener processes with correlation \( \rho \) [7]. --- Quantitative Factors and Construction Methods 1. Factor Name: Multi-Long-Short Ratio Scissor Difference - **Factor Construction Idea**: This factor is based on the number of stocks with bullish and bearish signals within an industry index. The scissor difference ratio is used to construct an industry timing strategy [15]. - **Factor Construction Process**: - Define the number of stocks with bullish signals as \( N_{bull} \) and bearish signals as \( N_{bear} \). - If \( N_{bull} = 0 \), set the bullish count to 0. Similarly, if \( N_{bear} = 0 \), set the bearish count to 0. - The scissor difference is calculated as \( N_{bull} - N_{bear} \), and the ratio is \( \frac{N_{bull} - N_{bear}}{N_{bull} + N_{bear}} \) [15]. - **Factor Evaluation**: The backtesting results show that this factor outperforms the respective industry indices in all cases, indicating excellent historical performance [15]. --- Backtesting Results of Models and Factors 1. Heston Model - **Implied Volatility Results**: - SSE 50: 13.48% (+1.11% WoW) - SSE 500: 16.97% (+0.72% WoW) - CSI 1000: 21.37% (+1.76% WoW) - CSI 300: 13.25% (-0.12% WoW) [9]. 2. Multi-Long-Short Ratio Scissor Difference - **Industry Timing Strategy Results**: - The timing model outperformed the respective industry indices in 100% of cases [15]. - **Specific Industry Examples**: - Retail Trade: Strategy Annualized Return 19.5%, Max Drawdown -43.39%, Index Annualized Return -1.49%, Max Drawdown -77.37% - Home Appliances: Strategy Annualized Return 16.27%, Max Drawdown -38.25%, Index Annualized Return 11.06%, Max Drawdown -48.96% - Comprehensive: Strategy Annualized Return 24.05%, Max Drawdown -40.81%, Index Annualized Return 0.11%, Max Drawdown -81.18% [16][18].

Core Insights - The report highlights the completion of the China-ASEAN Free Trade Area 3.0 negotiations, which aims to create a modern and inclusive trade agreement covering nine new chapters including digital economy and green economy [9][5] - The automotive sector is identified as a leading industry, with A-share markets showing slight upward trends, supported by strong consumer demand and government policies [10][18] - The electric power and public utilities sector demonstrates strong defensive characteristics, with stable revenue and profit growth expected despite a challenging economic environment [14][15] Domestic Market Performance - The Shanghai Composite Index closed at 3,387.57 with a slight increase of 0.21%, while the Shenzhen Component Index rose by 0.44% to 10,294.22 [3] - The A-share market is experiencing a steady upward trend, with average P/E ratios for the Shanghai Composite and ChiNext at 13.84 and 36.88 respectively, indicating a favorable long-term investment environment [10][12] International Market Performance - The Dow Jones Industrial Average closed at 30,772.79, down by 0.67%, while the Nikkei 225 saw a slight increase of 0.62% to 26,643.39 [4] Industry Analysis - The automotive industry continues to show growth, with April production and sales figures indicating a year-on-year increase of 8.86% and 9.78% respectively, despite a month-on-month decline [18][19] - The electric power and public utilities sector is characterized by stable cash flows and a decreasing financial expense ratio, with a net cash flow of 6,243.77 billion yuan in 2024, up by 11.75% [15][16] - The lithium battery sector has shown resilience, with a revenue increase of 18.12% year-on-year in Q1 2025, indicating a recovery trend in the industry [27][28] Investment Recommendations - The report maintains a "stronger than market" rating for the electric power and public utilities sector, suggesting a focus on large hydro and nuclear power companies for long-term investments [17][15] - In the automotive sector, the report recommends monitoring the impact of new vehicle releases and trade-in policies on consumer demand, particularly in the context of smart driving technology advancements [18][19] - The report advises attention to the AI and cloud computing sectors, particularly in light of increased capital expenditures by North American cloud providers [31][34]

Investment Rating - The report maintains a positive outlook on the micro-cap stock index, indicating a favorable investment environment following regulatory changes [3][13]. Core Insights - The recent modification of the "Major Asset Restructuring Management Measures" by the China Securities Regulatory Commission allows for cross-border mergers and acquisitions, which is seen as a significant positive for micro-cap stocks [3][13]. - The micro-cap stock index has shown strong performance, ranking first among 38 broad indices over the past month with a 12.51% increase and a 68.6% increase over the past year [4][14][24]. Summary by Sections 1. Overview of Micro-Cap Stock Index Performance - The micro-cap stock index increased by 1.58% over the past week, ranking 5th among 38 indices [4][14]. - Over the past month, the index rose by 12.51%, ranking 1st [4][19]. - In the last quarter, the index saw a 17.17% increase, also ranking 1st [4][20]. - The annual performance shows a significant increase of 68.6%, ranking 2nd [4][22][24]. 2. Factor Performance of Micro-Cap Stocks - The top-performing factors this week include standardized expected earnings (0.154), leverage (0.127), and quarterly net profit growth (0.102) [5][14][28]. - The bottom-performing factors include momentum (-0.08) and growth factors (-0.032) [5][14][28]. 3. Diffusion Index Observations - The diffusion index remains high but has shown a slight decline, indicating potential sell signals if the trend continues [6][15][33]. - The first threshold method triggered a sell signal on May 8, 2025, while the delayed threshold method provided a buy signal on April 22, 2025 [6][15][36][40]. 4. Calendar Effects - The micro-cap stock index has shown positive average returns on Tuesdays and Thursdays, while Mondays and Wednesdays have negative average returns [7][16]. - The index achieved an 84% win rate in February and a 90% win rate in March and May [7][16]. 5. Micro-Cap Stock Related Fund Performance - The highest-performing micro-cap fund this week yielded 2.79%, while the lowest yielded 0.35% [16][43].

Key Insights - The report highlights the implementation of revised regulations for major asset restructuring by the China Securities Regulatory Commission, aimed at simplifying review processes and enhancing regulatory inclusiveness [4][7] - The National Bureau of Statistics has set a target for the digital economy's core industries to account for over 10% of GDP by the end of 2025 [4][7] - The report notes a significant increase in capital expenditure by North American cloud vendors, with a 64% year-on-year growth in Q1 2025, indicating strong demand for AI and cloud services [15][16] Domestic Market Performance - The Shanghai Composite Index closed at 3,367.46, down 0.40%, while the Shenzhen Component Index closed at 10,179.60, down 0.07% [3] - The report indicates that the average P/E ratios for the Shanghai Composite and ChiNext are at 13.86 and 36.47 respectively, suggesting a suitable environment for medium to long-term investments [8][11] Industry Analysis - The chemical industry saw a decline in prices due to falling oil prices, with a focus on potassium and phosphorus chemical sectors for potential investment opportunities [13][14] - The semiconductor industry reported a robust growth in Q1 2025, with a 12.99% increase in revenue and a 33.22% increase in net profit year-on-year, driven by the growth of AI applications [25][27] - The food and beverage sector showed resilience, with the food and beverage index outperforming the broader market, particularly in snacks and dairy products [22][23] Investment Recommendations - The report suggests focusing on sectors with strong fundamentals such as potassium and phosphorus chemicals, AI-driven semiconductor firms, and the food and beverage industry, particularly in alcoholic beverages and soft drinks [13][22][24] - It emphasizes the importance of monitoring policy changes and market dynamics, particularly in technology and consumer sectors, for potential investment opportunities [8][11][19]