Group 1: Manufacturing Sector Insights - The manufacturing PMI rose to 50.1%, marking a return to the expansion zone after 8 months[2] - The production index increased by 1.7 percentage points to 51.7%, attributed to reduced uncertainties in the external trade environment[2] - The new orders index improved by 1.6 percentage points to 50.8%, indicating the first return to expansion in the second half of the year[2] Group 2: Trade and Pricing Dynamics - New export orders increased by 1.4 percentage points to 49.0%, with a significant slowdown in contraction[2] - The factory price index's contraction pace continued to slow, while raw material purchase prices expanded, indicating ongoing operational pressures for enterprises[2] - Inventory levels for raw materials and finished products continued to decline, reflecting a de-stocking trend[2] Group 3: Non-Manufacturing Sector Performance - The non-manufacturing business activity index rose by 0.7 percentage points to 50.2%, returning to the expansion zone[3] - The construction sector's business activity index surged by 3.2 percentage points to 52.8%, driven by favorable weather and upcoming holidays[3] - The service sector's business activity index saw a slight increase of 0.2 percentage points to 49.7%, remaining below the expansion threshold[3] Group 4: Future Outlook and Risks - The composite PMI output index rose by 1.0 percentage point to 50.7%, driven by the rebound in both manufacturing and non-manufacturing sectors[3] - The outlook for January 2026 suggests continued expansion in manufacturing, supported by a stable external trade environment and incremental policy implementations[3] - Risks include potential underperformance of policy deployments and uncertainties in the external environment due to rising global trade protectionism[3]

Macro and Strategy Research - The core support for A-share performance in 2026 is expected to come from price stability rather than volume growth, with PPI showing signs of recovery in October and November 2025, indicating a potential narrowing of year-on-year declines in 2026 [3][4] - The "anti-involution" policy is anticipated to provide significant price support in 2025, with ongoing efforts to regulate capacity in key industries, which may stabilize prices and reduce the risk of PPI turning negative [4][5] - External factors, including potential interest rate cuts by the Federal Reserve ahead of the 2026 midterm elections, could positively influence PPI recovery and global commodity prices [5] Fixed Income Research - The report discusses how bond ETFs' premiums and discounts affect the underlying securities' prices, particularly during market adjustments, where investor confidence impacts ETF net asset values [6][7] - The liquidity of underlying assets is significantly affected during deep discounts, leading to increased market pressure and potential price discovery issues [8] - The report emphasizes the importance of understanding the relationship between ETF pricing and underlying bond performance, particularly in the context of market fluctuations and liquidity constraints [9] Industry Research - In the steel sector, demand is expected to weaken seasonally, leading to increased inventory pressure, while macroeconomic conditions remain supportive for price stability [19][21] - The copper market is facing supply constraints due to incidents at major mines, which may support prices despite weak demand; the sector is expected to benefit from increased demand in electric vehicles and infrastructure [22] - The aluminum industry is projected to see stable profits due to strict production limits and potential demand growth from new energy sectors, with the "anti-involution" policy expected to improve the supply landscape [22] - Gold prices are influenced by geopolitical risks and U.S. economic data, with long-term trends favoring gold as a hedge against economic instability [22] - The rare earth sector is poised for growth due to strategic export controls and increasing demand from high-tech industries, suggesting a positive outlook for related companies [23]

Quantitative Models and Construction Methods 1. Model Name: HP Filter - **Model Construction Idea**: The HP filter is used to decompose a time series into trend and cyclical components, aiming to remove long-term trends and short-term noise from macroeconomic factors[10][9] - **Model Construction Process**: The HP filter solves the following optimization problem to balance trend smoothness and data fit: $$\operatorname*{min}\left\{\sum_{t=1}^{T}(y_{t}-g_{t})^{2}+\lambda\sum_{t=2}^{T-1}[(g_{t+1}-g_{t})-(g_{t}-g_{t-1})]^{2}\right\}$$ - \(y_t\): Original time series data - \(g_t\): Trend component - \(\lambda\): Smoothing parameter, where larger \(\lambda\) results in a smoother trend In this report, a larger \(\lambda\) is used to remove long-term trends, and a smaller \(\lambda\) is applied to filter out noise, resulting in a mid-cycle series for further analysis[10] - **Model Evaluation**: The HP filter aligns with classical macroeconomic analysis frameworks but suffers from endpoint bias and cannot identify different frequency cycles[3][42] 2. Model Name: Fourier Transform - **Model Construction Idea**: Fourier Transform decomposes a time series into a combination of sine waves with different frequencies, amplitudes, and phases, enabling the identification of dominant cycles in macroeconomic data[25][26] - **Model Construction Process**: The Fourier Transform is defined as: $$F(f)=\int_{-\infty}^{\infty}f(x)e^{-i2\pi f(x)}\,\mathrm{d}x$$ - \(f(x)\): Time series data - \(F(f)\): Frequency domain representation Since most macroeconomic data are non-stationary, the HP filter is first applied to remove long-term trends, producing a stationary series. The Fourier Transform is then used to extract the main cycles and fit the periodic series[25][26] - **Model Evaluation**: Suitable for analyzing historical data and identifying economic cycle patterns, but assumes constant periodic structures over time, which may reduce short-term fit[3][42] 3. Model Name: Hybrid Filtering - **Model Construction Idea**: Combines the strengths of HP filtering and Fourier Transform to achieve both extrapolation capability and flexibility in cycle fitting[42] - **Model Construction Process**: - Apply Fourier Transform to identify periodic patterns in macroeconomic data - Use HP filtering to observe short-term trends in macroeconomic factors - Combine the results to create a series that retains both periodicity and trend information[42] - **Model Evaluation**: Balances the advantages of both methods, providing better adaptability for macroeconomic data analysis[42] 4. Model Name: Merrill Lynch Clock Model - **Model Construction Idea**: Divides the economic cycle into four phases based on economic growth and inflation, using PMI YoY growth as a proxy for economic growth and PPI YoY growth for inflation[68][72] - **Model Construction Process**: - Recovery: PMI YoY up, PPI YoY down → 60% stocks, 40% bonds - Expansion: PMI YoY up, PPI YoY up → 60% commodities, 40% stocks - Stagflation: PMI YoY down, PPI YoY up → 60% cash, 40% commodities - Recession: PMI YoY down, PPI YoY down → 60% bonds, 40% cash[72] - **Model Evaluation**: Achieves higher returns and Sharpe ratio compared to a balanced allocation model, with a monthly win rate of 56.49%[68][70] 5. Model Name: Monetary-Credit Model - **Model Construction Idea**: Adapts the Merrill Lynch Clock for the Chinese market by focusing on monetary and credit conditions, using M2 YoY growth for monetary policy and social financing YoY growth for credit conditions[76] - **Model Construction Process**: - Loose Monetary & Loose Credit: M2 YoY up, social financing YoY up → 60% stocks, 40% commodities - Tight Monetary & Loose Credit: M2 YoY down, social financing YoY up → 60% commodities, 40% stocks - Tight Monetary & Tight Credit: M2 YoY down, social financing YoY down → 60% cash, 40% bonds - Loose Monetary & Tight Credit: M2 YoY up, social financing YoY down → 60% bonds, 40% stocks[76] - **Model Evaluation**: Slightly lower annualized returns than the Merrill Lynch Clock but demonstrates more stable excess returns since 2020[76][85] --- Model Backtesting Results 1. HP Filter - **Annualized Excess Return**: 1.43%-3.16% for stock index timing[57][58] - **Annualized Excess Return**: 4.84%-9.91% for stock-bond timing[60][61] 2. Fourier Transform - **Core Cycle**: Identified a 38-44 month cycle across all macroeconomic factors, suggesting a 3-4 year mid-cycle pattern[26][83] 3. Merrill Lynch Clock Model - **Annualized Return**: 11.71% - **Annualized Excess Return**: 5.82% - **Sharpe Ratio**: 1.037 - **Monthly Win Rate**: 56.49%[68][70] 4. Monetary-Credit Model - **Annualized Return**: 9.93% - **Annualized Excess Return**: 4.04% - **Sharpe Ratio**: 0.589 - **Monthly Win Rate**: 56.90%[76][79] --- Quantitative Factors and Construction Methods 1. Factor Name: PMI YoY Growth - **Construction Idea**: Represents economic growth trends[9][83] - **Construction Process**: Derived from the year-over-year growth rate of the Purchasing Managers' Index (PMI)[9][83] 2. Factor Name: PPI YoY Growth - **Construction Idea**: Represents inflation trends[9][83] - **Construction Process**: Derived from the year-over-year growth rate of the Producer Price Index (PPI)[9][83] 3. Factor Name: M1 YoY Growth - **Construction Idea**: Reflects changes in narrow money supply[9][83] - **Construction Process**: Derived from the year-over-year growth rate of M1[9][83] 4. Factor Name: M2 YoY Growth - **Construction Idea**: Reflects changes in broad money supply[9][83] - **Construction Process**: Derived from the year-over-year growth rate of M2[9][83] 5. Factor Name: Social Financing YoY Growth - **Construction Idea**: Represents credit supply conditions[9][83] - **Construction Process**: Derived from the year-over-year growth rate of total social financing[9][83] 6. Factor Name: 1-Year Treasury Yield YoY Difference - **Construction Idea**: Reflects interest rate trends[9][83] - **Construction Process**: Calculated as the year-over-year difference in 1-year treasury yields[9][83] 7. Factor Name: Industrial Production YoY Growth - **Construction Idea**: Represents industrial output trends[9][83] - **Construction Process**: Derived from the year-over-year growth rate of industrial production[9][83] 8. Factor Name: Corporate Profit YoY Growth - **Construction Idea**: Reflects corporate profitability trends[9][83] - **Construction Process**: Derived from the year-over-year growth rate of corporate profits[9][83] --- Factor Backtesting Results Stock Index Timing - **Annualized Excess Return**: 1.43%-3.16% for factors like M1 YoY, PPI YoY, and PMI YoY[57][58] Stock-Bond Timing - **Annualized Excess Return**: 4.84%-9.91% for factors like M1 YoY, PPI YoY, and PMI YoY[60][61]

Investment Rating - The report maintains a "Positive" rating for the steel industry and a "Positive" rating for the non-ferrous metals industry, with "Buy" ratings for specific companies including Luoyang Molybdenum (603993), Zhongjin Gold (600489), Huayou Cobalt (603799), Zijin Mining (601899), and China Aluminum (601600) [5][6]. Core Insights - The steel industry is expected to see improved profitability due to the implementation of stable growth policies and an anticipated increase in demand from shipbuilding and construction sectors. The focus on "equipment upgrades" and "low-carbon transformation" is expected to drive industry development [3][5]. - In the copper sector, global copper supply is projected to tighten further due to incidents at major mines, providing support for copper prices. Demand is expected to increase as major economies enter a rate-cutting cycle, enhancing the industry's outlook [3][5]. - The aluminum sector is facing a supply surplus, with stable supply conditions and weak demand expected to keep prices under pressure in the short term. However, the industry is anticipated to benefit from improved profitability as the "anti-involution" policy takes effect [5][6]. - Gold prices are influenced by geopolitical risks and changes in U.S. economic data, with long-term trends favoring gold due to central bank purchases and the weakening of the U.S. dollar [5][6]. - The rare earth sector is expected to see a revaluation of related companies due to China's export control upgrades, with significant demand growth anticipated from robotics and new energy sectors [5][6]. - The cobalt market is expected to remain tight due to constrained supply from the Democratic Republic of Congo, with demand driven by electric vehicles and consumer electronics [5][6]. Summary by Sections Steel Industry - The steel industry is experiencing a seasonal decline in demand, with limited improvement expected. Steel inventory pressures may accumulate further as demand weakens [2][3][16]. - As of December 26, 2025, the total steel inventory was 12.58 million tons, a decrease of 2.73% from the previous week but an increase of 12.07% year-on-year [24][25]. - The average price of steel on December 26 was 3,439.15 CNY per ton, reflecting a decrease of 0.28% from the previous week [31][32]. Copper Industry - The copper market is facing a seasonal demand slowdown, with high prices suppressing downstream demand. Supply is expected to contract as the year ends, leading to weaker price drivers in the short term [4][34]. - On December 26, the price of copper was 98,000 CNY per ton, an increase of 5.79% from the previous week [38]. Aluminum Industry - The aluminum sector is characterized by stable supply and weak demand, with prices expected to remain under pressure. The average price of aluminum on December 26 was 22,000 CNY per ton, a 0.92% increase from the previous week [42]. Gold Industry - Geopolitical tensions and U.S. economic data are key factors influencing gold prices, which are expected to experience increased volatility in the short term. On December 26, gold prices were 4,562.00 USD per ounce, up 4.42% from the previous week [47]. Rare Earth and Cobalt Industries - The rare earth sector is poised for growth due to strategic importance and demand from emerging technologies. The cobalt market is expected to remain tight, driven by electric vehicle demand [5][6].

Report Industry Investment Rating No information provided in the given content. Core Viewpoints - The issuance guidance rates announced by the National Association of Financial Market Institutional Investors during the period from December 22 to December 28, 2025, showed a differentiated trend, with most high - grade rates declining and most medium - and low - grade rates rising, with an overall change range of - 3 BP to 2 BP [1][15][63]. - The issuance scale of credit bonds decreased compared with the previous period. Corporate bonds remained at zero issuance, the issuance amounts of corporate bonds and private placement notes decreased, while the issuance amounts of medium - term notes and commercial paper increased. The net financing of credit bonds decreased compared with the previous period [1][13][63]. - In the secondary market, the trading volume of credit bonds increased compared with the previous period. The trading volumes of corporate bonds, corporate bonds, medium - term notes, and private placement notes increased, while the trading volume of commercial paper decreased [1][19][63]. - The yields of most credit bonds declined during this period. The credit spreads of medium - and short - term notes, corporate bonds, and urban investment bonds were differentiated, with most 1 - year and 7 - year spreads widening and most 3 - year and 5 - year spreads narrowing [1][22][63]. - From the perspective of absolute return, the shortage of supply and relatively strong allocation demand will promote the continued recovery of credit bonds. In the long run, the yields are still in a downward channel, and the idea of increasing allocation during adjustments is still feasible. From the perspective of relative return, although the compression space of credit spreads at all tenors is insufficient, the probability of unilateral callback in the short term is also small. Therefore, it is still possible to achieve the coupon strategy through credit downgrade and extending the duration [1][63]. Summary by Directory 1. Primary Market Situation 1.1 Issuance and Maturity Scale - From December 22 to December 28, 2025, a total of 211 credit bonds were issued, with an issuance amount of 254.432 billion yuan, a 2.51% decrease compared with the previous period. The net financing of credit bonds was 42.433 billion yuan, a decrease of 18.343 billion yuan compared with the previous period [13]. - Corporate bonds had zero issuance, with a net financing of - 6.252 billion yuan, an increase of 0.498 billion yuan compared with the previous period. Corporate bonds issued 74 bonds, with an issuance amount of 49.363 billion yuan, a 46.55% decrease compared with the previous period, and a net financing of 15.757 billion yuan, a decrease of 29.511 billion yuan compared with the previous period. Medium - term notes issued 66 bonds, with an issuance amount of 109.469 billion yuan, a 30.15% increase compared with the previous period, and a net financing of 78.532 billion yuan, an increase of 37.169 billion yuan compared with the previous period. Commercial paper issued 60 bonds, with an issuance amount of 90.117 billion yuan, a 23.36% increase compared with the previous period, and a net financing of - 44.152 billion yuan, a decrease of 25.187 billion yuan compared with the previous period. Private placement notes issued 11 bonds, with an issuance amount of 5.483 billion yuan, a 52.24% decrease compared with the previous period, and a net financing of - 1.452 billion yuan, a decrease of 1.312 billion yuan compared with the previous period [13]. 1.2 Issuance Interest Rates - The issuance guidance rates announced by the National Association of Financial Market Institutional Investors were differentiated, with most high - grade rates declining and most medium - and low - grade rates rising, with an overall change range of - 3 BP to 2 BP. By tenor, the 1 - year variety had an interest rate change range of - 2 BP to 0 BP, the 3 - year variety had an interest rate change range of - 3 BP to 2 BP, the 5 - year variety had an interest rate change range of - 3 BP to 2 BP, and the 7 - year variety had an interest rate change range of - 2 BP to 1 BP. By grade, the key AAA - grade and AAA - grade varieties had an interest rate change range of - 3 BP to - 1 BP, the AA + - grade variety had an interest rate change range of - 1 BP to 2 BP, the AA - grade variety had an interest rate change range of 0 BP to 2 BP, and the AA - - grade variety had an interest rate change range of 0 BP to 1 BP [15]. 2. Secondary Market Situation 2.1 Market Trading Volume - From December 22 to December 28, 2025, the total trading volume of credit bonds was 1.030617 trillion yuan, a 7.72% increase compared with the previous period. Corporate bonds, corporate bonds, medium - term notes, commercial paper, and private placement notes traded 28.754 billion yuan, 446.075 billion yuan, 347.636 billion yuan, 145.597 billion yuan, and 62.555 billion yuan respectively [19]. 2.2 Credit Spreads - In medium - and short - term notes, the credit spreads of each variety were differentiated. The 1 - year credit spreads widened; among the 3 - year notes, the credit spreads of AA - grade and AA - - grade widened, while the spreads of AAA - grade and AA + - grade narrowed; the 5 - year credit spreads narrowed; among the 7 - year notes, the credit spread of AAA - grade narrowed, while the spread of AA + - grade widened [22]. - In corporate bonds, the credit spreads of each variety were differentiated. The 1 - year AAA - grade credit spread narrowed, while the spreads of other varieties widened; among the 3 - year notes, the credit spreads of AAA - grade and AA + - grade narrowed, while the spreads of AA - grade and AA - - grade widened; the 5 - year credit spreads narrowed; among the 7 - year notes, the credit spread of AAA - grade narrowed, while the spreads of other varieties widened [27]. - In urban investment bonds, the credit spreads of each variety were differentiated. The 1 - year credit spreads widened; the 3 - year credit spreads narrowed; among the 5 - year notes, the credit spreads of AAA - grade and AA + - grade narrowed, while the spreads of AA - grade and AA - - grade widened; among the 7 - year notes, the credit spread of AAA - grade narrowed, while the spreads of other varieties widened [37]. 2.3 Term Spreads and Rating Spreads - For AA + medium - and short - term notes, the 3Y - 1Y term spread narrowed by 1.20 BP, the 5Y - 3Y term spread narrowed by 3.20 BP, and the 7Y - 3Y term spread widened by 3.22 BP. The 3Y - 1Y term spread was at a low - to - middle historical percentile (21.6%), the 5Y - 3Y term spread was at a low - to - middle historical percentile (34.5%), and the 7Y - 3Y term spread was at a historical median (41.9%). In terms of rating spreads, the (AA - )-(AAA) spread of 3 - year medium - and short - term notes widened by 3.00 BP, the (AA)-(AAA) spread widened by 3.00 BP, and the (AA + )-(AAA) spread widened by 2.00 BP [47]. - For AA + corporate bonds, the 3Y - 1Y term spread narrowed by 3.69 BP, the 5Y - 3Y term spread widened by 3.12 BP, and the 7Y - 3Y term spread widened by 8.55 BP. The 3Y - 1Y term spread was at a historical low (12.2%), the 5Y - 3Y term spread was at a low - to - middle historical percentile (36.3%), and the 7Y - 3Y term spread was at a historical median (42.9%). In terms of rating spreads, the (AA - )-(AAA) spread of 3 - year corporate bonds widened by 6.00 BP, the (AA)-(AAA) spread widened by 6.00 BP, and the (AA + )-(AAA) spread remained unchanged from the previous period [52]. - For AA + urban investment bonds, the 3Y - 1Y term spread narrowed by 0.72 BP, the 5Y - 3Y term spread narrowed by 1.67 BP, and the 7Y - 3Y term spread widened by 2.25 BP. The 3Y - 1Y term spread was at a low - to - middle historical percentile (20.3%), the 5Y - 3Y term spread was at a low - to - middle historical percentile (31.2%), and the 7Y - 3Y term spread was at a historical median (46.8%). In terms of rating spreads, the (AA - )-(AAA) spread of 3 - year urban investment bonds narrowed by 1.00 BP, the (AA)-(AAA) spread widened by 1.00 BP, and the (AA + )-(AAA) spread remained unchanged from the previous period [54]. 3. Credit Rating Adjustment and Default Bond Statistics 3.1 Credit Rating Adjustment Statistics - From December 22 to December 28, 2025, a total of 2 companies had their ratings (including outlooks) adjusted, both of which were upgrades. They were Wenzhou Transportation Development Group Co., Ltd. and Guangxi Energy Group Co., Ltd. [60]. 3.2 Default and Extension Bond Statistics - There were no credit bond defaults during the period from December 22 to December 28, 2025. One issuer, Bohai Leasing Co., Ltd., had its credit bonds extended, namely "18 Bojin 03" and "18 Bozu 05", with a total bond balance of 823 million yuan at the time of extension [62]. 4. Investment Viewpoints - The overall idea is to continue to be optimistic about the credit bond market in the long term, but pay attention to short - term fluctuations. In terms of configuration, the coupon strategy can be moderately optimistic, and the trading strategy can be kept optimistic. When selecting bonds, focus on the trend of interest - rate bonds and the coupon value of individual bonds. At the same time, it is possible to achieve the coupon strategy through credit downgrade and extending the duration according to one's own capital characteristics, but pay attention to the rhythm [1][63].

1. Report Industry Investment Rating - No relevant content provided in the given report. 2. Core Viewpoints of the Report - The report focuses on the main characteristics of bond ETF premiums and discounts and their impact on component bonds. It analyzes the influence mechanism of bond ETF premiums and discounts on component bonds, the characteristics and influencing factors of premiums and discounts, the volume - price changes of component bonds during premium and discount periods, and provides corresponding conclusions and insights [8][61]. 3. Summary According to Relevant Catalogs 3.1 Bond ETF Premium and Discount Impact Mechanism on Component Bonds - The premium - discount rate is used to measure the deviation between the bond ETF price and the net value. In the discount stage, investors redeem shares in the primary market and sell ETFs in the secondary market, leading to a decline in the ETF price and net value. Arbitrage behavior can repair the discount to some extent. In the premium stage, investors subscribe for shares in the primary market and buy ETFs in the secondary market, causing the ETF price and net value to rise, and arbitrage can repair the premium. Different redemption mechanisms (physical redemption and cash redemption) have different impacts on ETFs [9][10][12]. 3.2 Characteristics and Influencing Factors of Bond ETF Premiums and Discounts 3.2.1 When Do Premiums and Discounts Occur? - Local - government bond ETFs had continuous deep discounts from 2022 - 2023, mainly due to low trading activity. Since 2024, they have maintained a slight premium. Credit - type ETFs had discounts from September 2022 to April 2023 and in the second half of 2025, and slight premiums in 2024 and the second quarter of 2025. The physical redemption mode often has a deeper discount than the cash redemption mode [17][20][21]. 3.2.2 How Do Turnover, Share, and Net Value Change During Premium and Discount Stages? - Turnover: In the deep - discount stage, turnover is prone to peak, but the correlation has weakened since 2025 [28][29][40]. - Share: There is synchronicity between short - term deep discounts and share redemptions [33][34][36]. - Net Value: In the deep - discount stage, the ETF net value often recovers before the price [38]. - Summary: In the deep - discount stage, the underlying asset liquidity of the ETF is extremely restricted. Turnover is prone to peak, but it does not necessarily correspond to continuous large - scale redemptions. Since 2025, the correlation between the premium - discount rate and turnover, share, and net - value changes has weakened [40]. 3.3 Volume - Price Change Characteristics of ETF Component Bonds During Premium and Discount Stages 3.3.1 Volume: Trading Activity - The trading activity is measured by the ratio of the number of bonds with transactions to the number of bonds without transactions. The trading activity of component bonds in different indexes responds differently to ETF premiums and discounts. The urban investment index shows an anti - intuitive phenomenon, while the Shanghai and Shenzhen market - making indexes conform to the theoretical mechanism [43][44][46]. 3.3.2 Price: Credit Spread - The credit spread is measured by the difference between the bond's yield to maturity and the yield of the same - term China Development Bank bond. In the deep - discount stage of the urban investment index, the credit spread of non - component bonds widens more significantly. In the Shanghai and Shenzhen market - making indexes, the credit spread of component bonds widens significantly during premium and discount periods, indicating higher price - discovery efficiency [53][54][56]. 3.4 Main Conclusions and Insights - In the deep - discount stage, the underlying asset liquidity is restricted, and large - scale redemptions often occur during short - term discounts in the continuous premium stage. Different indexes have different response patterns to ETF premiums and discounts. When selecting bonds in the discount stage, it is necessary to judge the source of the discount. The lack of liquidity in the credit - bond market is a major constraint, and bond ETFs should improve market efficiency and provide protection during market adjustments [62][63].

投资策略 [Table_MainInfo] A 股业绩支撑：政策呵护逻辑下的价格水平 ——A 股市场投资策略专题报告 | 究 | 分析师： | 宋亦威 | SAC NO： | 年 | 月 | 日 | S1150514080001 | 2025 | 12 | 30 | [Table_Analysis] | [Table_Summary] | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 证券分析师 | 投资要点： | 宋亦威 | | | | | | | | | | | | 就 | 年行情的业绩支撑而言，并不来自于量的超预期增长，而来自于 | ⚫ | 2026 | 022-23861608 | 价格端的有效支撑。从今年 | 月、11 | 月的情况来看，PPI | 价格已经连续 | 10 | | | | | songyw@bhzq.com | 两月出现环比转正，这种态势如能持续，将意味着明年 | 同比降幅将 | PPI | | | | | | | | | | | [Table_Author] | 严 ...

Macro and Strategy Research - The profit growth rate of industrial enterprises in China has marginally declined by 1.8 percentage points to 0.1% year-on-year for the period from January to November 2025, with November showing a significant drop of 13.1% compared to October, which is a decrease of 7.6 percentage points [4] - The industrial added value growth rate for November was 4.8%, a slight decrease of 0.1 percentage points from October, influenced by insufficient domestic demand and a high base effect from the previous year [4] - The revenue profit margin for January to November was 5.29%, down by 2.0% year-on-year, indicating a further expansion of the decline compared to the previous months [4] - Among 41 industrial sectors, 18 sectors achieved positive profit growth during the same period, with notable growth in sectors such as black metal smelting and processing, non-ferrous metal mining, and high-tech manufacturing [5] Fund Research - The market saw a continued inflow of nearly 50 billion yuan into the CSI A500 index, with the ETF market scale reaching a new high of over 6 trillion yuan [7][11] - The average return for equity funds was 2.69%, with 87.08% of funds reporting positive returns, while bond funds and other categories also showed positive performance [10] - The ETF market experienced a net inflow of 914.98 billion yuan, with bond ETFs leading the inflow at 599.48 billion yuan [10] Company Research: WuXi AppTec - WuXi AppTec is positioned as a leading integrated CRDMO provider, offering end-to-end drug development and manufacturing services, with a focus on continuous development through both organic and inorganic growth strategies [15] - The CRO industry is thriving due to the high costs and long timelines associated with drug development, leading to increased demand for specialized services [15] - WuXi Chemistry reported a strong performance in its integrated services, with a significant number of new molecules added to its pipeline, indicating robust growth potential [15] - The company has streamlined its operations by divesting its clinical services research business, allowing it to focus on core competencies and enhance its service offerings [16] Industry Research: Light Industry Manufacturing & Textile Apparel - The Chinese government plans to continue funding support for the "old-for-new" consumption policy in 2026, which has already driven over 2.5 trillion yuan in sales for related products in 2025 [19] - Retail sales of clothing and footwear saw a year-on-year increase of 3.5% in November, reflecting a positive trend in consumer spending [19] - The light industry manufacturing sector underperformed compared to the CSI 300 index, indicating challenges in the current market environment [19]

Macroeconomic and Strategy Research - The U.S. labor market remains in a weak balance, with inflation showing signs of slowing down, prompting the Federal Reserve to lower interest rates again in December. The Fed's cautious stance indicates only one rate cut is expected in 2026, which is less than market predictions [2][3] - In Europe, a weak economic recovery is coupled with the European Central Bank's increased tolerance for inflation, leading to market expectations of a rate hike in 2026 [3] - Domestic consumption and investment are slowing due to high bases and weak expectations, while external demand remains strong, particularly in export-oriented sectors. Structural support for service consumption is anticipated as policies support recovery [3][3] - The Central Economic Work Conference emphasized the need for stable economic growth and quality improvement, with a focus on the integrated effects of monetary and fiscal policies. A reserve requirement ratio cut is expected to be implemented first, with interest rate cuts being more structural [3][3] Fixed Income Research - Panda bonds, which are RMB-denominated bonds issued by foreign entities in China, have seen their market scale exceed 1.14 trillion RMB, reflecting the ongoing internationalization of the RMB and the opening of China's bond market [6][6] - The panda bond market has evolved through three stages: initial exploration (2005-2013), development with increased participation (2014-2022), and rapid expansion and product innovation (2023-present) [6][6] - Panda bonds offer lower financing costs compared to offshore dollar bonds and provide flexibility in fund usage, while also serving as a risk diversification tool for investors [7][7] - As of December 5, 2025, there are 263 panda bonds with a market size of 414.886 billion RMB, indicating a significant increase in issuance driven by policy optimization [7][7] Industry Research - The sixth batch of high-value medical consumables procurement has been initiated, with significant developments including the approval of a domestic anti-CTLA-4 monoclonal antibody and the introduction of a weight-loss version of semaglutide for cardiovascular indications [11][11] - The Shanghai Composite Index rose by 2.15% and the Shenzhen Component Index by 3.66% during the week of December 19-25, 2025, with the SW Pharmaceutical and Biological Index increasing by 1.43% [11][11] - The report suggests focusing on pharmaceutical companies whose products enter medical insurance and the investment opportunities arising from structural optimization in innovative drug payments, as well as the progress in the medical device sector following the initiation of high-value consumables procurement [12][12]

1. Report Industry Investment Rating No relevant content provided. 2. Core Viewpoints of the Report - In the last few trading days of the year, it is expected that there will be limited changes in the bond market. Interest rates may continue a mostly sideways trend. Attention should be paid to the catch - up opportunities of medium - and long - term varieties, while being vigilant about the high volatility of ultra - long - term varieties and the disturbance of rising cross - year funding prices on 1 - 2Y term varieties. Moderately seize the spread between China Development Bank bonds and treasury bonds with a term of 7Y and below, as well as the term spread between 5Y - 3Y treasury bonds [2][17]. - In the long run, the influence of fundamentals on bond market pricing is expected to increase in 2026, and price signals are the key [15]. 3. Summary by Relevant Catalogs 3.1 Funding Prices: Cross - year Funding Prices Rise - From December 19th to December 25th, the central bank's open - market operations had a net withdrawal of 6.59 billion yuan. On the 25th, 40 billion yuan of MLF was carried out, with an over - renewal of 10 billion yuan [2][8]. - During the statistical period, the 14 - day funding price rose significantly, with R014 rising by 24bp. Starting from the 25th, as 7 - day funds began to cross the year, DR007 rose 10bp on that day but remained in the range of 1.4 - 1.5%. Overnight funding prices continued to decline, with DR001 dropping to a new low of 1.26% for the year. The yield of inter - bank certificates of deposit declined slightly, with the 1Y certificate of deposit yield falling to around 1.64%, in line with the year - end seasonal characteristic of declining certificate of deposit yields [8]. 3.2 Primary Market: Issuance Nears the End - From December 19th to December 25th, only 11 interest - rate bonds were issued in the primary market, indicating that interest - rate bond issuance is coming to an end [2][9]. 3.3 Secondary Market: The Yield Curve Continues to Steepen - From December 19th to December 25th, the yields of most treasury bonds declined, and the seesaw effect between stocks and bonds continued to weaken. In terms of term structure, the yields of medium - and short - term treasury bonds declined more. The market traded on the expectation that the central bank would increase its support for the funding market and that the bond - buying scale in December would increase. The term spread between 10Y and 1Y treasury bonds widened to 53bp, reaching a new high since January 7, 2025. Long - end interest rates are still in a state of game, with large intraday fluctuations and limited response to Beijing's real - estate relaxation policies. In addition, secondary - market trading volume also decreased seasonally at the year - end [2][10]. 3.4 Market Outlook - Fundamentals: Currently, it is hard to say that the bond market has returned to fundamental pricing. Factors such as policy expectations, asset price - to - value ratios, and institutional behavior may still be dominant. However, in the longer term, the influence of fundamentals on bond market pricing is expected to increase in 2026, with price signals being the key [15]. - Policy: The central bank released the communiqué of the fourth - quarter monetary policy meeting. Three adjustments in the statements are worthy of attention. First, the statement of "preventing idle funds" was deleted. Second, "promoting a decline in the overall social financing cost" was adjusted to "promoting the overall social financing cost to operate at a low level." Combining these two points, it can be understood that the current overall social financing cost is already at a low level. Further interest - rate cuts may face many constraints and may not necessarily achieve good results, but there are still various means to inject funds, and liquidity injection tools of various terms will be used flexibly. Third, "optimizing supply" was added after the statement of "expanding domestic demand." From the perspective of financial institutions, this may indicate that goals such as the total amount of credit issuance are further downplayed, and more emphasis is placed on the quality of issuance [15]. - Funding: As the year - end approaches, funding prices may rise slightly, but with the central bank's open - market operation support, the possibility of a significant tightening of funds is limited [15].