Core Viewpoint - The high-end equipment sector is experiencing mixed performance, with significant movements in specific stocks and a positive long-term outlook for the military industry driven by technological advancements and increased defense spending [1][3][4]. Group 1: Market Performance - As of August 7, 2025, the CSI High-End Equipment Sub-Index decreased by 0.80%, with stocks showing varied performance; 712 led with an increase of 8.65%, while Guorui Technology saw the largest decline [1]. - The high-end equipment ETF (159638) had a turnover rate of 4.57% and a transaction volume of 54.32 million yuan, with an average daily transaction volume of 63.18 million yuan over the past week [3]. Group 2: ETF Performance - The latest scale of the high-end equipment ETF reached 1.198 billion yuan, with a net value increase of 33.28% over the past year [3]. - Since its inception, the ETF has recorded a highest single-month return of 19.30%, with the longest consecutive monthly gains being three months and a maximum increase of 21.15% [3]. Group 3: Industry Outlook - Recent reports indicate that the domestic military construction is transitioning towards "intelligent and unmanned" systems, with global military trade demand expanding, suggesting a long-term growth cycle for the military industry [3]. - The recent successful launch of the Pakistan Remote Sensing Satellite 01 demonstrates the maturity and stability of China's aerospace technology, while the successful flight of the Kuaizhou-1A rocket reinforces the high prosperity of the aerospace equipment sector [3]. Group 4: Key Stocks - As of July 31, 2025, the top ten weighted stocks in the CSI High-End Equipment Sub-Index accounted for 46.03% of the index, with notable companies including AVIC Shenyang Aircraft Company and Aero Engine Corporation of China [4]. - The performance of key stocks varied, with AVIC Shenyang Aircraft Company down by 2.36% and Aerospace Electronic Technology up by 2.08% [6]. Group 5: Investment Opportunities - Investors can consider the CSI High-End Equipment Sub-Index ETF linked fund (018028) for potential industry rotation opportunities [6].

Quantitative Models and Construction Methods 1. Model Name: Diffusion Index Model - **Model Construction Idea**: The model is based on the principle of price momentum, aiming to capture upward trends in industry performance[26][39] - **Model Construction Process**: The diffusion index is calculated for each industry, reflecting the proportion of stocks within the industry that exhibit positive momentum. The index ranges from 0 to 1, where higher values indicate stronger momentum. The model selects industries with the highest diffusion indices for allocation. For example, as of August 1, 2025, the top-ranked industries included Steel (1.0), Comprehensive Finance (1.0), and Non-Banking Finance (0.999)[27][28] - **Model Evaluation**: The model has shown mixed performance over the years. While it achieved significant excess returns in 2021 (up to 25% before September), it experienced notable drawdowns in 2023 (-4.58%) and 2024 (-5.82%) due to its inability to adjust to market reversals[26] 2. Model Name: GRU Factor Model - **Model Construction Idea**: This model leverages GRU (Gated Recurrent Unit) deep learning networks to process high-frequency volume and price data, aiming to identify industry rotation opportunities[40] - **Model Construction Process**: The GRU network is trained on historical minute-level data to predict industry factor rankings. The model then allocates to industries with the highest predicted rankings. As of August 1, 2025, the top-ranked industries included Non-Banking Finance (-1.15), Steel (0.7), and Base Metals (0.5)[34][38] - **Model Evaluation**: The model has demonstrated strong adaptability in short-term scenarios but struggles in long-term or extreme market conditions. Its performance in 2025 has been hindered by concentrated market themes, resulting in difficulty capturing inter-industry excess returns[33][40] --- Backtesting Results of Models 1. Diffusion Index Model - **Weekly Average Return**: -1.67%[30] - **Excess Return (August)**: -0.44%[30] - **Excess Return (2025 YTD)**: -0.40%[25][30] 2. GRU Factor Model - **Weekly Average Return**: 0.00%[38] - **Excess Return (August)**: 0.16%[38] - **Excess Return (2025 YTD)**: -2.35%[33][38] --- Quantitative Factors and Construction Methods 1. Factor Name: Diffusion Index - **Factor Construction Idea**: Measures the breadth of positive momentum within an industry[27] - **Factor Construction Process**: The diffusion index is calculated as the proportion of stocks in an industry with positive momentum. For example, as of August 1, 2025, the diffusion index for Steel was 1.0, while for Coal it was 0.23[27][28] - **Factor Evaluation**: The factor effectively identifies industries with strong upward trends but may underperform during market reversals[26] 2. Factor Name: GRU Industry Factor - **Factor Construction Idea**: Utilizes GRU deep learning to rank industries based on high-frequency trading data[40] - **Factor Construction Process**: The GRU network processes minute-level volume and price data to generate factor rankings. For instance, as of August 1, 2025, the GRU factor for Non-Banking Finance was -1.15, while for Steel it was 0.7[34][38] - **Factor Evaluation**: The factor is effective in capturing short-term trends but struggles in long-term or highly volatile markets[33][40] --- Backtesting Results of Factors 1. Diffusion Index Factor - **Top Industries (August 1, 2025)**: Steel (1.0), Comprehensive Finance (1.0), Non-Banking Finance (0.999)[27][28] - **Weekly Average Return**: -1.67%[30] - **Excess Return (August)**: -0.44%[30] - **Excess Return (2025 YTD)**: -0.40%[25][30] 2. GRU Industry Factor - **Top Industries (August 1, 2025)**: Non-Banking Finance (-1.15), Steel (0.7), Base Metals (0.5)[34][38] - **Weekly Average Return**: 0.00%[38] - **Excess Return (August)**: 0.16%[38] - **Excess Return (2025 YTD)**: -2.35%[33][38]

Core Viewpoint - Public fund institutions are optimistic about the market outlook and advocate for balanced allocation to respond to industry rotation [1] Group 1 - Public fund institutions believe that the market will continue to show positive trends in the near future [1] - The strategy of balanced allocation is recommended to mitigate risks associated with industry rotation [1] - There is an emphasis on the importance of adapting investment strategies in response to changing market conditions [1]

Quantitative Models and Construction Methods Model: Duration Timing Model - **Construction Idea**: Predict the yield curve and map the expected returns of bonds with different durations[20] - **Construction Process**: - Use the improved Diebold2006 model to predict the instantaneous yield curve - Predict level, slope, and curvature factors - Level factor prediction based on macro variables and policy rate following - Slope and curvature factors prediction based on AR(1) model[20] - **Evaluation**: The model effectively predicts the yield curve and provides actionable insights for bond duration management[20] - **Test Results**: - July return: 6.6bp - Benchmark return: -25.8bp - Strategy excess return: 32.4bp[21] Model: Gold Timing Model - **Construction Idea**: Relate the forward real returns of gold and US TIPS to construct the expected return model for gold[32] - **Construction Process**: - Use the formula: $E[Real\_Return^{gold}]=k\times E[Real\_Return^{Tips}]$ - Estimate parameter k using OLS with an extended window - Use the Fed's long-term inflation target of 2% as a proxy[32] - **Evaluation**: The model provides a robust framework for predicting gold returns based on TIPS yields[32] - **Test Results**: - Expected return for the next year: 22.4% - Past year absolute return: 39.77%[33][35] Model: Active Risk Budget Model - **Construction Idea**: Combine the risk parity model with active signals to construct an active risk budget model for optimal stock and bond allocation[37] - **Construction Process**: - Use the Fed model to define equity risk premium (ERP): $ERP={\frac{1}{PE_{ttm}}}-YTM_{TB}^{10Y}$ - Adjust asset weights dynamically based on ERP, stock valuation percentiles, and market liquidity (M2-M1 spread) - Convert equity asset signal scores into risk budget weights using the softmax function: $softmax(x)={\frac{\exp(\lambda x)}{\exp(\lambda x)+\exp(-\lambda x)}}$[39][47] - **Evaluation**: The model dynamically adjusts asset weights based on multiple dimensions, providing a balanced risk-return profile[37] - **Test Results**: - July stock position: 18.72% - Bond position: 81.28% - July portfolio return: 0.84% - August stock position: 7.44% - Bond position: 92.56%[51] Model Backtest Results 1. **Duration Timing Model** - July return: 6.6bp - Benchmark return: -25.8bp - Strategy excess return: 32.4bp[21] 2. **Gold Timing Model** - Expected return for the next year: 22.4% - Past year absolute return: 39.77%[33][35] 3. **Active Risk Budget Model** - July stock position: 18.72% - Bond position: 81.28% - July portfolio return: 0.84% - August stock position: 7.44% - Bond position: 92.56%[51] Quantitative Factors and Construction Methods Factor: High-Frequency Macroeconomic Factors - **Construction Idea**: Use asset portfolio simulation to construct a high-frequency macro factor system to observe market macro expectations[12] - **Construction Process**: - Combine real macro indicators to form low-frequency macro factors - Select assets leading low-frequency macro factors - Use rolling multiple leading regression to determine asset weights and simulate macro factor trends[12] - **Evaluation**: High-frequency macro factors provide leading indicators for market expectations, offering valuable insights for asset allocation[12] Factor: Convertible Bond Valuation Factors - **Construction Idea**: Compare the relative valuation of convertible bonds and stocks, and between convertible bonds and credit bonds[25] - **Construction Process**: - Construct the "100-yuan conversion premium rate" to compare the valuation of convertible bonds and stocks - Use the "modified YTM - credit bond YTM" median to compare the valuation of debt-biased convertible bonds and credit bonds - Construct style rotation portfolios based on market sentiment indicators like 20-day momentum and volatility deviation[25][27] - **Evaluation**: The factors effectively capture the relative valuation and style characteristics of convertible bonds, aiding in portfolio construction[25][27] - **Test Results**: - "100-yuan conversion premium rate": 33.71% - "Modified YTM - credit bond YTM" median: -2.06% - Style rotation annualized return: 24.54% - Maximum drawdown: 15.89% - IR: 1.47 - Monthly win rate: 65.17% - 2025 return: 35.17%[26][29] Factor Backtest Results 1. **High-Frequency Macroeconomic Factors** - High-frequency economic growth: Upward trend - High-frequency consumer inflation: Downward trend - High-frequency producer inflation: Upward trend[17] 2. **Convertible Bond Valuation Factors** - "100-yuan conversion premium rate": 33.71% - "Modified YTM - credit bond YTM" median: -2.06% - Style rotation annualized return: 24.54% - Maximum drawdown: 15.89% - IR: 1.47 - Monthly win rate: 65.17% - 2025 return: 35.17%[26][29]

1. Report Industry Investment Rating No relevant content provided. 2. Core Viewpoints of the Report - Today, the convertible bond market declined with reduced trading volume, and the valuation increased compared to the previous day [1]. - The CSI Convertible Bond Index decreased by 0.08% compared to the previous day, while the Shanghai Composite Index rose by 0.17%, the Shenzhen Component Index decreased by 0.77%, the ChiNext Index decreased by 1.62%, the SSE 50 Index rose by 0.38%, and the CSI 1000 Index decreased by 0.82% [1]. - The large - cap value style was relatively dominant in the market. The large - cap growth index decreased by 0.48%, the large - cap value index rose by 0.84%, the mid - cap growth index decreased by 0.17%, the mid - cap value index rose by 0.51%, the small - cap growth index decreased by 0.76%, and the small - cap value index decreased by 0.27% [1]. - The trading sentiment in the convertible bond market weakened. The trading volume of the convertible bond market was 76.134 billion yuan, a 2.88% decrease compared to the previous day; the total trading volume of the Wind All - A Index was 1.870976 trillion yuan, a 2.28% increase compared to the previous day; the net out - flow of main funds in the Shanghai and Shenzhen stock markets was 52.9 billion yuan, and the yield of the 10 - year treasury bond decreased by 2.86bp to 1.72% [1]. 3. Summary by Related Catalogs Market Overview - Index performance: The CSI Convertible Bond Index decreased by 0.08% compared to the previous day, while the Shanghai Composite Index rose by 0.17%, the Shenzhen Component Index decreased by 0.77%, the ChiNext Index decreased by 1.62%, the SSE 50 Index rose by 0.38%, and the CSI 1000 Index decreased by 0.82% [1]. - Market style: The large - cap value style was relatively dominant. The large - cap growth index decreased by 0.48%, the large - cap value index rose by 0.84%, the mid - cap growth index decreased by 0.17%, the mid - cap value index rose by 0.51%, the small - cap growth index decreased by 0.76%, and the small - cap value index decreased by 0.27% [1]. - Capital performance: The trading volume of the convertible bond market was 76.134 billion yuan, a 2.88% decrease compared to the previous day; the total trading volume of the Wind All - A Index was 1.870976 trillion yuan, a 2.28% increase compared to the previous day; the net out - flow of main funds in the Shanghai and Shenzhen stock markets was 52.9 billion yuan, and the yield of the 10 - year treasury bond decreased by 2.86bp to 1.72% [1]. Convertible Bond Price - The central price of convertible bonds decreased, and the proportion of high - price bonds remained the same. The weighted average closing price of convertible bonds was 126.79 yuan, a 0.05% decrease compared to the previous day. Among them, the closing price of equity - biased convertible bonds was 167.54 yuan, a 0.24% decrease; the closing price of debt - biased convertible bonds was 117.04 yuan, a 0.22% increase; the closing price of balanced convertible bonds was 124.96 yuan, a 0.08% increase [2]. - The proportion of high - price bonds above 130 yuan was 43.84%, remaining the same as the previous day; the range with the largest change in proportion was 110 - 120 (including 120), with a proportion of 20.95%, a 0.65pct decrease compared to the previous day; there were 2 bonds with a closing price below 100 yuan. The median price was 128.43 yuan, a 0.19% increase compared to the previous day [2]. Convertible Bond Valuation - Valuation increased. The fitted conversion premium rate of 100 - yuan par value was 27.74%, a 0.18pct increase compared to the previous day; the overall weighted par value was 96.98 yuan, a 0.30% decrease compared to the previous day. The premium rate of equity - biased convertible bonds was 6.82%, a 0.29pct increase; the premium rate of debt - biased convertible bonds was 85.62%, a 0.25pct increase; the premium rate of balanced convertible bonds was 22.17%, a 0.05pct increase [2]. Industry Performance - In the A - share market, more than half of the underlying stock industry indices declined, with 16 industries falling. The top three industries with the largest declines were power equipment (-2.22%), computer (-1.59%), and automobile (-1.27%); the top three industries with the largest increases were steel (+2.05%), petroleum and petrochemical (+1.84%), and media (+1.00%) [3]. - In the convertible bond market, 18 industries declined. The top three industries with the largest declines were communication (-2.25%), automobile (-1.07%), and household appliances (-0.96%); the top three industries with the largest increases were building materials (+0.82%), textile and apparel (+0.79%), and building decoration (+0.42%) [3]. - Closing price: The large - cycle sector decreased by 0.04%, the manufacturing sector decreased by 0.57%, the technology sector decreased by 0.81%, the large - consumption sector increased by 0.04%, and the large - finance sector decreased by 0.18% [3]. - Conversion premium rate: The large - cycle sector increased by 0.063pct, the manufacturing sector increased by 1.1pct, the technology sector increased by 0.87pct, the large - consumption sector increased by 0.68pct, and the large - finance sector increased by 0.14pct [3]. - Conversion value: The large - cycle sector decreased by 0.14%, the manufacturing sector decreased by 1.22%, the technology sector decreased by 1.37%, the large - consumption sector remained unchanged, and the large - finance sector decreased by 0.71% [3]. - Pure - debt premium rate: The large - cycle sector decreased by 0.062pct, the manufacturing sector decreased by 0.72pct, the technology sector decreased by 1.2pct, the large - consumption sector increased by 0.054pct, and the large - finance sector decreased by 0.22pct [4]. Industry Rotation - The leading rising industries were steel, petroleum and petrochemical, and media. The daily increase of steel was 2.05%, petroleum and petrochemical was 1.84%, and media was 1.00%. In the convertible bond market, the corresponding daily changes were -0.10%, -0.06%, and -0.66% respectively [54].

Summary of Key Points from Conference Call Industry Overview - The conference call discusses the impact of the national unified childcare subsidy policy on various sectors, particularly focusing on the maternal and infant industry, food and beverage sector, and related consumer goods [1][5][12]. Core Insights and Arguments 1. **Childcare Subsidy Policy**: The national unified childcare subsidy policy is expected to require approximately 120 billion yuan in funding for 2025, accounting for about 0.4% of the general fiscal budget. The central government will primarily fund this, with regional subsidies varying by area [1][3]. 2. **Impact on Retail and Consumption**: The subsidy is projected to boost the social retail total by about 0.2 percentage points, significantly affecting essential categories like maternal and infant food, especially in central and western regions [1][5]. 3. **Investment Opportunities**: Investors are advised to focus on industry rotation opportunities arising from the subsidy, particularly in undervalued Hong Kong stocks. Consumer goods and related supply chains are seen as relatively undervalued, with the subsidy acting as a catalyst for industry rotation rather than an immediate improvement in fundamentals [1][8]. 4. **Market Performance**: In a bullish market atmosphere, public fund positions in Hong Kong stocks have rapidly increased, with total holdings around 17% and investable fund positions nearing 29%. Cyclical industries and consumer goods are expected to be the next focus areas [1][9]. 5. **Healthcare Sector**: The subsidy policy is anticipated to stimulate demand in reproductive health and maternal health sectors in the short term, with companies like Jinxin Reproductive and BGI being highlighted. Mid-term focus includes pediatric drug development, while long-term attention is directed towards specialized services like ophthalmology and dental check-ups [1][11]. Additional Important Content 1. **Food and Beverage Sector**: The food and beverage industry is expected to benefit from increased demand for maternal and infant products, particularly infant formula and dairy products. Companies like Yili, Mengniu, and New Hope are recommended due to their strong market positions [3][13][14]. 2. **Consumer Electronics**: The maternal and infant small appliance market is experiencing rapid growth, with online sales projected to reach approximately 5.3 billion yuan in 2024, showing a compound annual growth rate of 25% from 2017 to 2024. Brands like Bear Electric and Supor are increasing their market share [19][20][21]. 3. **Textile and Apparel Opportunities**: Despite a decline in newborn numbers over the past seven years, the overall market size is growing due to refined parenting and consumption upgrades. Brands in children's clothing and home textiles are expected to benefit from this trend [15]. 4. **Investment in Nursing Centers**: High-end nursing center services are highlighted as a growth area, with companies like Shengmeila showing potential due to their service offerings and market positioning [16]. 5. **Cross-Border E-commerce**: Companies involved in cross-border e-commerce for maternal and infant products, such as Anzheng Fashion, are expected to benefit from the rise in maternal and infant consumption [17]. This summary encapsulates the key points discussed in the conference call, providing insights into the implications of the childcare subsidy policy across various industries and highlighting potential investment opportunities.

1. Report Industry Investment Rating No relevant content provided in the report. 2. Report's Core View - During the week from July 21 to July 26, 2025, the convertible bond market continued its moderate upward trend, with the price center approaching historical highs, the valuation structure stretching overall, and market trading remaining active. The mid - cap style outperformed, and the valuation repair momentum of low - priced and medium - high - priced varieties increased, reflecting improvements in both credit and elasticity preferences. In the equity market, the growth style was dominant, and the continuous inflow of funds into the science - technology innovation and manufacturing sectors drove the active performance of high - elasticity convertible bond individual bonds. The intensity of style and industry rotation increased significantly, and the short - term emotional upsurge required vigilance against the risk of intensified fluctuations. At the current stage, it is recommended to re - evaluate the risk - return ratio and consider a balanced allocation of high - quality low - and medium - priced individual bonds, taking into account fundamental support, valuation safety, and liquidity [2][5]. - The price center of the current convertible bond market continued to rise, and the median weekly average price approached 130 yuan again. The valuation level entered the historical high - level range, and the allocation strategy may need to be adjusted. As some individual bonds with longer durations entered the forced redemption stage, the outstanding scale continued to shrink, and the capacity shortage intensified. Meanwhile, the intensity of industry and style rotation was at a relatively high level, short - term sentiment heated up, and trading games became more prominent. From the perspective of sector rotation, it is recommended to focus on the mainline opportunities of the "anti - involution" related sectors in the current market and the potential opportunities in the commercial retail and transportation sectors. It is also recommended to re - evaluate the risk - return ratio in a high - level environment, pay attention to the rotation and repair opportunities of large - cap and medium - priced varieties, and take into account valuation safety and liquidity support [9]. - The A - share market continued its volatile upward trend during the week, and capital preference remained concentrated in high - elasticity sectors, with the growth style dominant. Small - and medium - cap stocks in the science - technology innovation sector were active, and the cyclical manufacturing sector also received some incremental capital support, forming the market's mainline, and market hotspots showed a structural spread. At the same time, the performance of the weight sectors was weak, and the capital switch may support the acceleration of the sector rotation rhythm, so caution is needed when participating in sector switches. Overall, it is recommended to continuously pay attention to the fundamental support and capital persistence of high - elasticity sectors, and at the same time, be vigilant against the callback risk in high - congestion directions, and maintain the flexibility and balance of the allocation [9]. - The convertible bond market continued to rise during the week, with the mid - cap style outperforming. The market trading sentiment recovered, but the momentum slowed down marginally. In terms of the valuation structure, looking at different market price intervals, the repair momentum of low - and medium - priced and medium - and high - priced varieties was relatively strong. The low - price interval reflected an improvement in credit preference, while the elastic gaming funds in the high - price interval were slightly cautious. The implied volatility continued to rise, and market fluctuations may be magnified periodically. The emotional upsurge requires vigilance against short - term callback risks. At the sector level, sectors such as medicine, basic chemicals, and power equipment received incremental capital support, and the capital concentration increased significantly. In terms of individual bonds, the outstanding performers were mostly driven by the strength of the underlying stocks, showing characteristics of high elasticity and medium - to - short durations. It is recommended to conduct a structured allocation around the direction that emphasizes both fundamental support and valuation elasticity [9]. - The supply rhythm of the primary market of convertible bonds was stable during the week. A total of 2 new bonds were listed, and 9 companies updated their issuance plans. In terms of terms, a total of 6 individual bonds announced that they were expected to trigger a downward revision, 9 announced no downward revision, and 1 individual bond proposed a downward revision. On the redemption side, 9 individual bonds announced that they were expected to trigger redemption, 5 announced early redemption, and 4 clearly stated no early redemption. Overall, the supply continued to advance, and clause games and redemption events occurred frequently. It is recommended to continuously pay attention to the allocation opportunities brought about by individual bond games [9]. 3. Summary According to Relevant Catalogs 3.1 Look at Stocks and Do Bonds: How to Layout When Convertible Bonds Reach High Levels - The median weekly average price of convertible bonds has reached a historical high. Since 2021, the median weekly average price of convertible bonds has gradually increased, briefly reaching the 130 - yuan mark in January and August 2022 but failing to break through effectively later. Currently, with the strengthening of the equity market and the fact that the outstanding convertible bonds are mostly "old bonds" and some high - priced varieties have entered the forced redemption stage, the market outstanding scale has further shrunk. As the median weekly average price of convertible bonds approaches the 130 - yuan mark again, the current allocation strategy needs to be re - evaluated [14]. - From the perspective of industry rotation, the rotation intensity has reached a relatively high historical level. The sum of the absolute values of the changes in the weekly sector price - increase rankings is used as the sector rotation intensity indicator, and the 24 - week average is used for smoothing. Both the current week's rotation intensity and the smoothed 24 - week average are above the 85th percentile since 2010, in a relatively high - level range [14]. - From the perspective of the net financing scale of the entire A - share market, short - term sentiment may enter an over - heated range. The net financing amount of the entire A - share market is positively correlated with the trend of the Wind All - A Index. The net financing amount is at the 98.9th percentile since 2010, and the 4 - week rolling regression slope of the net financing amount is at the 94.3rd percentile since 2010, reflecting a rapid rise in short - term sentiment and a possible entry into an over - heated range [17]. - From the perspective of industry rotation, it is possible to layout opportunities related to sectors in the fourth quadrant. The first - quadrant sectors are the current market mainline, and the fourth quadrant harbors the potential to become the first - quadrant sectors. In the current week, steel, building materials, non - ferrous metals, and coal were the absolute mainlines, and their relative momentum and relative strength indicators increased significantly compared with the previous week. From the perspective of rotation, in the short term, it is recommended to pay attention to the rotation opportunities of the transportation and commercial retail sectors, which are located in the fourth quadrant and have shown good performance in both relative momentum and relative strength indicators compared with the previous week [22]. - From the perspective of convertible bond style rotation, the large - cap and medium - price indexes may be gestating opportunities. The large - cap index and the medium - value index are weaker than other styles in terms of strength and momentum. As the overall price of convertible bonds continues to rise, some funds may choose to take profits and return to the large - cap and medium - price indexes [23]. 3.2 Market Theme Weekly Review 3.2.1 Equity Theme Weekly Review - During the week from July 21 to July 26, 2025, the trading themes in the equity market were active. The infrastructure industry chain related to the Yajiang Hydropower Project saw a surge in trading popularity. The water conservancy and hydropower index led the major theme directions with a weekly price increase of 27.1% and a weekly trading volume of 142.31 billion yuan. Resource - related themes such as the rare earth index, small - metal index, and lithium - ore index had weekly price increases of 24.5%, 17.5%, and 12.4% respectively. Leading - stock indexes, dragon - tiger list indexes, and limit - up trading indexes had weekly price increases of over 20%. The previously pressured high - amplitude index and market sentiment index recovered, rising by 23.3% and 17.8% respectively, indicating that funds were concentrated in high - elasticity fields. The technology field showed structural differentiation, with the chip design index and semiconductor industry index rising by 7.1% and 4.8% respectively, while the previously popular optical module (CPO) index and optical communication index declined by 2.1% and 0.8% respectively. In terms of capital flow, the trading - theme indexes showed a significant upward trend, and the total weekly trading volume of the leading - stock index, dragon - tiger list index, and limit - up trading index exceeded 970 billion yuan. The weekly trading volume of the high - amplitude index was 633.88 billion yuan, significantly increasing compared with the previous week. Overall, market sentiment was high, and short - term funds were active. It is recommended to pay attention to high - elasticity trading opportunities, be cautious when participating in short - term over - heated themes, and maintain the flexibility and balance of the strategy [27]. 3.2.2 Convertible Bond Weekly Review - During the week from July 21 to July 26, 2025, the convertible bond market continued to rise, and the capital style switched to mid - cap elastic varieties, further enhancing market activity. The overall valuation structure showed a repair trend. Looking at different market price intervals, both the low - and high - price intervals showed signs of recovery, but the valuation of the medium - price range was under pressure, indicating that gaming funds were becoming more cautious. The implied volatility fluctuated upward, and market sentiment heated up. At the industry level, both the cyclical and growth styles performed well, and the trading focus was concentrated in the medicine, power equipment, and chemical sectors. In terms of individual bonds, medium - to - short - duration and high - elasticity bonds were favored by the market and led the price increases. The supply rhythm of the primary market was stable, and structural games continued. In terms of allocation, it is recommended to dig for individual bonds with valuation advantages and underlying - stock catalysts among medium - priced varieties, while also participating in rotation market trends and controlling risks [30]. 3.3 Market Weekly Tracking 3.3.1 Main Stock Indexes Strengthened, and Cyclical Sectors Were the Mainline of the Week - **Main stock indexes continued to strengthen, and small - and medium - cap science - technology innovation stocks performed strongly**: During the week from July 21 to July 26, 2025, the main A - share stock indexes continued to strengthen. The Shanghai Composite Index had a weekly price increase of 1.7%, the Shenzhen Component Index had a weekly price increase of 2.3%, and the ChiNext Index led the main stock indexes with a weekly price increase of 2.8%. In terms of style, small - and medium - cap science - technology innovation stocks performed prominently. The CSI 500 Index rose by 4.6% weekly, the CSI 2000 Index had a weekly price increase of 3.3%, the SSE 50 Index had a weekly price increase of 1.7%, and the STAR 50 Index had a weekly price increase of 1.8%. In terms of capital, the market's main funds continued to flow out net during the week, and the outflow pressure increased. The average daily trading volume of the entire market was about 1.8 trillion yuan, a week - on - week increase of 0.3 trillion yuan. The market showed a net capital outflow on all five trading days of the week. The net capital outflow scale expanded from 1.364 billion yuan on Monday to 4.083 billion yuan on Wednesday, then significantly shrank to 0.3 billion yuan on Thursday, and expanded again to 3.098 billion yuan on Friday, possibly indicating short - term profit - taking behavior by funds. The average daily net outflow of main funds during the week was 2.474 billion yuan, an increase of 0.792 billion yuan compared with the previous week, and market sentiment remained cautious [31]. - **The overall performance of different industries strengthened, and cyclical sectors were relatively dominant**: During the week from July 21 to July 26, 2025, the A - share market continued its structural differentiation pattern, and cyclical sectors performed strongly. The steel sector led the Shenwan primary industries with a price increase of 9.1%. The coal and non - ferrous metal sectors followed closely, with weekly price increases of 9.0% and 8.9% respectively. The building materials and building decoration sectors had weekly price increases of 7.9% and 5.9% respectively, and their trading volumes increased week - on - week, indicating the market's preference for cyclical sectors. The previously leading high - elasticity sectors continued their upward trends. The communication and computer sectors had weekly price increases of 7.5% and 4.1% respectively. The consumer sector showed internal structural differentiation. The beauty care and medicine and biology sectors both had weekly price increases of 5.4%, while the food and beverage and household appliances sectors performed relatively weakly, with only 1.5% and 0.1% weekly price increases respectively. The banking sector performed poorly, with a weekly price decline of 2.3%, leading the decliners among all industries. Overall, market funds were concentrated in cyclical sectors. It is recommended to pay attention to cyclical industries with policy support and definite performance, while also considering the technology - growth sectors. Be cautious about previously high - level sectors and guard against adjustment risks [36]. - **The trading volume showed a significant structural flow pattern**: The market funds showed obvious structural flow characteristics during the week, which was positively correlated with the sector price increases. The electronics sector had the highest average daily trading volume of 181.02 billion yuan, a week - on - week increase of 3.47 billion yuan, accounting for 10.0% of the market. The computer sector had an average daily trading volume of 148.48 billion yuan, a week - on - week decrease of 16.95 billion yuan, but still accounting for 8.2% of the market, indicating a relatively high level of overall capital attention. The non - ferrous metals, machinery, and power equipment sectors received incremental capital support of 35.81 billion yuan, 33.71 billion yuan, and 32.40 billion yuan respectively, and their average daily trading volumes were 115.25 billion yuan, 144.15 billion yuan, and 148.16 billion yuan respectively, indicating a strong willingness to layout in cyclical sectors [37]. - **The market sector congestion showed a differentiated pattern**: Cyclical sectors showed obvious congestion characteristics. The infrastructure industry chain centered on the Yajiang Hydropower Project became the main direction of capital allocation. The building materials and building decoration sectors showed obvious characteristics of high trading volume and high turnover rate, with their trading volume percentiles reaching the 100% historical peak and their turnover rate percentiles being 100% and 99% respectively. The capital concentration and trading activity were both at historical high levels. The steel and non - ferrous metal sectors also maintained high popularity, with their trading volume percentiles reaching the 98th percentile and their turnover rate percentiles being 98% and 95% respectively. The transportation sector had both indicators at the 96th percentile of the historical level, reflecting that under the expectation of policy - driven infrastructure industry chain profitability, the capital layout intensity continued to increase. The internal differentiation of the technology - growth sector intensified. The computer sector maintained high activity with a 90% trading volume percentile and an 84% turnover rate percentile. The electronics sector had an 89% trading volume percentile but only a 63% turnover rate percentile, and the communication sector had a 92% trading volume percentile but only a 40% turnover rate percentile, indicating selective capital allocation. The food and beverage sector had a trading volume percentile of only 45% and a turnover rate percentile of only 55%, indicating a low willingness of capital allocation. Overall, currently, funds are concentrated in infrastructure and some cyclical sectors. It is recommended to pay attention to possible short - term adjustment risks and consider potential rotation sectors that may experience high - low switches [43]. 3.3.2 Convertible Bond Market Continued to Strengthen, and Mid - Cap Convertible Bonds Outperformed - **The convertible bond market as a whole continued to rise, and mid - cap convertible bonds led the way**: During the week from July 21 to July 26, 2025, the convertible bond market continued to rise, and the price increase was slightly larger than that of the previous week. In terms of style, mid - cap convertible bonds performed better. The CSI Convertible Bond Index rose by 2.1% weekly, with the Wind Mid - Cap Convertible Bond Index leading the increase at 2.5%, the large - cap index rising by 1.5%, and the small - cap convertible bond index rising by 2.4%. The market as a whole continued to recover, but the momentum weakened marginally. The leading performance of the mid - cap index reflected that funds were biased towards high - elasticity varieties. In terms of capital, the trading activity of the convertible bond market increased significantly, with an average daily trading volume of about 85.86 billion yuan, a week - on - week increase of 12.02 billion yuan [47]. - **The valuation of the convertible bond market stretched overall by parity interval**: In the low - parity interval, there was a repair trend. The conversion premium rate of the below - 80 - yuan interval stretched by 2.08%, and the 80 - 90 - yuan interval stretched by 1.36%. In the 100 - yuan parity interval, the conversion premium rate of the 90 - 100 - yuan interval stretched by 1.78%, and the 100 - 110 - yuan interval stretched by 1.06%. In the medium - and high - parity intervals, the 110 - 120 - yuan interval stretched by 0.55%, the 120 - 130 - yuan interval compressed by 1.06%, and the above - 130 - yuan interval stretched by 1.19%. The valuation of the convertible bond market stretched overall by parity

- Model Name: Diffusion Index Model; Construction Idea: The model is based on the principle of price momentum, capturing industry trends through diffusion indices; Construction Process: The model tracks the weekly and monthly changes in the diffusion indices of various industries, ranking them accordingly. The formula for the diffusion index is not explicitly provided; Evaluation: The model has shown varying performance over the years, with significant drawdowns during market reversals[24][25][28] - Model Name: GRU Factor Model; Construction Idea: The model utilizes GRU (Gated Recurrent Unit) deep learning networks to process minute-level volume and price data, aiming to capture trading information; Construction Process: The model ranks industries based on GRU factors, which are derived from the deep learning network's analysis of trading data. The specific formula for GRU factors is not provided; Evaluation: The model has performed well in short cycles but has shown general performance in longer cycles[31][32][35] - Diffusion Index Model, Average Weekly Return: 0.89%, Excess Return Since July: -3.47%, Excess Return YTD: -0.45%[28] - GRU Factor Model, Average Weekly Return: 4.27%, Excess Return Since July: 1.34%, Excess Return YTD: -4.25%[35] - Factor Name: Diffusion Index; Construction Idea: The factor is based on the momentum of industry prices, capturing upward trends; Construction Process: The factor is calculated by observing the weekly and monthly changes in the diffusion indices of various industries. The specific formula is not provided; Evaluation: The factor has shown varying performance, with significant drawdowns during market reversals[24][25][28] - Factor Name: GRU Factor; Construction Idea: The factor is derived from GRU deep learning networks, capturing trading information from minute-level volume and price data; Construction Process: The factor is calculated by ranking industries based on the GRU network's analysis of trading data. The specific formula is not provided; Evaluation: The factor has performed well in short cycles but has shown general performance in longer cycles[31][32][35] - Diffusion Index Factor, Top Industries: Comprehensive Finance (1.0), Steel (1.0), Non-Bank Finance (0.999), Comprehensive (0.998), Non-Ferrous Metals (0.997), Home Appliances (0.995)[25] - GRU Factor, Top Industries: Banking (3.3), Real Estate (0.58), Oil & Petrochemicals (-1.26), Textile & Apparel (-1.73), Light Manufacturing (-2.49), Electric Power & Utilities (-2.83)[32]

Core Viewpoint - The article discusses the investment strategy of Hu Zhongyuan, a fund manager at Huashang Fund, emphasizing the importance of both offensive and defensive strategies in investment, particularly during market adjustments [4][8]. Group 1: Investment Strategy - Hu Zhongyuan employs a "dual diversification" strategy in product allocation, focusing on industry diversification to reduce portfolio volatility by including both high-growth and stable defensive sectors [5][9]. - The fund managed by Hu Zhongyuan, Huashang Runfeng Flexible Allocation Mixed Fund, has shown impressive long-term performance, with a net value increase of 193.98% over nearly seven years, significantly outperforming the benchmark and the CSI 300 index [5][6]. - The investment framework is based on industry cycles and win rates, selecting industries with upward revenue and profit trends for allocation, while avoiding a preset preference for any specific industry [6][7]. Group 2: Market Adaptation - Hu Zhongyuan has demonstrated a proactive approach to market changes, such as shifting investments from high-valued sectors like liquor and pharmaceuticals to undervalued sectors like coal and pork during market fluctuations [7][10]. - The fund's performance during market downturns has been notable, with a smaller drawdown compared to many peers, attributed to a mix of defensive public utilities and bond assets [10]. Group 3: Market Outlook - The current market is viewed as favorable, with structural opportunities expected due to ongoing policy support, ample liquidity, and evolving industry dynamics [11][12]. - Key factors supporting the A-share market include sustained policy effects, a favorable funding environment, and emerging structural investment opportunities in sectors like artificial intelligence, new consumption, and innovative pharmaceuticals [12][13][14].

主动权益基金情绪偏乐观， 证券研究报告 银行行业配置达到历史高位 —— 量化市场追踪周报（2025W30） 请阅读最后一页免责声明及信息披露 http://www.cindasc.com 1 [Table_ReportTime] 2025 年 4 月 27 日 金工研究 [Table_ReportType] 金工定期报告 [Table_Author] 于明明 金融工程与金融产品 首席分析师 执业编号：S1500521070001 联系电话：+86 18616021459 邮 箱：yumingming@cindasc.com 吴彦锦 金融工程与金融产品 分析师 执业编号：S1500523090002 联系电话：+86 18616819227 邮 箱：wuyanjin@cindasc.com 周君睿 金融工程与金融产品 分析师 执业编号：S1500523110005 联系电话：+86 19821223545 邮 箱：zhoujunrui@cindasc.com [Table_Title] 量化市场追踪周报(2025W30)：主动权益基金情绪 偏乐观，银行行业配置达到历史高位 [Table_ReportDate] ...