Report Summary 1. Core Viewpoint Among AA-rated urban investment bonds with the highest discount rates, "25 Gaomi 01" had the largest deviation in valuation price; among the top 50 bonds with the largest net price declines, "24 SDIC MTN002" had the largest deviation; among the top 50 bonds with the largest net price increases, "23 Vanke MTN002" had the largest deviation; among the top 50 Tier 2 and perpetual bonds with the largest net price increases, "25 ABC Tier 2 Capital Bond 01B(BC)" had the largest deviation [2]. 2. Summary by Directory Discount - Leading AA Urban Investment Bonds (Subject Rating) - The report listed 40 AA-rated urban investment bonds with high discount rates, including "25 Gaomi 01" with a 4.27-year remaining term, a valuation price deviation of -0.28%, a valuation net price of 105.07 yuan, and a valuation yield of 3.93% [4]. Top 50 Bonds with the Largest Net Price Declines - The report presented 50 bonds with significant net price drops, such as "24 SDIC MTN002" with a 28.76-year remaining term, a valuation price deviation of -0.40%, a valuation net price of 98.10 yuan, and a valuation yield of 2.58% [6]. Top 50 Bonds with the Largest Net Price Increases - It included 50 bonds experiencing substantial net price increases. For example, "23 Vanke MTN002" had a 0.42-year remaining term, a valuation price deviation of 2.30%, a valuation net price of 16.85 yuan, and a valuation yield of 1067.74% [9]. Top 50 Tier 2 and Perpetual Bonds with the Largest Net Price Increases - The report listed 50 Tier 2 and perpetual bonds with large net price increases, like "25 ABC Tier 2 Capital Bond 01B(BC)" with a 9.53-year remaining term, a valuation price deviation of 0.29%, a valuation net price of 96.65 yuan, and a valuation yield of 2.50% [13].

Report Summary 1. Industry Investment Rating No industry investment rating is provided in the report. 2. Core Viewpoints - In November, the new social financing scale was not low, mainly driven by corporate credit and off - balance - sheet financing. However, the credit structure remained poor, with bill financing reaching a record high for the same period, corporate medium - and long - term loans at the lowest level since 2016 for the same period, and both short - term and medium - and long - term household loans at record lows for the same period. The credit demand of the real sector was significantly weak. Looking ahead, the net financing scale of government bonds in December may decline slightly month - on - month, still dragging down social financing. The intensive implementation of 500 billion yuan of policy - based financial instrument support projects from October to December may boost social financing to some extent, but the weak credit demand and the banks' desire to reserve projects for January next year may cause significant disturbances to social financing [6][33]. 3. Summary by Content Social Financing Aggregate - In November, the stock growth rate of social financing remained flat at 8.5%. The new social financing in November was 2.49 trillion yuan, an increase of 159.7 billion yuan year - on - year. Compared with the average of 2.3 trillion yuan in the same period of the past five years, the new social financing scale in November this year was not much different from the historical average, falling at the upper edge of the new scale in the same period of the past five years [2][8]. Factors Contributing to the Increase in Social Financing - Off - balance - sheet financing was one of the main contributors to the year - on - year increase in social financing this month. In November, trust loans and undiscounted bank acceptance bills in the off - balance - sheet financing items both increased year - on - year, supporting social financing. The new trust loan scale in November has generally declined compared with October since 2020, but this month's trend was anti - seasonal, possibly related to the recently launched new policy - based financial instrument support projects. In addition, corporate bonds were another supporting item for the increase in social financing this month. In November, new corporate bonds increased by 178.8 billion yuan to 416.9 billion yuan, the highest level in the same period since 2020, and were the only item with an increase in direct financing projects [3][15][18]. Credit Structure - There was a divergence between the total social financing and the credit structure. Although the overall performance of social financing in November was not bad, credit was still weak. Corporate sector credit increased by 360 billion yuan year - on - year to 610 billion yuan, mainly driven by short - term corporate loans and bill financing, while medium - and long - term corporate loans decreased year - on - year. Household sector credit had a negative growth for the first time in the same period in history [4][20]. - New medium - and long - term corporate loans were at the lowest level in the same period since 2016. The reasons for the year - on - year increase in corporate sector credit this year were the low base of corporate sector credit in November 2024 and the simultaneous efforts of short - term corporate loans and bill financing in November this year, which pushed up the corporate credit scale this month. In November, short - term corporate loans increased by 110 billion yuan year - on - year to 100 billion yuan, higher than the average of 50.2 billion yuan in the same period of the past five years. The new short - term corporate loan scale this year has always been at the upper edge of the historical same period, possibly because although the economy was sluggish, enterprises still needed a certain amount of funds for business turnover, and banks may also have vigorously issued short - term corporate loans at the end of the quarter to boost the scale. The new bill financing scale in November was at a record high for the same period, indicating that corporate credit issuance was still weak, and bill financing was used to increase the total credit scale. Medium - and long - term corporate loans decreased by 40 billion yuan year - on - year to 170 billion yuan, the lowest level in the same period since 2016, and the growth rate of the balance of medium - and long - term corporate loans further declined by 0.05 percentage points to 7.8%, having declined for 28 consecutive months [4][20][21]. - Household sector credit had a negative growth for the first time in the same period in history. In November, household sector credit decreased by 476.3 billion yuan year - on - year to - 206.3 billion yuan. Among them, short - term household loans decreased by 178.8 billion yuan year - on - year to - 215.8 billion yuan, also setting a record low for the same period. Contrary to short - term corporate loans, short - term household loans have basically been at the lower edge of the historical same period this year, and have even set record lows for the same period many times, possibly indicating weak household consumption willingness against the background of unstable income expectations. Medium - and long - term household loans decreased by 290 billion yuan year - on - year to 1 billion yuan, also the lowest value for the same period. The year - on - year growth rate of the sales area of commercial housing in 30 large and medium - sized cities in November declined to - 30.91%, the lowest level since May 2024, while the growth rate of the commercial housing sales area in the same period last year was 11.6%, indicating that current household home - buying willingness was also weak [5][24]. M1 and M2 - The growth rate of M1 continued to decline by 1.3 percentage points. In November this year, the monthly incremental scale of M1 was 0.89 trillion yuan, while the incremental scale of M1 in November last year was 2.15 trillion yuan. As the impact of the ban on manual interest compensation had gradually dissipated and the low - base effect faded, the growth rate of M1 continued to decline by 1.3 percentage points to 4.9% in November [6][25]. - Fiscal expenditure had limited support for M2. In terms of deposits, both household and corporate deposits decreased year - on - year in November, indicating that deposit creation was also not ideal against the background of sluggish loans. At the same time, non - bank deposits decreased by 100 billion yuan year - on - year to 80 billion yuan, and the new scale was significantly lower than that in the same period since 2022. Historically, the growth rate of the non - bank deposit balance had a certain similarity with the trend of the Shanghai Composite Index. The stock market had a slight correction in November, which may have led to a low new non - bank deposit scale in November. In summary, the growth rate of M2 further declined by 0.2 percentage points to 8% in November. In addition, fiscal deposits decreased by 190 billion yuan year - on - year to - 50 billion yuan. The fiscal expenditure intensity was generally weaker than that from 2021 to 2023 and stronger than that in 2024, but its support for the M2 growth rate was limited [6][30].

基本内容 中央经济工作会议通稿在总基调和核心内容上与本周初的政治局会议基本一致，但篇幅更长、增量信息更多；同时， 对比去年和今年的会议通稿，我们又可以看到诸多变化。 风险提示 1）经济目标、赤字率、特别国债、专项债等数字安排需要到明年两会期间发布，当前评估尚存在不确定性；2）外部 环境仍然复杂多变，可能给国内经济工作重心和政策节奏带来扰动。 敬请参阅最后一页特别声明 1 扫码获取更多服务 中央经济工作会议通稿在总基调和核心内容上与本周初的政治局会议基本一致，但篇幅更长、增量信息更多；同时， 对比去年和今年的会议通稿，我们又可以看到诸多变化。 对形势评估更有信心。相比于往年，今年会议对于外部环境使用了"影响加深"这一相对中性的表述，去年会议则描 述为"不利影响加深"。今年对于内部问题指出"大多是发展中、转型中的问题，经过努力是可以解决的"，这一变化 呼应了今年中国在外交、经济、市场等方面的表现，也对应了防风险工作的顺位从去年的第五位降到今年的第八位。 财政政策更有定力。会议对财政政策"更加积极"的定调与去年一致，但细节更显定力。例如，指出"保持必要的" 财政赤字、债务规模和支出总量，去年则直接提出要"提高财政赤 ...

Investment Rating - The report maintains a "Buy" rating for the company, expecting a price increase of over 15% in the next 6-12 months [5]. Core Views - The company demonstrates confidence in its future development by repurchasing 8.14 million shares at an average price of 12.26 HKD, totaling 99.77 million HKD [2]. - The Hilo product line is gaining traction, with strong promotional efforts from British American Tobacco (BAT) leading to a 50% retention rate among traditional and heated tobacco consumers, which supports future sales growth [3]. - The core vaping business is recovering, benefiting from regulatory crackdowns on illegal e-cigarettes in the U.S. and a shift in European markets towards compliant products. BAT expects revenue recovery in the U.S. market by the second half of 2025, with a projected market share increase [4]. - The company is well-positioned to capitalize on the expanding compliant vaping market in Europe and the U.S., with a focus on accelerating the global promotion of Hilo products by 2026 [4]. Financial Summary - The company’s projected earnings per share (EPS) for 2025-2027 are 0.22, 0.37, and 0.59 CNY, respectively, with corresponding price-to-earnings (P/E) ratios of 53, 31, and 20 [5]. - Revenue is expected to grow from 11,168 million CNY in 2023 to 20,462 million CNY by 2027, reflecting a compound annual growth rate (CAGR) of approximately 20.48% [10]. - The net profit is projected to recover from 1,303 million CNY in 2024 to 3,656 million CNY by 2027, indicating a significant growth trajectory [10].

Report Summary 1. Industry Investment Rating No industry investment rating is provided in the given content. 2. Core Viewpoints - The report tracks the supply and trading of local government bonds, including the primary supply rhythm and secondary trading characteristics [9][20]. 3. Summary by Directory I. Local Government Bond Supply and Trading Tracking 1. Primary Supply Rhythm - From December 1st to 5th, 2025, local government bonds issued a total of 108.7 billion yuan, including 39 billion yuan in new special bonds and 17 billion yuan in refinancing special bonds [9]. - "Ordinary/Project Revenue" and "Repayment of Existing Debts" are the main investment areas for special bond funds [9]. - As of December 5th, 2025, 1.1 billion yuan of special refinancing special bonds have been issued in December, accounting for 30.5% of the monthly local bond issuance scale [9]. - The average issuance interest rate of local bonds has increased marginally. The spreads between the issuance interest rates of 30 - year, 20 - year, and 10 - year local bonds and the same - term treasury bonds have widened to 23.6BP, 24.5BP, and 19.2BP respectively [16]. - In December, Tianjin, Shandong, Shaanxi and other provinces are the main regions for local bond issuance. The issuance scale of local bonds within 7 years in Tianjin reached 19.05 billion yuan, and the average coupon rate of local government bonds in Henan is close to 2.5% [19]. 2. Secondary Trading Characteristics - Last week, the 7 - 10 - year and over - 10 - year local bond indices fell 0.27% and 0.69% respectively month - on - month, with the decline similar to that of the same - term credit bonds [20]. - The trading activity of Henan government bonds increased, with a week - on - week increase of 123 transactions, while the trading volume of Jiangxi local bonds decreased significantly [20]. - The average trading terms of Liaoning and Jilin government bonds have been significantly extended, reaching 24.0 years and 24.2 years respectively, an increase of 11.0 years and 12.2 years compared to last week. The average trading yields of Henan, Hebei, and Guangdong government bonds rose to around 2.4% [22].

Investment Rating - The report assigns a "Buy" rating to the company with a target price of HKD 109.78, based on a PE valuation of 30 times for 2025 [4]. Core Insights - The company is a leading player in China's beauty and personal care industry, with a multi-brand matrix covering skincare, baby care, and hair care segments. The main brand, Han Shu, has rapidly expanded its presence on platforms like Douyin, achieving significant revenue growth [2][3]. - The company is expected to achieve revenue of CNY 67.93 billion in 2024, representing a year-on-year growth of 62.1%, with a net profit of CNY 7.81 billion, up 69.4% [14]. - The growth strategy is supported by a strong brand operation methodology, focusing on market-driven brand positioning, precise consumer targeting, and innovative marketing strategies [3][39]. Summary by Relevant Sections Company Highlights - The company has a multi-brand strategy with a focus on online sales, achieving nearly 93% online sales in the first half of 2025. The main brand, Han Shu, is projected to generate revenue of CNY 55.91 billion in 2024, a growth of 80.90% year-on-year [2]. - New brands like Yi Ye are experiencing rapid growth, with projected annual growth rates of 498% for 2023/2024 and 146% for the first half of 2025 [2]. Investment Logic - The company is expected to see significant growth in its three main segments: skincare, baby care, and hair care. Han Shu is projected to exceed CNY 10 billion in revenue within three years, while Yi Ye is expected to maintain a compound annual growth rate of over 50% [3]. - The baby care brand Yi Ye is leveraging a unique "medical research co-creation" model, while the hair care segment is expected to produce major brands through clear positioning and effective marketing strategies [3]. Profit Forecast, Valuation, and Rating - The forecasted EPS for 2025, 2026, and 2027 is CNY 2.68, CNY 3.33, and CNY 4.09 respectively, with a projected valuation of 24 times for 2026. The strong growth potential of the multi-brand strategy supports the "Buy" rating [4]. - The company is expected to achieve a return on equity (ROE) of 41.92% in 2025, indicating strong profitability [8].

Report Summary 1. Industry Investment Rating No information about the industry investment rating is provided in the report. 2. Core Viewpoints - Among the bonds with discounted transactions, "25 Yungang Y4" had a large deviation in the valuation price. Among the bonds with rising net prices, "25 Datong C3" had a relatively high deviation in the valuation price. Among the Tier 2 and perpetual bonds with rising net prices, "22 Bank of Communications Tier 2 Capital Bond 02B" had a large deviation in the valuation price; among the commercial financial bonds with rising net prices, "25 Agricultural Bank of China TLAC Non - capital Bond 02C(BC)" had a relatively high deviation in the valuation price. Among the bonds with a transaction yield higher than 5%, real - estate bonds ranked high [2]. - The changes in the valuation yield of credit bonds were mainly distributed in the [-5,0) interval. The transaction terms of non - financial credit bonds were mainly distributed between 2 and 3 years, with the highest proportion of discounted transactions for varieties within 0.5 years. The transaction terms of Tier 2 and perpetual bonds were mainly distributed between 4 and 5 years, with the highest proportion of discounted transactions for varieties within 1 year. In terms of industries, bonds in the national defense and military industry had the largest average deviation in valuation prices [2]. 3. Summary by Relevant Charts Chart 1: Discounted Transaction Tracking - The table listed 30 bonds with large discounts, including "25 Yungang Y4", "25 Dongfang K1", etc., with information on the remaining term, valuation price deviation, valuation net price, valuation yield deviation, and transaction scale. The industries involved included transportation, non - financial finance, and urban investment [4]. Chart 2: Tracking of Bonds with Rising Net Prices - The table showed 43 bonds with large positive deviations, such as "25 Datong C3", "25 Raofa 02", etc. It provided details on the remaining term, valuation price deviation, valuation net price, valuation yield deviation, and transaction scale. The industries included non - financial finance, comprehensive, and public utilities [6]. Chart 3: Tracking of Tier 2 and Perpetual Bond Transactions - The table presented 40 Tier 2 and perpetual bonds, including "22 Bank of Communications Tier 2 Capital Bond 02B", "22 Industrial and Commercial Bank of China Tier 2 Capital Bond 04B", etc., with information on the remaining term, valuation price deviation, valuation net price, valuation yield deviation, bank classification, and transaction scale [7]. Chart 4: Tracking of Commercial Financial Bond Transactions - The table listed 29 commercial financial bonds, such as "25 Agricultural Bank of China TLAC Non - capital Bond 02C(BC)", "24 Agricultural Bank of China TLAC Non - capital Bond 01B(BC)", etc., providing details on the remaining term, valuation price deviation, valuation net price, valuation yield deviation, bank classification, and transaction scale [8]. Chart 5: Bonds with a Transaction Yield Higher than 5% - The table showed 20 bonds with a high - yield transaction, including "21 Vanke 06", "23 Vanke 01", etc., with information on the remaining term, valuation price deviation, valuation net price, valuation yield deviation, and transaction scale. The industries involved included real estate, steel, and non - financial finance [10]. Chart 6: Distribution of Valuation Deviations in Credit Bond Transactions on the Day - The chart showed the distribution of changes in the valuation yield of credit bonds on the day, with the intervals [-10,-5), [-5,0), (0,5], and (5,10], and the number of bonds and transaction scale in each interval [13]. Chart 7: Distribution of Transaction Terms of Non - financial Credit Bonds on the Day - The chart presented the distribution of transaction terms of non - financial credit bonds on the day, including intervals such as within 0.5 years, 0.5 - 1 year, etc., and the corresponding transaction scale [15]. Chart 8: Distribution of Transaction Terms of Tier 2 and Perpetual Bonds on the Day - The chart showed the distribution of transaction terms of Tier 2 and perpetual bonds on the day, including intervals such as within 1 year, 1 - 1.5 years, etc., and the corresponding transaction scale [18]. Chart 9: Discounted Transaction Ratio and Transaction Scale of Non - financial Credit Bonds in Each Industry - The chart displayed the average valuation price deviation and transaction scale of non - financial credit bonds in various industries, including petroleum and petrochemicals, real estate, etc. The national defense and military industry had the largest average valuation price deviation [20].

Report Industry Investment Rating No information provided. Core Viewpoints - Economic growth shows cost reduction and widespread decline in steel prices, with production - related indicators such as power plant daily consumption, blast furnace operation rate, tire operation rate, and loom operation rate showing different trends; demand - side data for real estate, automobiles, steel, cement, glass, and shipping also vary [1][4]. - Inflation is characterized by the agricultural product price index being higher than in recent years, with different price trends for various agricultural products; PPI shows weak oil prices, and different trends for copper and aluminum prices [2][4]. Summary by Directory 1. Economic Growth: Cost Reduction and Widespread Decline in Steel Prices 1.1 Production: Seasonal Increase in Power Plant Daily Consumption - **1.1.1 Production End: Seasonal Increase in Power Plant Daily Consumption** - On December 9, the average daily consumption of 6 major power - generation groups was 79.7 tons, a 2.3% increase from December 2; on December 2, the daily consumption of power plants in eight southern provinces was 190.8 tons, a 3.9% increase from November 25. Heating demand in the north boosts power consumption, but demand in non - power industries has limited growth [4][12]. - **1.1.2 Production End: Overall Decline in Blast Furnace Operation Rate** - On December 5, the national blast furnace operation rate was 80.1%, a 0.9 - percentage - point decrease from November 28; the capacity utilization rate was 87.1%, also a 0.9 - percentage - point decrease. However, the blast furnace operation rate of Tangshan steel mills increased by 2.4 percentage points. Heavy - pollution response measures and weakening demand in the off - season led to the decline [4][17]. - **1.1.3 Production End: Slight Recovery in Tire Operation Rate** - On December 4, the operation rate of all - steel truck tires was 63.5%, a 0.2 - percentage - point increase from November 27; the operation rate of semi - steel car tires was 70.9%, a 1.7 - percentage - point increase. The loom operation rate in the Jiangsu - Zhejiang region continued to decline [4][20]. 1.2 Demand: Cost Reduction and Widespread Decline in Steel Prices - **1.2.1 Demand End: Improved Monthly - on - Monthly New Home Sales in 30 Cities** - From December 1 - 9, the average daily sales area of commercial housing in 30 large - and medium - sized cities was 256,000 square meters, a 42.0% increase from November, but a decline compared to the same period in previous years. Sales in first - tier, second - tier, and third - tier cities all decreased year - on - year [4][25]. - **1.2.2 Demand End: Weak Growth in Automobile Retail Sales** - In December, retail sales decreased by 32% year - on - year, and wholesale sales decreased by 40% year - on - year. The low growth was due to high sales in December last year and the weakening impact of the trade - in policy [4][29]. - **1.2.3 Demand End: Widespread Decline in Steel Prices** - On December 9, the prices of rebar, wire rod, hot - rolled coil, and cold - rolled coil decreased by 2.4%, 2.1%, 2.7%, and 0.5% respectively compared to December 2. Steel inventory reduction accelerated [4][34]. - **1.2.4 Demand End: Moderate Increase in Cement Prices** - On December 9, the national cement price index increased by 0.4% compared to December 2, with prices in the East China and Yangtze River regions performing better. However, price increases were difficult to implement due to high inventory in some areas. The year - on - year decline in cement prices narrowed [4][35]. - **1.2.5 Demand End: Glass Prices Reached a New Low in the Second Half of the Year** - On December 9, the active glass futures contract price was 985 yuan/ton, a 5.2% decrease from December 2. Weak demand and high inventory were the main reasons [4][40]. - **1.2.6 Demand End: Container Shipping Freight Index Turned Down Again** - On December 5, the CCFI index decreased by 0.6% and the SCFI index decreased by 0.4% compared to November 28. Weak market demand and expanding container ship capacity dragged down freight rates [4][44]. 2. Inflation: Agricultural Product Price Index Higher than in Recent Years 2.1 CPI: Agricultural Product Price Index Higher than in Recent Years - **2.1.1 Pork Prices Rose and Then Fell** - On December 9, the average wholesale price of pork was 17.6 yuan/kg, a 0.1% decrease from December 2. The pressure came from the concentrated slaughter at the end of the year. The month - on - month decline widened [4][49]. - **2.1.2 Agricultural Product Price Index Higher than in Recent Years** - On December 9, the agricultural product wholesale price index increased by 1.1% compared to December 2. Different agricultural products had different price trends. The year - on - year and month - on - month increases in the agricultural product price index were 6.0% and 2.4% respectively [4][55]. 2.2 PPI: Weak Oil Prices - **2.2.1 Oil Prices Weakened** - On December 9, the spot prices of Brent and WTI crude oil were $62.8 and $58.3 per barrel respectively, a 2.2% and 0.7% decrease from December 2. Oversupply expectations and weakening geopolitical support led to the decline [4][58]. - **2.2.2 Copper Prices Rose and Aluminum Prices Fell** - On December 9, the prices of LME 3 - month copper and aluminum increased by 3.0% and decreased by 0.7% respectively compared to December 2. The domestic commodity index showed different trends in month - on - month changes [4][63]. - **2.2.3 Most Industrial Product Prices Declined Month - on - Month** - Since December, most industrial product prices declined month - on - month, with coking coal and coke having the largest declines. The year - on - year decline in most industrial product prices narrowed, except for cold - rolled sheet and glass [4][65].

Report Industry Investment Rating - Not provided in the content Core Viewpoints - The subscription sentiment for new science and technology innovation bonds has cooled. The supply scale of the primary market has decreased, and its anti - decline ability is being tested. When selecting bonds, it is advisable to choose individual bonds with high liquidity and strong credit support and wait for more attractive valuation points [2][4] Summary by Directory 1. Primary Issuance Scale and Structure - The subscription sentiment for new science and technology innovation bonds has cooled. Due to the rise in bond market interest rates, the financing cost of issuance subjects has increased. This week (December 1 - 5, 2025), the primary market supply scale reached 45.54 billion yuan, a significant decline from the previous two weeks. Affected by specific risk events and year - end market caution, the subscription sentiment has continued to cool, but the reading is still higher than that of non - science and technology general credit bonds [2][12] 2. Secondary Trading Activity and Pricing - **Rating and Industry Distribution**: The ratings of outstanding science and technology innovation bonds are highly concentrated. Bonds with an implied rating of AA+ and above account for 72.6%, and AA - rated medium - quality individual bonds account for 23.1%, reflecting the financing needs of some small and medium - sized science and technology innovation entities. The industry distribution is dominated by traditional industries, with the bond quantity of industries such as building decoration, public utilities, and comprehensive accounting for 37.4%. Textile and apparel, pharmaceutical biology, power equipment, and communication industries have an excess spread of over 13bp compared to the overall credit bonds of the industry [3][19] - **Liquidity**: Driven by the active trading of science and technology innovation bond ETFs this week, the number of transactions of science and technology innovation bonds has increased to 724, far exceeding the weekly average of 400 since November. However, the weekly turnover rate of science and technology innovation bonds has dropped to 1.2%, and the liquidity is weaker than the overall general credit bonds [3][28] - **Yield and Price Comparison**: The anti - decline ability of science and technology innovation bonds is being tested. Last week, the average weekly trading yield of 1 - 3 - year exchange - traded science and technology innovation bonds increased by 6.8bp compared to the previous week, with a stronger adjustment amplitude than general credit bonds of the same term. The reasons for the large retracement are the weakening of demand - side support and the partial erasure of the premium advantage. In terms of the internal price comparison of science and technology innovation bonds, the spread between the index component bonds and non - component bonds has been stable at 10 - 15bp in the past two weeks, and the spread between the inter - bank variety and the component bonds is basically within 5bp. For the 1 - 3 - year variety, there is still a compression space of 24bp [4][34]

- The report tracks the performance of high-frequency stock selection factors, including Price Range Factor, Price-Volume Divergence Factor, Regret Avoidance Factor, and Slope Convexity Factor. These factors are evaluated based on their excess returns and predictive capabilities[2][3][11] - **Price Range Factor**: This factor measures the activity of stock transactions in different price ranges during the day, reflecting investors' expectations for future stock trends. It includes sub-factors such as high-price range transaction volume (VH80TAW), high-price range transaction count (MIH80TAW), and low-price range average transaction volume (VPML10TAW). The factor shows a strong predictive effect and stable performance this year[3][12][14] - **Price-Volume Divergence Factor**: This factor evaluates the correlation between stock prices and trading volumes. A lower correlation indicates a higher likelihood of future price increases. Sub-factors include price-to-transaction count correlation (CorrPM) and price-to-volume correlation (CorrPV). The factor has shown relatively stable performance this year, despite a declining trend since 2020[3][20][22] - **Regret Avoidance Factor**: Based on behavioral finance, this factor examines the proportion and degree of stock price rebounds after being sold by investors. Sub-factors include sell-rebound proportion (LCVOLESW) and sell-rebound deviation (LCPESW). The factor demonstrates stable out-of-sample excess returns, indicating that regret avoidance sentiment significantly impacts stock price expectations[3][23][31] - **Slope Convexity Factor**: Derived from the elasticity of supply and demand, this factor uses order book data to calculate the slope and convexity of buy and sell orders. Sub-factors include low-level slope (Slope_abl) and high-level convexity (Slope_alh). The factor's performance has been relatively flat in recent years, with some fluctuations in recent weeks[3][32][35] - The report constructs two enhanced strategies: the "High-Frequency Gold" portfolio and the "High-Frequency & Fundamental Resonance" portfolio. The "High-Frequency Gold" portfolio combines the three high-frequency factors with equal weights, achieving an annualized excess return of 10.11% and an IR of 2.36. The "High-Frequency & Fundamental Resonance" portfolio integrates high-frequency factors with fundamental factors (e.g., consensus expectations, growth, and technical factors), achieving an annualized excess return of 14.21% and an IR of 3.39[3][39][44] - **Performance Metrics for High-Frequency Gold Portfolio**: Annualized return: 9.49%, Annualized volatility: 23.87%, Sharpe ratio: 0.40, Maximum drawdown: 47.77%, Annualized excess return: 10.11%, IR: 2.36, Maximum excess drawdown: 6.04%[40][43] - **Performance Metrics for High-Frequency & Fundamental Resonance Portfolio**: Annualized return: 13.66%, Annualized volatility: 23.49%, Sharpe ratio: 0.58, Maximum drawdown: 39.60%, Annualized excess return: 14.21%, IR: 3.39, Maximum excess drawdown: 4.52%[47][48]