Quantitative Models and Construction Methods - **Model Name**: Diffusion Index Model **Model Construction Idea**: Based on price momentum principles, the model identifies upward trends in industries to optimize allocation decisions[23][24][27] **Model Construction Process**: 1. Calculate the diffusion index for each industry based on price momentum 2. Rank industries by their diffusion index values 3. Allocate to industries with the highest diffusion index values **Evaluation**: The model performs well in capturing upward trends but struggles during market reversals or when trends shift to oversold rebounds[23][27] - **Model Name**: GRU Factor Model **Model Construction Idea**: Utilizes GRU (Gated Recurrent Unit) deep learning networks to analyze minute-level volume and price data for industry rotation[31][32][36] **Model Construction Process**: 1. Input minute-level volume and price data into the GRU network 2. Train the model on historical data to identify industry rotation signals 3. Rank industries based on GRU factor scores and allocate accordingly **Evaluation**: The model adapts well to short-term market dynamics but faces challenges in long-term performance and extreme market conditions[31][38] Model Backtesting Results - **Diffusion Index Model**: - Weekly average return: -1.26% - Excess return over equal-weighted industry index: -1.99% - November excess return: -0.74% - Year-to-date excess return: 1.84%[22][27] - **GRU Factor Model**: - Weekly average return: 1.72% - Excess return over equal-weighted industry index: 1.00% - November excess return: 2.69% - Year-to-date excess return: -3.34%[31][36] Quantitative Factors and Construction Methods - **Factor Name**: Diffusion Index **Factor Construction Idea**: Measures industry momentum by tracking price trends and ranking industries accordingly[24][25][26] **Factor Construction Process**: 1. Calculate the diffusion index for each industry using price trend data 2. Rank industries based on diffusion index values 3. Identify industries with the highest and lowest diffusion index values for allocation decisions **Evaluation**: Effective in identifying upward trends but sensitive to market reversals[23][24] - **Factor Name**: GRU Factor **Factor Construction Idea**: Derived from GRU deep learning networks, the factor captures industry rotation signals based on volume and price dynamics[31][32][36] **Factor Construction Process**: 1. Train GRU networks on historical minute-level data 2. Generate GRU factor scores for industries 3. Rank industries by GRU factor scores for allocation decisions **Evaluation**: Strong adaptability to short-term market changes but limited robustness in long-term scenarios[31][38] Factor Backtesting Results - **Diffusion Index Factor**: - Top industries by diffusion index: Nonferrous metals (0.991), Banking (0.968), Steel (0.949), Communication (0.918), Electric equipment & new energy (0.914), Comprehensive (0.885)[24][25][26] - Weekly average return: -1.26% - Excess return over equal-weighted industry index: -1.99% - November excess return: -0.74% - Year-to-date excess return: 1.84%[22][27] - **GRU Factor**: - Top industries by GRU factor: Comprehensive (3.41), Real estate (2.63), Petroleum & petrochemical (2.13), Light manufacturing (1.67), Steel (0.53), Comprehensive finance (0.52)[32][35][36] - Weekly average return: 1.72% - Excess return over equal-weighted industry index: 1.00% - November excess return: 2.69% - Year-to-date excess return: -3.34%[31][36]

Group 1 - Northbound capital activity has rebounded, with a net buying of A-shares, particularly in the computer, food and beverage, and non-ferrous metal sectors, while there was net selling in the machinery sector [1][10] - Margin trading activity has also slightly increased, reaching a three-week high, with net buying mainly in the electric new energy, communication, and machinery sectors, and net selling in food and beverage, oil and petrochemicals, and coal sectors [16][39] - The trading heat and volatility in the market have risen, with sectors like communication, electronics, electric new energy, chemicals, machinery, and real estate showing trading heat above the 80th percentile [2][5] Group 2 - The ETF market has seen net subscriptions, primarily in institutional ETFs, with significant net buying in sectors such as electronics, non-bank financials, and pharmaceuticals, while there was net selling in electric new energy, chemicals, and banking sectors [31][32] - The buy-sell ratio of the top 10 active northbound stocks compared to the overall northbound trading has shown a slight increase, indicating a shift in trading dynamics [13] - The buy consensus for ETFs and northbound trading has decreased, while the buy consensus for margin trading and the dragon and tiger list has increased, suggesting a mixed sentiment among market participants [39]

1. Report Industry Investment Rating - Not provided in the given content 2. Core Views of the Report - Overseas Fed's policy shift may lead to global liquidity easing, opening up space for China's reserve - requirement ratio and interest - rate cuts. The market is still dominated by liquidity - easing trades. The next Fed meeting is on October 29, and the market expects a 25 - bps rate cut. Attention should be paid to the US September non - farm and inflation data in early - mid October. The transmission of Fed's preventive rate cuts to the US real economy takes about 2 - 3 months [6]. - China's economic growth slowed in Q3. There is an expectation that the funds from existing growth - stabilizing policies will be in place faster, and attention should be paid to the implementation of 500 billion yuan in financial policy tools and new directions in the "14th Five - Year Plan". Investment data slowed significantly from July to August, especially infrastructure investment. There is a risk that infrastructure funds in Q4 may fall short of expectations. However, the GDP growth rates in Q3 and Q4 are expected to be 4.9% and 4.7% respectively, and the annual 5% target can still be achieved [6]. - After the policies at home and abroad are settled, risk assets may experience a short - term adjustment. In the next 1 - 2 quarters, global loose liquidity and fiscal leverage - driven economic recovery expectations will support risk assets. In the medium - term from Q4 this year to H1 next year, the expected performance order is equities > commodities > bonds. In Q4, the stock market is expected to be volatile, domestic commodities depend on policies, overseas commodities such as gold and non - ferrous metals are favored, the weak US dollar trend continues but with a slower slope. Domestic bonds' allocation value increases after the interest - rate rise, and they should be evenly allocated with equities in Q4. Gold is for long - term strategic allocation, and rate cuts are the main logic in Q4 [6]. 3. Summary by Relevant Catalogs 3.1 Macro Highlights - **Overseas Macro**: After the Fed's policy shift, a new round of global liquidity easing is expected. The Fed's independence risk may increase the potential for future rate cuts. Attention should be paid to the US economic data before the next Fed meeting [6]. - **Domestic Macro**: China's economic growth slowed in Q3. There are risks in infrastructure investment in Q4, but the annual GDP target can still be achieved. The probability of the implementation of existing funds and new policies in Q4 will increase if investment and exports continue to decline in September [6]. - **Asset Views**: In the medium - term, equities are expected to perform better than commodities and bonds. In Q4, the stock market is volatile, domestic commodities depend on policies, overseas gold and non - ferrous metals are favored, and bonds' allocation value increases. Gold is for long - term strategic investment [6]. 3.2 View Highlights 3.2.1 Financial - **Stock Index Futures**: Use a dumbbell structure to deal with market divergence. The short - term judgment is "oscillating" due to the attenuation of incremental funds [7]. - **Stock Index Options**: Continue the hedging and defensive strategy. The short - term judgment is "oscillating" considering the possible deterioration of option market liquidity [7]. - **Treasury Bond Futures**: The stock - bond seesaw may continue in the short term. The short - term judgment is "oscillating" with concerns about unexpected changes in tariffs, supply, and monetary easing [7]. 3.2.2 Precious Metals - **Gold/Silver**: Driven by dovish expectations, prices are rising. The short - term judgment is "oscillating and rising", and attention should be paid to the US fundamentals, Fed's monetary policy, and global equity market trends [7]. 3.2.3 Shipping - **Container Shipping to Europe**: The peak season in Q3 has passed, and there is no upward driving force. The short - term judgment is "oscillating", and attention should be paid to the rate of freight - rate decline in September [7]. 3.2.4 Black Building Materials - **Steel Products**: Demand recovery is slow, and there are continuous policy disturbances. The short - term judgment is "oscillating", and attention should be paid to the progress of special - bond issuance, steel exports, and iron - water production [7]. - **Iron Ore**: Shipments have decreased, and port inventories have increased. The short - term judgment is "oscillating", and attention should be paid to overseas mine production and shipments, domestic iron - water production, weather, port inventories, and policy dynamics [7]. - **Coke**: The fundamentals are healthy, and the spot price is stable. The short - term judgment is "oscillating", and attention should be paid to steel - mill production, coking costs, and macro sentiment [7]. - **Coking Coal**: Spot transactions are good, and the futures price has a slight correction. The short - term judgment is "oscillating", and attention should be paid to steel - mill production, coal - mine safety inspections, and macro sentiment [7]. - **Silicon Iron**: Supply - demand drivers are limited, and the futures price has fallen from a high level. The short - term judgment is "oscillating", and attention should be paid to raw material costs and steel procurement [7]. - **Manganese Silicon**: Supply - demand expectations are pessimistic, and the price is under pressure. The short - term judgment is "oscillating", and attention should be paid to cost prices and overseas quotes [7]. - **Glass**: Futures and spot inventories have increased significantly, and mid - stream restocking is coming to an end. The short - term judgment is "oscillating", and attention should be paid to spot sales [7]. - **Soda Ash**: Inventory has been continuously transferred, and upstream inventory has decreased significantly. The short - term judgment is "oscillating", and attention should be paid to soda - ash inventory [7]. 3.2.5 Non - Ferrous Metals and New Materials - **Copper**: There are new disturbances in copper - ore supply, and the copper price is oscillating strongly. The short - term judgment is "oscillating and rising", and attention should be paid to supply disturbances, domestic policies, Fed's policy, domestic demand recovery, and economic recession risks [7]. - **Alumina**: The spot market is weak, and inventory is accumulating. The alumina price is under pressure. The short - term judgment is "oscillating", and attention should be paid to ore production recovery, electrolytic - aluminum production recovery, and extreme market trends [7]. - **Aluminum**: Inventory continues to accumulate, and the aluminum price is oscillating. The short - term judgment is "oscillating", and attention should be paid to macro risks, supply disturbances, and demand shortfalls [7]. - **Zinc**: Inventory continues to accumulate, and the zinc price is oscillating. The short - term judgment is "oscillating", and attention should be paid to macro risks and zinc - ore supply recovery [7]. - **Lead**: Supply of recycled lead has decreased, and the lead price is rising. The short - term judgment is "oscillating and rising", and attention should be paid to supply - side disturbances and battery exports [7]. - **Nickel**: Indonesia has cracked down on illegal mining, and the nickel price is oscillating widely. The short - term judgment is "oscillating", and attention should be paid to macro and geopolitical risks, Indonesian policies, and supply - chain issues [7]. - **Stainless Steel**: Cost support is strong, and the stainless - steel futures price has risen significantly. The short - term judgment is "oscillating", and attention should be paid to Indonesian policies and demand growth [7]. - **Tin**: The resumption of production in Wa State is slower than expected, and the tin price is oscillating at a high level. The short - term judgment is "oscillating", and attention should be paid to the resumption of production and demand improvement in Wa State [7]. - **Industrial Silicon**: Supply is increasing, suppressing the silicon price. The short - term judgment is "oscillating", and attention should be paid to supply - side production cuts and photovoltaic installation [7]. - **Lithium Carbonate**: Fundamental drivers are weak, and the price is oscillating. The short - term judgment is "oscillating", and attention should be paid to demand, supply disturbances, and technological breakthroughs [7]. 3.2.6 Energy and Chemicals - **Crude Oil/LPG**: Supply pressure continues, and there are geopolitical disturbances. The short - term judgment for crude oil is "oscillating and falling", and for LPG is "oscillating", with attention to OPEC+ policies and Middle - East geopolitics [9]. - **Asphalt**: The futures price is under pressure at the 3500 level. The short - term judgment is "oscillating and falling", and attention should be paid to sanctions and supply disturbances [9]. - **High - Sulfur Fuel Oil**: The fuel - oil futures price is weakly oscillating. The short - term judgment is "oscillating and falling", and attention should be paid to geopolitics and crude - oil prices [9]. - **Low - Sulfur Fuel Oil**: It follows the weak trend of crude oil. The short - term judgment is "oscillating and falling", and attention should be paid to crude - oil prices [9]. - **Methanol**: Affected by olefins and port inventory, the short - term judgment is "oscillating", and attention should be paid to macro - energy and upstream - downstream device dynamics [9]. - **Urea**: The price is under cost pressure, and there is a risk of an emotional rebound. The short - term judgment is "oscillating", and attention should be paid to export policies and the seventh Indian tender [9]. - **Ethylene Glycol**: Market sentiment is affected by future inventory accumulation. The short - term judgment is "oscillating", and attention should be paid to coal and oil prices, port inventory, and device operations [9]. - **PX**: Due to postponed device maintenance and capacity expansion, the supply - demand balance has weakened. The short - term judgment is "oscillating", and attention should be paid to crude - oil price fluctuations, macro changes, and demand during the peak season [9]. - **PTA**: Low processing fees lead to more production cuts. The short - term supply - demand situation has improved, but the long - term oversupply remains. The short - term judgment is "oscillating", and attention should be paid to crude - oil price fluctuations, macro changes, and demand during the peak season [9]. - **Short - Fiber**: Terminal orders have improved slightly, but high supply poses risks. The short - term judgment is "oscillating", and attention should be paid to downstream yarn - mill purchases and peak - season demand [9]. - **Bottle Chips**: There is short - term replenishment, but long - term demand recovery is uncertain. The short - term judgment is "oscillating", and attention should be paid to production - cut targets and terminal demand [9]. - **Propylene**: The price difference with PP oscillates between 500 - 550. The short - term judgment is "oscillating", and attention should be paid to oil prices and domestic macro - economy [9]. - **PP**: There may be support at the previous low. The short - term judgment is "oscillating", and attention should be paid to oil prices and domestic and overseas macro - economies [9]. - **Plastic**: Maintenance support is limited, and the price is falling. The short - term judgment is "oscillating", and attention should be paid to oil prices and domestic and overseas macro - economies [9]. - **Styrene**: Market sentiment has improved, and attention should be paid to policy details. The short - term judgment is "oscillating", and attention should be paid to oil prices, macro policies, and device operations [9]. - **PVC**: There is a situation of weak reality and strong expectation. The short - term judgment is "oscillating", and attention should be paid to expectations, costs, and supply [9]. - **Caustic Soda**: There are expectations of alumina production resumption, and the caustic - soda price is rising. The short - term judgment is "oscillating", and attention should be paid to market sentiment, production, and demand [9]. 3.2.7 Agriculture - **Oils and Fats**: The expected production of Malaysian palm oil in September has decreased month - on - month. The short - term judgment is "oscillating", and attention should be paid to US soybean weather and Malaysian palm - oil supply - demand data [9]. - **Protein Meal**: There is pre - holiday restocking, and the futures price has rebounded from the lower end of the range. The short - term judgment is "oscillating and rising", and attention should be paid to US soybean weather, domestic demand, and trade relations [9]. - **Corn/Starch**: Farmers are more willing to sell, and the futures price has broken through the previous low. The short - term judgment is "oscillating", and attention should be paid to demand, macro - economy, and weather [9]. - **Pigs**: Supply and demand are loose, and the price is weak. The short - term judgment is "oscillating and falling", and attention should be paid to farming sentiment, epidemics, and policies [9]. - **Rubber**: There is positive sentiment from data correction, and attention should be paid to its sustainability. The short - term judgment is "oscillating", and attention should be paid to production - area weather, raw - material prices, and macro - changes [9]. - **Synthetic Rubber**: The futures price is oscillating within a range. The short - term judgment is "oscillating", and attention should be paid to crude - oil price fluctuations [9]. - **Cotton**: The cotton price has adjusted downward in advance due to expectations of a new - crop supply increase. The short - term judgment is "oscillating", and attention should be paid to demand and inventory [9]. - **Sugar**: The fundamentals have not improved, and the sugar price is looking for support. The short - term judgment is "oscillating", and attention should be paid to imports [9]. - **Pulp**: The spot market is weak, and the pulp price is oscillating. The short - term judgment is "oscillating", and attention should be paid to macro - economic changes and US dollar - based quotes [9]. - **Offset Printing Paper**: The price is oscillating narrowly. The short - term judgment is "oscillating", and attention should be paid to production - sales, education policies, and paper - mill operations [9]. - **Logs**: The futures price is fluctuating narrowly. The short - term judgment is "oscillating", and attention should be paid to shipments and dispatches [9].

Quantitative Models and Construction Methods 1. Model Name: Diffusion Index Industry Rotation Model - **Model Construction Idea**: The model is based on the principle of price momentum, aiming to capture upward trends in industries through a diffusion index[26][27] - **Model Construction Process**: 1. Calculate the diffusion index for each industry based on price momentum 2. Rank industries by their diffusion index values 3. Select top industries for allocation based on their rankings 4. Adjust the portfolio monthly or weekly based on updated diffusion index rankings[26][27] - **Model Evaluation**: The model has shown stable performance in certain years (e.g., 2022 with an annual excess return of 6.12%) but struggled during market reversals or concentrated market themes, such as in 2024 and 2025[26][33] 2. Model Name: GRU Factor Industry Rotation 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[38] - **Model Construction Process**: 1. Input high-frequency volume and price data into the GRU network 2. Train the GRU model on historical data to identify patterns in industry rotation 3. Generate factor scores for industries based on the GRU model's output 4. Rank industries by their GRU factor scores and allocate to top-ranked industries[38][34] - **Model Evaluation**: The model performs well in short cycles but struggles in long cycles or extreme market conditions. It has shown difficulty in capturing excess returns in concentrated market themes during 2025[33][38] --- Model Backtesting Results 1. Diffusion Index Industry Rotation Model - **Weekly Average Return**: -1.74%[30] - **Excess Return (Weekly)**: -1.41%[30] - **Excess Return (September 2025)**: -1.88%[30] - **Excess Return (2025 YTD)**: 2.76%[25][30] 2. GRU Factor Industry Rotation Model - **Weekly Average Return**: -0.72%[36] - **Excess Return (Weekly)**: -0.38%[36] - **Excess Return (September 2025)**: -0.10%[36] - **Excess Return (2025 YTD)**: -7.78%[33][36] --- Quantitative Factors and Construction Methods 1. Factor Name: Diffusion Index - **Factor Construction Idea**: Measures the breadth of price momentum across industries to identify upward trends[26][27] - **Factor Construction Process**: 1. Calculate the proportion of stocks in an industry with positive price momentum 2. Aggregate these proportions to derive the diffusion index for the industry 3. Rank industries based on their diffusion index values[27][28] - **Factor Evaluation**: Effective in capturing upward trends but vulnerable to reversals and underperformance in counter-trend markets[26][33] 2. Factor Name: GRU Factor - **Factor Construction Idea**: Utilizes GRU deep learning to analyze high-frequency trading data and generate predictive scores for industry rotation[38] - **Factor Construction Process**: 1. Input high-frequency trading data into the GRU network 2. Train the model to recognize patterns in industry rotation 3. Output factor scores for industries based on the model's predictions[38][34] - **Factor Evaluation**: Strong in short-term predictions but less effective in long-term or extreme market conditions[33][38] --- Factor Backtesting Results 1. Diffusion Index - **Top Industries (Weekly)**: Non-ferrous Metals (0.978), Banking (0.968), Communication (0.946), Electronics (0.877), Automotive (0.874), Retail (0.873)[27] - **Bottom Industries (Weekly)**: Food & Beverage (0.354), Real Estate (0.46), Coal (0.487), Transportation (0.543), Construction (0.574), Building Materials (0.618)[27] 2. GRU Factor - **Top Industries (Weekly)**: Non-ferrous Metals (7.4), Petrochemicals (5.38), Coal (4.17), Steel (4.15), Building Materials (3.46), Non-banking Financials (3.08)[34] - **Bottom Industries (Weekly)**: Comprehensive Finance (-19.42), Utilities (-13.41), Electronics (-13.18), Pharmaceuticals (-11.14), Automotive (-10.07), Consumer Services (-10.04)[34]

1. Report Industry Investment Rating - Not provided in the content 2. Core Viewpoints of the Report - A-share market continued to rebound this week with an oscillating upward trend. The growth style performed well, driving up TMT-themed funds. However, many quantitative index-enhanced products still had mediocre excess returns. The weekly average daily trading volume of the two markets decreased by 10.63% week-on-week. If the trading volume continues to shrink, the chips in high-position sectors will loosen and differentiate, and the market will shift from a unilateral rise to a range-bound pattern. It is recommended to focus on the supplementary rise opportunities of low-position sectors. The basis of four types of stock index futures contracts showed differentiation, with the IM contract having a large discount and the IF contract having a large premium. In the upcoming week with a dense schedule of important macroeconomic events, the A-share market is likely to maintain a volatile and relatively strong market. It is recommended to focus on technology frontier tracks such as robotics and AI computing power, and also seize the rotation and supplementary rise opportunities of sectors such as securities, pig cycles, and games. After a deep adjustment, the national debt market has shown rare allocation value, and investors are advised to moderately increase the allocation ratio [1][11][16]. 3. Summary According to Relevant Catalogs 3.1 This Week's Market Review 3.1.1 Industry Index - The A-share market continued to rebound this week, with the growth style performing well and driving up TMT-themed funds. The weekly average daily trading volume of the two markets was 2.3 trillion yuan, a week-on-week decrease of 10.63%. The basis of four types of stock index futures contracts showed differentiation, and the average and median returns of neutral hedge funds this week were -0.06% and -0.08% respectively. This week, the electronics, real estate, agriculture, forestry, animal husbandry, and fishery, media, and computer sectors led the gains. The real estate and agriculture, forestry, animal husbandry, and fishery sectors had a relatively large increase in the weekly trading volume ratio compared with last week, while the trading activity of the comprehensive finance and national defense and military industry sectors decreased significantly. The real estate sector rose 5.82% this week, and the weekly trading volume ratio increased to a new high in the past four weeks at 1.50%. The power equipment and new energy sector only rose 0.50% this week, and the weekly trading volume ratio was a new high in the past four weeks at 9.04%, and the sector may face short-term adjustment pressure [11]. 3.1.2 Market Style - This week, the growth style index rose 3.56%, and the weekly trading volume ratio slightly decreased to 58.73%. The consumption style index rose 0.88%, and the weekly trading volume ratio increased to 11.85%. The financial style index performed weakly in the past month, rising only 0.24% this week, and the weekly trading volume ratio decreased significantly to a new low in the past four weeks at 5.59%. The cyclical style index rose 1.87%, and the weekly trading volume ratio increased to a new high in the past four weeks at 20.69%. The stable style index rose 1.14%, and the weekly trading volume ratio increased significantly to a new high in the past four weeks at 3.13%. Based on the CSI A-share index, the CSI 500 index led the gains this week, rising 3.38%, and the weekly trading volume ratio was a new high in the past four weeks at 19.03%, while the Shanghai and Shenzhen 300 index only rose 1.38%, and the weekly trading volume ratio decreased to 27.65%. In the past three months, the market has shown highly structured characteristics, and the CSI 500 index has performed strongly. In an environment with abundant liquidity, funds clearly prefer opportunities with certainty, driving the collective supplementary rise of high-quality leading stocks in various industries [15]. 3.2 Active Equity Funds 3.2.1 Funds with Excellent Performance in Different Thematic Tracks This Week - The report screened single-track and double-track funds based on six sectors: TMT, financial real estate, consumption, medicine, manufacturing, and cycle. Single-track funds are those with a position in a certain sector greater than 70% for multiple consecutive periods, and double-track funds are those with positions in two sectors both greater than 30% for multiple consecutive periods. The report listed the top five funds in each sector in terms of performance this week [20][21]. 3.2.2 Funds with Excellent Performance in Different Strategy Classifications - The report improved the growth, BP, and profit factors to obtain growth, valuation, and quality factors, and divided the funds into different types such as deep undervaluation, high growth, high quality, quality growth, quality undervaluation, GARP, and balanced cost-effectiveness. It also listed the funds with relatively excellent performance in different types of funds this week [22]. 3.3 Index-Enhanced Funds 3.3.1 Distribution of Excess Returns of Index-Enhanced Funds This Week - This week, the Shanghai Composite Index rose 1.52%, the Shenzhen Component Index rose 2.65%, the ChiNext Index rose 2.10%, the STAR 50 rose 5.48%, and the Beijing Stock Exchange 50 fell 1.07%. The representative indexes of the value style sector, such as the Shanghai 50, CSI 100, and Shanghai and Shenzhen 300, rose 0.89%, 1.54%, and 1.38% respectively, while the representative indexes of the growth style sector, such as the Small and Medium 100, CSI 500, CSI 1000, and CSI 2000, rose 3.66%, 3.38%, 2.45%, and 2.16% respectively. The report also listed the average and median excess returns of different index-enhanced funds and the top three funds in terms of excess returns in each category this week [25][26][30]. 3.4 This Week's Fund High-Frequency Position Detection - After excluding funds with high positions in Hong Kong stocks and Beijing Stock Exchange stocks, funds with a scale of less than 200 million yuan, industry-themed funds, and quantitative funds, the results showed that active equity funds significantly increased their positions in the basic chemical (0.61%), machinery (0.24%), and power equipment and new energy (0.19%) industries this week, and significantly reduced their positions in the electronics (0.55%), computer (0.41%), and national defense and military industry (0.19%) industries. From a one-month perspective, the positions in the electronics (2.12%) and communication (0.97%) industries increased significantly, while the positions in the banking (1.11%) and automobile (1.04%) industries decreased significantly [3][43].

Group 1 - The Hong Kong stock market faced overall pressure, with the Hang Seng Index declining by 1.12% to close at 25,058.51, the Hang Seng Tech Index down 1.85% to 5,578.86, and the Hang Seng China Enterprises Index falling 1.25% to 8,937.09 [6][8] - The market's trading volume reached HKD 302.23 billion, with net inflows from southbound funds amounting to HKD 706 million [2][8] - Sectors with stable cash flow and high defensive attributes, such as utilities, coal, and banks, showed resilience and outperformed the market despite the overall downturn [6][8] Group 2 - In terms of sector performance, the power equipment and new energy sectors led gains with an increase of 1.46%, while sectors like non-ferrous metals and pharmaceuticals saw declines of 4.94% and 4.01%, respectively [6][8] - The report highlights a market style shift, with funds rotating towards sectors that exhibit strong defensive characteristics amid market volatility [8] - Future outlook suggests potential for Hong Kong stocks to reach new highs, driven by AI technology, sustained inflows from southbound funds, and favorable monetary conditions [8]

Macro Liquidity - The US dollar index rebounded last week, and the degree of "inversion" in the China-US interest rate spread deepened. The nominal and real yields of 10Y US Treasuries both increased, indicating a rise in inflation expectations [1][15] - Offshore dollar liquidity has marginally eased, while the domestic interbank funding situation remains overall balanced and slightly loose, with a slight narrowing of the yield spread between 10Y and 1Y [1][20] Market Trading Activity - Overall market trading activity has increased, with most industry trading heat above the 80th percentile. Major index volatility has also risen, although most industry volatilities remain below the 40th historical percentile [1][27] - The trading heat in sectors such as light industry, textiles, retail, computing, construction materials, and financial real estate is notably high [1][30] Institutional Research - High research activity is observed in sectors such as electronics, pharmaceuticals, home appliances, computing, retail, and non-ferrous metals, with real estate, home appliances, oil and petrochemicals, and telecommunications also seeing a rise in research activity [2] Analyst Forecasts - Analysts have raised net profit forecasts for the entire A-share market for 2025/2026. Sectors such as telecommunications, chemicals, non-ferrous metals, electric new energy, electronics, non-bank financials, construction, media, food and beverage, and home appliances have all seen upward adjustments in their profit forecasts [3][4] - The net profit forecasts for the CSI 500, ChiNext Index, and CSI 300 have been raised, while the forecast for the SSE 50 has been adjusted both up and down [3][4] - In terms of investment style, mid-cap/small-cap growth and mid-cap value sectors have seen upward adjustments in their profit forecasts for 2025/2026, while large-cap growth and large/mid/small-cap value sectors have seen downward adjustments [3][4] Northbound Trading Activity - Northbound trading activity has rebounded, with overall net purchases of A-shares. The average daily trading volume and proportion of northbound trading have both increased significantly [5][6] - Based on the top 10 active stocks, the trading volume ratio for northbound trading in sectors such as banking, telecommunications, electric utilities, computing, electric new energy, and non-ferrous metals has risen, while it has fallen in sectors like home appliances, automobiles, electronics, non-bank financials, pharmaceuticals, and agriculture [5][6] Margin Financing Activity - Margin financing activity has increased, with net purchases amounting to 22.546 billion yuan last week. The main net purchases were in non-ferrous metals, computing, non-bank financials, electric new energy, and electronics, while net sales were seen in food and beverage, transportation, oil and petrochemicals, and real estate [4][6] - The financing purchase ratio has increased in sectors such as coal, textiles, agriculture, military, and transportation [4][6] Fund Activity - Active equity funds have increased their positions, particularly in sectors like automobiles, TMT, home appliances, electric new energy, pharmaceuticals, and non-ferrous metals, while reducing positions in oil and petrochemicals, electric utilities, real estate, coal, and construction [6][9] - ETFs have seen overall net subscriptions, primarily driven by individual ETFs, with significant net purchases in sectors like electronics, military, banking, coal, steel, and machinery, while net sales were observed in non-bank financials, pharmaceuticals, electric new energy, telecommunications, media, and computing [6][9]