Report Industry Investment Rating No information provided in the content. Core Viewpoints - The current convertible bond of Yingliu Co., Ltd. raises 1.5 billion yuan. After deducting issuance fees, it will be used for the blade machining and coating project, the intelligent upgrading project of advanced nuclear energy materials and key components, and supplementing working capital and repaying bank loans. It will be listed on October 22, 2025. - The expected listing price is above 130 yuan. The bond rating of Yingliu Convertible Bond is AA+. The latest parity is 112.5 yuan. Considering the high sentiment in the convertible bond market since July and the high prosperity of the company's industry, the conversion premium rate on the listing day is expected to be between 25 - 30%, and the listing price will be above 130 yuan. If the price is below 140 yuan, it can be actively concerned [1]. Summary by Directory I. Convertible Bond Clause Analysis - The issuance scale of the company's current convertible bond is 1.5 billion yuan, with a term of 6 years. The initial conversion price is 30.47 yuan. Calculated at the initial conversion price, it can be converted into 49.2287 million A - shares of Yingliu Co., Ltd. The dilution rate of full conversion on the company's total A - share capital and non - restricted tradable shares is 7.25%. The conversion period starts from March 25, 2026, to the maturity date of the convertible bond (September 18, 2031). The original shareholder placement ratio is 78.4% [10]. - The 6 - year coupon rates of the convertible bond are 0.10% in the first year, 0.30% in the second year, 0.60% in the third year, 1.00% in the fourth year, 1.50% in the fifth year, and 2.00% in the sixth year, slightly lower than the industry average. The maturity redemption price is 109 yuan. The bond is rated AA+ for both the issuer and the bond, and there is no guarantee. The additional terms include a conversion price correction clause (15/30, 85%), a conditional redemption clause (15/30, 130%), and a put clause (30, 70%) [11][12]. - As of October 20, 2025, the latest closing price is 34.27 yuan, corresponding to a parity of 112.47 yuan. The calculated pure bond value is 97.67 yuan, with good bond - bottom protection. The yield to maturity is 2.00%, higher than the yield of the same - term treasury bond [12]. II. Underlying Stock Fundamentals - It is a private enterprise with relatively dispersed equity. As of the first half of 2025, Mr. Du Yingliu directly holds 1.71% of the company's shares and controls 27.37% through Yingliu Investment. Together with the shares held by the consistent action persons of the controlling shareholder, he controls 34.74% of the company's shares in total and serves as the chairman and general manager [13]. - The company's main products are high - temperature alloy products, precision cast steel products, nuclear power and other medium - and large - sized cast steel products, and new materials and equipment, which are mainly used in high - end equipment fields such as aerospace, gas turbines, and nuclear power. Its manufacturing technology and production equipment are domestically leading, and its products are exported to more than 40 countries and regions, serving more than 100 customers, including domestic and global industry leaders [16]. - In the first half of 2025, the company's sales revenue was 1.384 billion yuan, a year - on - year increase of 9.11%. The revenue of high - temperature alloy products and precision castings was 842 million yuan, accounting for 63%. The revenue scale of the two - engine products has been steadily increasing, and the overseas revenue accounted for 47.4% [19]. - The company's gross profit margin has remained at a high level, around 36% in the past few years. The period expenses have gradually decreased, with the management expense rate dropping to around 8%, the sales expense rate remaining at around 1%, and the financial expense rate dropping to around 4% [22]. - The company has maintained a high - intensity R & D investment, with an R & D expense rate of over 10% for many years and a long - term technical staff ratio of over 20% [26]. - The two - engine business has high industrial chain prosperity. The downstream orders in the gas turbine and aero - engine fields are growing rapidly, and the company's two - engine business orders are also growing rapidly. As of the first half of 2025, the on - hand orders exceeded 1.5 billion yuan [29][30]. - The nuclear power business is recovering. The domestic nuclear power industry has maintained a good development momentum, and the company is an important domestic supplier in the nuclear power field. It signed a strategic cooperation agreement with Shengu Nuclear Power in the first half of 2025 and won multiple nuclear energy material projects. It also holds 60% of the equity of Jubian New Materials [34]. - The company's profitability is gradually improving. As a heavy - asset industry, with the increase in capacity utilization, the company's net profit margin, asset turnover rate, and ROE have all increased. The ROE has increased from 2% to around 10% [34]. III. Analysis of Convertible Bond Fund - Raising Projects - The company's current convertible bond raises 1.5 billion yuan. After deducting issuance fees, it will be used for the blade machining and coating project, the intelligent upgrading project of advanced nuclear energy materials and key components, and supplementing working capital and repaying bank loans [1][41]. - The blade machining and coating project is an extension of the company's existing product deep - processing processes, which can improve the service life and efficiency of high - temperature alloy components and form a complete production chain. The planned construction period is 48 months, starting from July 2022 and expected to be completed in June 2026 [41]. - The intelligent upgrading project of advanced nuclear energy materials and key components produces materials that have passed national - level industry appraisals. The project is expected to be completed in October 2026, with a construction period of 24 months starting from November 2024 [41].

Investment Rating - The report maintains a "Buy" rating for the company, indicating an expected price increase of over 15% in the next 6-12 months [5]. Core Insights - The company reported a revenue of 794.67 billion yuan for the first three quarters of 2025, a year-on-year increase of 0.41%, and a net profit attributable to shareholders of 115.35 billion yuan, up 4.0% year-on-year [2]. - In Q3 2025, the company achieved a revenue of 250.90 billion yuan, reflecting a year-on-year growth of 2.53%, with a net profit of 31.12 billion yuan, an increase of 1.43% year-on-year [2]. - The company's main business revenue in Q3 2025 reached 216.20 billion yuan, slightly outperforming the industry, which saw a decline in telecom revenue in July and August [3]. - The company has launched an "AI+" action plan, aiming to double its investment in AI by the end of 2028 and establish the largest and most advanced intelligent computing infrastructure in the country [4]. Summary by Sections Performance Review - For the first three quarters of 2025, the company achieved a revenue of 794.67 billion yuan, with a net profit of 115.35 billion yuan, showing a slight increase compared to the previous year [2]. - The Q3 revenue was 250.90 billion yuan, with a net profit of 31.12 billion yuan, indicating stable growth [2]. Operational Analysis - The company's EBITDA for the first three quarters of 2025 was 265.40 billion yuan, a year-on-year increase of 0.9%, with an EBITDA margin of approximately 33.4%, up 0.2 percentage points [3]. - The gross margin in Q3 2025 was 29.94%, down 0.88 percentage points year-on-year, primarily due to a decline in ARPU from traditional businesses and ongoing investments in emerging sectors [3]. Future Outlook - The company forecasts revenues of 1,084.54 billion yuan, 1,129.32 billion yuan, and 1,176.47 billion yuan for 2025, 2026, and 2027, respectively, with net profits projected at 145.33 billion yuan, 152.07 billion yuan, and 159.47 billion yuan [5]. - The report highlights the potential for high growth in AI and emerging businesses, despite short-term pressures on margins due to increased costs [4].

Group 1: Stock Index Futures Market Overview - The main performance of the four major index futures contracts showed a decline, with the CSI 500 index futures experiencing the largest drop of -5.32%, while the SSE 50 index futures had the smallest decline of -0.32% [3][11] - Average trading volumes for the current, next, and seasonal contracts of IC, IF, and IH increased, with IH showing the largest increase of 23.91% [3][11] - As of last Friday's close, the annualized basis rates for the current contracts of IF, IC, IM, and IH were -3.60%, -12.20%, -12.83%, and -0.90% respectively, indicating a deepening of the basis for IF and IC, while IH shifted from premium to discount [3][11] Group 2: Cross-Period Price Differences - The cross-period price difference rates for the current contracts of IF, IC, IM, and IH were at the 92.30%, 97.70%, 92.80%, and 85.30% percentiles since 2019 [4][12] - Currently, there are no arbitrage opportunities for the main IF contract and the next month contract based on the closing prices [4][12] - The estimated impact of dividends on the CSI 300, CSI 500, SSE 50, and CSI 1000 indices over the next year is projected to be 76.75, 82.44, 68.62, and 63.50 points respectively [4][12] Group 3: Recent Sell-Side Strategy Insights - Seven brokerages are optimistic about the A-share market outlook, while six believe that policy expectations and liquidity easing will support the market [5][49] - There is a consensus among brokerages regarding the AI industry chain, non-ferrous metals, deep technology, green transformation, modern services, and high-dividend assets [5][49] - Divergence exists among brokerages regarding market trends, with some expecting a stable or slow bull market while others anticipate short-term adjustments [5][52]

Investment Rating - The report maintains a "Buy" rating for the company [1] Core Views - The company's performance in Q3 2025 met expectations, with a revenue of 104.2 billion RMB, a year-on-year increase of 13% and a quarter-on-quarter increase of 11%. The net profit attributable to shareholders was 18.5 billion RMB, reflecting a year-on-year increase of 41% and a quarter-on-quarter increase of 12% [1][2] - The company is positioned as a global leader in lithium batteries, benefiting from accelerated capacity expansion and technological breakthroughs. The previous pressure on volume and price due to industry competition is gradually easing, and with the surge in demand for energy storage and commercial vehicles, along with breakthroughs in sodium batteries and solid-state technologies, the company's performance is expected to continue to exceed previous highs [3] Performance Analysis - In Q3 2025, the company shipped over 180 GWh, with actual receipts at 165 GWh, representing a year-on-year increase of 32% and a quarter-on-quarter increase of 10%. The revenue growth is attributed to the stabilization of product prices at 0.55-0.60 RMB/Wh, while costs are estimated to be between 0.40-0.45 RMB/Wh [2] - The gross margin and net profit margin for Q3 were 25.8% and 16%, respectively, remaining stable compared to the previous quarter [1][2] - The company’s inventory at the end of Q3 was 80.2 billion RMB, an 11% increase from the previous quarter, aligning with the growth in shipment volume [2] Profit Forecast and Valuation - The company is projected to achieve net profits attributable to shareholders of 70.1 billion RMB, 91.5 billion RMB, and 113.4 billion RMB for the years 2025, 2026, and 2027, respectively, corresponding to P/E ratios of 24x, 18x, and 15x [3]

Economic Growth - The cumulative growth rate for the first three quarters is 5.2%, establishing a solid foundation for achieving the annual target of 5%[3] - The minimum GDP growth requirement for the fourth quarter is set at 4.6% to meet the annual goal[3] Policy Measures - Continuous and stable policies will be maintained, with potential for monetary policy adjustments such as interest rate cuts if pressures increase[3] - Fiscal policy may involve increasing the scale of policy financial tools and utilizing government bond balances to support growth[3] GDP Performance - In Q3, GDP at constant prices grew by 4.8% year-on-year, down from 5.2%, while nominal GDP growth was 3.7%, also lower than the previous 3.9%[5] - Q3 fixed asset investment (FAI) saw a significant decline of 6.6%, while retail sales growth dropped to 3.4%[5] Economic Disparities - The gap between constant price GDP growth and nominal GDP growth indicates a disparity in economic performance, with nominal GDP growth at its lowest for 2023[8] - The GDP deflator index has shown negative growth for ten consecutive quarters, reflecting ongoing price pressures in the economy[8] Sectoral Insights - Industrial value added increased by 5.8% year-on-year in Q3, with high-tech manufacturing growing by approximately 9.6%[12] - Service sector value added rose by 5.4%, with information technology services leading at 11.2% growth[12] Investment Dynamics - Despite a decline in fixed asset investment, capital formation contributed positively to GDP growth, adding 0.9 percentage points[19] - The performance of intangible asset investments, particularly in software, has been relatively strong, benefiting from advancements in artificial intelligence[19] Future Outlook - Economic growth may slow in Q4 due to high base effects, particularly in consumer goods, with automotive retail showing negative growth[21] - Policy efforts will focus on boosting service consumption and fixed asset investment, with an estimated 2.2 percentage point support from new fiscal measures[21] Risk Factors - Risks include US-China trade tensions, tariff increases, and global supply chain adjustments, which may impact exports and corporate profits[4] - Ongoing geopolitical changes and international market fluctuations could affect commodity prices and related industries[4]

Investment Rating - The report maintains a "Buy" rating for the company, expecting significant growth in the upcoming years [4]. Core Insights - The company reported a revenue of 6.08 billion RMB for Q3 2025, representing a year-on-year growth of 10.0%. The gross profit was 2.45 billion RMB, up by 8.6%, while the net profit attributable to shareholders reached 140 million RMB, showing a remarkable increase of 202.4% [2]. - The cash flow from operating activities for Q3 2025 was 900 million RMB, reflecting a year-on-year growth of 25.2%, indicating strong operational efficiency [2]. - The revenue structure indicates that the C-end business accounted for 32% of total revenue, with a year-on-year growth of 38%, suggesting it remains the primary growth driver [3]. - The company is in the process of raising 4 billion RMB through a private placement, with 800 million RMB allocated for AI education products, which is expected to further boost revenue in the education sector [3]. Summary by Sections Performance Review - Q3 2025 revenue was 6.08 billion RMB, up 10.0% year-on-year - Gross profit was 2.45 billion RMB, an increase of 8.6% - Net profit attributable to shareholders was 140 million RMB, a growth of 202.4% [2] Operational Analysis - C-end, B-end, and G-end revenue contributions were 32%, 42%, and 26% respectively - C-end business grew by 38% year-on-year, driving overall revenue growth - Total operating cash flow was 900 million RMB, up 25.2% year-on-year [3] Profit Forecast and Valuation - Projected revenues for 2025, 2026, and 2027 are 27.08 billion RMB, 30.65 billion RMB, and 34.3 billion RMB respectively, with growth rates of 16.0%, 13.2%, and 11.9% - Expected net profits for the same years are 950 million RMB, 1.16 billion RMB, and 1.3 billion RMB, with growth rates of 69.7%, 21.8%, and 11.8% respectively [4]

Report Summary 1. Investment Rating There is no information about the industry investment rating in the report. 2. Core View Last week (10/13 - 10/17), bond - type ETFs had a net capital outflow of 13.36 billion yuan. Convertible bond ETFs had a large drawdown, while the net values of credit bond and interest - rate bond ETFs showed marginal recovery. There was no new issuance of bond ETFs. The market values of interest - rate, credit, and convertible bond ETFs all decreased compared to the previous week. The average trading price of credit bond ETFs was lower than the fund's unit net value, indicating low allocation sentiment. The weekly turnover rates of all three types of products increased significantly [2][13][17]. 3. Section Summaries 3.1 Issuance Progress Tracking - No new bond ETFs were issued last week [17]. 3.2 Stock Product Tracking - As of October 17, 2025, the circulating market values of interest - rate bond ETFs, credit bond ETFs, and convertible bond ETFs were 134.1 billion yuan, 368.2 billion yuan, and 66 billion yuan respectively, with credit bond ETFs accounting for 64.8% of the total. Haifutong China Short - term Financing ETF and Bosera Convertible Bond ETF had the top two circulating market values [19]. - Compared to the previous week, the circulating market values of interest - rate bond ETFs, credit bond ETFs, and convertible bond ETFs decreased by 3.76 billion yuan, 3.41 billion yuan, and 2.16 billion yuan respectively. Products with a market value reduction of over 1.5 billion yuan last week included Haifutong China Short - term Financing ETF, Bosera Convertible Bond ETF, etc. [21]. - Among credit bond ETFs, the circulating market values of benchmark - making credit bond ETFs and science - innovation bond ETFs were 122 billion yuan and 246.5 billion yuan respectively, decreasing by 450 million yuan and 5.18 billion yuan compared to the previous week [24]. 3.3 ETF Performance Tracking - Recently, the market has been oscillating within a range. In the past two weeks, the cumulative unit net values of interest - rate bond ETFs and credit bond ETFs closed at 1.18 and 1.02 respectively [27]. - As of October 17, based on February 7 as the base date, the average cumulative return of benchmark - making credit bond ETFs rose to 0.42%. Based on July 17 as the base date, the cumulative return of science - innovation bond ETFs marginally recovered to - 0.30% but still remained in the negative range [32]. 3.4 Premium/Discount Rate Tracking - Last week, the average premium/discount rates of credit bond ETFs, interest - rate bond ETFs, and convertible bond ETFs were - 0.15%, + 0.001%, and + 0.04% respectively. The average trading price of credit bond ETFs was lower than the fund's unit net value, indicating low allocation sentiment. Specifically, the average weekly premium/discount rates of benchmark - making credit bond ETFs and science - innovation bond ETFs were - 0.21% and - 0.15% respectively [37]. 3.5 Turnover Rate Tracking - Last week, the turnover rate of interest - rate bond ETFs > credit bond ETFs > convertible bond ETFs. The weekly turnover rates of all three types of products increased significantly, rising to 187%, 143%, and 109% respectively. Specifically, interest - rate bond ETFs such as Haifutong Shanghai 5 - year Local Government Bond ETF and Huaxia Shanghai Benchmark - making Treasury Bond ETF had relatively high turnover rates [42].

Investment Rating - The report initiates coverage with a "Buy" rating for the company, setting a target price of 27.9 RMB based on a 90x PE for 2026 [4]. Core Insights - The company is one of the few integrated manufacturers of semiconductor silicon epitaxial wafers in China, capable of the entire production process from crystal growth to substrate formation and epitaxial growth. In H1 2025, the company achieved revenue of 625 million RMB, a year-on-year increase of 15%, and a net profit attributable to shareholders of 59.71 million RMB, up 24% year-on-year, indicating a recovery in revenue and profit growth [2][20]. - The global semiconductor market is showing signs of recovery, with a market size of 346 billion USD in H1 2025, reflecting a year-on-year growth of 19%. The WSTS has revised its forecast for the entire year of 2025 to 728 billion USD, expecting a 15% year-on-year increase, which is 4 percentage points higher than previous expectations [2][39]. - The company focuses on power devices and analog chips, benefiting from the recovery in end-user demand in automotive electronics and industrial sectors. The global discrete device market is expected to reach 46.1 billion USD by 2028, with a CAGR of 8.5% from 2024 to 2028 [2][39]. Summary by Sections 1. Integrated Semiconductor Silicon Epitaxial Wafer Supplier - The company has established itself as a key supplier in the semiconductor industry, providing high-quality silicon epitaxial wafers used in various applications, including power devices and analog chips [14][18]. - The company's revenue and performance have been influenced by the cyclical nature of the semiconductor industry, with a notable recovery in H1 2025 [20][24]. 2. Demand Driven by Power Devices and Analog Chips - The semiconductor materials market is experiencing a mild recovery, with the global semiconductor materials market expected to reach 76 billion USD in 2025, growing by 8.4% year-on-year [30]. - The company has a strong overseas presence, with 86% of its revenue coming from international markets, indicating a robust global sales network [25][30]. 3. Strategic Focus on 8-inch and 12-inch Wafer Production - The company is expanding its production capacity, particularly in 12-inch wafers, to meet the growing demand driven by AI and HPC sectors. The IPO in 2024 raised 1.4 billion RMB to fund these initiatives [3][4]. - The company aims to enhance its product structure by focusing on advanced process logic chips and automotive-grade products, which are expected to improve its competitive position [2][3]. 4. Profit Forecast and Investment Recommendations - The company is projected to achieve revenues of 1.31 billion RMB, 1.62 billion RMB, and 1.97 billion RMB in 2025, 2026, and 2027, respectively, with corresponding net profits of 160 million RMB, 204 million RMB, and 260 million RMB, indicating strong growth potential [4][8]. - The report highlights the company's advantageous customer structure, which is expected to contribute to margin improvements as the 12-inch epitaxial wafer capacity comes online [4][8].

Quantitative Models and Construction Methods - **Model Name**: Dynamic Macro Event Factor-based CSI Hong Kong Stock Connect Consumer Index Timing Strategy **Model Construction Idea**: The model explores the impact of China's macroeconomic factors on the overall performance and trends of Hong Kong-listed consumer companies, using dynamic macro event factors to construct a timing strategy framework [2][3][20] **Model Construction Process**: 1. **Macro Data Selection**: Select 20+ macroeconomic indicators across four dimensions: economy, inflation, currency, and credit, such as PMI, PPI, M1, etc [21][23] 2. **Data Preprocessing**: - Align data frequency to monthly frequency by either taking the last trading day of the month or calculating the monthly average for daily data - Fill missing values using the median of the first-order difference of the past 12 months added to the previous value $ X_{t}=X_{t-1}+Median_{diff12} $ [27] - Apply filtering using one-sided HP filter to avoid future data leakage $ \hat{t}_{t|t,\lambda}=\sum\nolimits_{s=1}^{t}\omega_{t|t,s,\lambda}\cdot y_{s}=W_{t|t,\lambda}(L)\cdot y_{t} $ [28] - Derive factors using transformations such as year-on-year, month-on-month, and moving averages [29] 3. **Macro Event Factor Construction**: - Determine event breakthrough direction by calculating the correlation between data and next-period asset returns - Identify leading or lagging relationships by deriving lagged event factors (0-4 periods) and selecting the most suitable lag period - Generate event factors using three types: data breaking through moving average, data breaking through median, and data moving in the same direction, with different parameters (e.g., moving average length: 2-12, rolling window: 2-12, same direction period: 1-5) [30][32] 4. **Event Factor Evaluation and Screening**: - Use two metrics: win rate of returns and volatility-adjusted returns during opening positions - Initial screening criteria: t-test significance at 95% confidence level, win rate >55%, occurrence frequency > rolling window period/6 [31][32] 5. **Combining Event Factors**: Select the highest win rate event factor as the base factor, then combine it with the second-highest win rate factor with a correlation <0.85. If the combined factor improves the win rate, it is selected; otherwise, the base factor is used [33] 6. **Dynamic Exclusion**: If no event factor passes the screening, the macro indicator is marked as empty for the period and excluded from scoring [33] 7. **Optimal Rolling Window Determination**: Test rolling windows of 48, 60, 72, 84, and 96 months to find the most suitable parameter for each macro indicator based on volatility-adjusted returns during opening positions [33] 8. **Final Macro Indicators**: Five macro factors were selected based on their performance in the sample period: - PMI: Raw Material Prices (96-month rolling window) - US-China 10Y Bond Spread (72-month rolling window) - Financial Institutions: Medium-Long Term Loan Balance: Monthly New Additions: Rolling 12M Sum: YoY (48-month rolling window) - M1: YoY (48-month rolling window) - New Social Financing: Rolling 12M Sum: YoY (96-month rolling window) [34][35] 9. **Timing Strategy Construction**: - If >2/3 of factors signal bullishness, the category factor signal is marked as 1 - If <1/3 of factors signal bullishness, the category factor signal is marked as 0 - If the proportion of bullish signals falls between these ranges, the category factor is marked with the specific proportion - The score of each category factor is used as the timing position signal for the period [3][35] **Model Evaluation**: The strategy effectively captures systematic opportunities and avoids systematic risks, demonstrating superior performance compared to the benchmark in terms of annualized returns, maximum drawdown, Sharpe ratio, and return-drawdown ratio [2][3][20] --- Model Backtesting Results - **Dynamic Macro Event Factor-based CSI Hong Kong Stock Connect Consumer Index Timing Strategy** - **Annualized Return**: 10.44% - **Annualized Volatility**: 18.47% - **Maximum Drawdown**: -29.72% - **Sharpe Ratio**: 0.59 - **Return-Drawdown Ratio**: 0.35 [2][11][22] --- Quantitative Factors and Construction Methods - **Factor Name**: PMI: Raw Material Prices **Factor Construction Idea**: Use raw data to capture macroeconomic trends affecting asset returns [35] **Factor Construction Process**: Utilize raw data with a 96-month rolling window [35] - **Factor Name**: US-China 10Y Bond Spread **Factor Construction Idea**: Reflect the impact of interest rate differentials on asset returns [35] **Factor Construction Process**: Utilize raw data with a 72-month rolling window [35] - **Factor Name**: Financial Institutions: Medium-Long Term Loan Balance: Monthly New Additions: Rolling 12M Sum: YoY **Factor Construction Idea**: Measure credit expansion and its influence on asset returns [35] **Factor Construction Process**: Utilize raw data with a 48-month rolling window [35] - **Factor Name**: M1: YoY **Factor Construction Idea**: Capture monetary supply changes and their impact on asset returns [35] **Factor Construction Process**: Utilize raw data with a 48-month rolling window [35] - **Factor Name**: New Social Financing: Rolling 12M Sum: YoY **Factor Construction Idea**: Reflect credit growth and its effect on asset returns [35] **Factor Construction Process**: Utilize raw data with a 96-month rolling window [35] **Factor Evaluation**: The selected factors demonstrated strong performance in the sample period, with high win rates and volatility-adjusted returns during opening positions [34][35] --- Factor Backtesting Results - **PMI: Raw Material Prices** - **Rolling Window**: 96 months [35] - **US-China 10Y Bond Spread** - **Rolling Window**: 72 months [35] - **Financial Institutions: Medium-Long Term Loan Balance: Monthly New Additions: Rolling 12M Sum: YoY** - **Rolling Window**: 48 months [35] - **M1: YoY** - **Rolling Window**: 48 months [35] - **New Social Financing: Rolling 12M Sum: YoY** - **Rolling Window**: 96 months [35]

- The report tracks high-frequency stock selection factors, including price range factor, price-volume divergence factor, regret avoidance factor, and slope convexity factor, with their out-of-sample performance being generally strong[2][3][11] - **Price Range Factor**: Measures the activity of stock transactions within different intraday price ranges, reflecting investors' expectations of future stock trends. High price range transaction volume and transaction count factors are negatively correlated with future stock returns, while low price range average transaction volume factor is positively correlated with future stock returns. The factor is constructed by combining three sub-factors: high price 80% range transaction volume factor (VH80TAW), high price 80% range transaction count factor (MIH80TAW), and low price 10% range average transaction volume factor (VPML10TAW). These sub-factors are weighted at 25%, 25%, and 50%, respectively, and are industry market value neutralized[12][14][17] - **Price-Volume Divergence Factor**: Measures the correlation between stock price and trading volume. When price and volume diverge, the likelihood of future price increases is higher, while convergence indicates a higher likelihood of price decreases. The factor is constructed using high-frequency snapshot data to calculate the correlation between snapshot transaction price and snapshot trading volume, as well as snapshot transaction price and transaction count. Two sub-factors are used: price and transaction count correlation factor (CorrPM) and price and trading volume correlation factor (CorrPV). These sub-factors are equally weighted and industry market value neutralized[22][23][25] - **Regret Avoidance Factor**: Based on behavioral finance theory, this factor utilizes investors' regret avoidance emotions to construct effective stock selection factors. It examines the proportion and degree of stock price rebound after being sold by investors. The factor is constructed using transaction data to identify active buy/sell directions, with additional restrictions on small orders and closing trades to enhance performance. Two sub-factors are used: sell rebound proportion factor (LCVOLESW) and sell rebound deviation factor (LCPESW). These sub-factors are equally weighted and industry market value neutralized[26][32][35] - **Slope Convexity Factor**: Derived from the elasticity of supply and demand, this factor uses high-frequency snapshot data from limit order books to calculate the slope and convexity of buy and sell orders. The factor is constructed by aggregating order volume data by level and calculating the slope of buy and sell order books. Two sub-factors are used: low-level slope factor (Slope_abl) and high-level seller convexity factor (Slope_alh). These sub-factors are equally weighted and industry market value neutralized[36][41][43] - **High-frequency "Gold" Portfolio Strategy**: Combines the three high-frequency factors (price range, price-volume divergence, and regret avoidance) with equal weights to construct an enhanced strategy for the CSI 1000 Index. The strategy includes mechanisms to reduce transaction costs, such as weekly rebalancing and turnover rate buffering. The strategy's annualized excess return is 10.20%, with an IR of 2.38 and maximum excess drawdown of 6.04%[44][46][47] - **High-frequency & Fundamental Resonance Portfolio Strategy**: Combines high-frequency factors with fundamental factors (consensus expectations, growth, and technical factors) to construct an enhanced strategy for the CSI 1000 Index. The strategy's annualized excess return is 14.49%, with an IR of 3.46 and maximum excess drawdown of 4.52%[48][50][52]