股份發行人及根據《上市規則》第十九B章上市的香港預託證券發行人的證券變動月報表 截至月份: 2025年12月31日 狀態: 新提交 致：香港交易及結算所有限公司 公司名稱: 廣發証券股份有限公司 呈交日期: 2026年1月5日 I. 法定/註冊股本變動 | 1. 股份分類 | 普通股 | 股份類別 | H | | 於香港聯交所上市 (註1) | | 是 | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 證券代號 (如上市) | 01776 | 說明 | 廣發証券H股 | | | | | | | | | 法定/註冊股份數目 | | | 面值 | | 法定/註冊股本 | | | 上月底結存 | | | 1,701,796,200 | RMB | | 1 RMB | | 1,701,796,200 | | 增加 / 減少 (-) | | | 0 | | | RMB | | | | 本月底結存 | | | 1,701,796,200 | RMB | | 1 RMB | | 1,701,796,200 | | 2. 股份分類 | 普通股 | 股份 ...

智通财经APP获悉，广发证券发布研报称，2026年，我国牛肉总进口配额为268.8万吨，其中巴西份额 为110.6万吨，阿根廷为51.1万吨，乌拉圭32.4万吨，澳大利亚为20.5万吨。随着前期肉牛产能去化效应 显现，当前肉牛价格已经步入上行通道。同时，对进口牛肉产品配额制落地将有效缓和进口端的供应压 力，预计26年国内肉牛价格继续周期上涨，增厚牧业公司业绩弹性。此外，原奶行业大包粉库存逐步去 化，行业供需逐步走向平衡，目前原奶供给拐点已现，亦看好2026-27年原奶周期上行。 广发证券主要观点如下： 事件：12月31日，商务部发布公告，裁定进口牛肉数量增加对中国国内产业造成严重损害，决定自2026 年1月1日以"国别配额及配额外加征关税"形式对进口牛肉采取保障措施，保障措施实施期限为3年，对 超过配额的进口牛肉征收55%的额外关税，配额将逐年增加。 2024年进口牛肉占总供应27%，配额制落地缓和进口冲击 根据海关总署及国家统计局数据，2024年，我国牛肉进口量为287万吨，同比增长5.0%，其中巴西、阿 根廷、乌拉圭、澳大利亚进口量分别134万吨、59万吨、24万吨、21万吨，占比分别46.6%、20.6 ...

Quantitative Models and Construction Methods 1. Model Name: Fixed Proportion + Macro Indicators + Technical Indicators Combination - **Model Construction Idea**: This model combines fixed proportion asset allocation with adjustments based on macroeconomic and technical indicators to optimize portfolio performance[35][36] - **Model Construction Process**: - Select seven asset classes, including equities, bonds, commodities, and currencies - Set a fixed proportion as the baseline allocation for each asset class - Adjust the weights of non-currency assets based on the latest monthly signals from macroeconomic and technical indicators, while correspondingly increasing or decreasing the allocation to currency assets[37] - **Model Evaluation**: The model effectively integrates macro and technical signals to enhance portfolio performance and reduce risk[36] 2. Model Name: Classic Asset Allocation Model + Macro Indicators + Technical Indicators Combination - **Model Construction Idea**: This model incorporates classic asset allocation strategies, such as risk parity and volatility control, with macroeconomic and technical indicators to achieve better risk-adjusted returns[43] - **Model Construction Process**: - Use the same seven asset classes as the previous model - Set baseline weights based on risk parity or a 6% annualized volatility control - Adjust weights monthly based on macroeconomic and technical signals - Impose constraints on asset allocation proportions (e.g., equity allocation capped at 30%, commodity allocation capped at 20%) and turnover rates (e.g., single asset monthly turnover capped at 20%, total monthly turnover capped at 30%)[43] - **Model Evaluation**: The model balances risk and return effectively, with constraints improving feasibility and stability[43] --- Model Backtesting Results 1. Fixed Proportion + Macro Indicators + Technical Indicators Combination - Annualized Return: 10.22%[40] - Maximum Drawdown: 9.34%[40] - Annualized Volatility: 6.24%[40] 2. Classic Asset Allocation Model + Macro Indicators + Technical Indicators Combination - **Volatility Control (6%) + Macro Indicators + Technical Indicators Combination**: - Annualized Return: 9.10%[47] - Maximum Drawdown: 5.06%[47] - Annualized Volatility: 4.94%[47] - **Risk Parity + Macro Indicators + Technical Indicators Combination**: - Annualized Return: 8.28%[47] - Maximum Drawdown: 4.47%[47] - Annualized Volatility: 3.40%[47] --- Quantitative Factors and Construction Methods 1. Factor Name: Macroeconomic Trend Factor - **Factor Construction Idea**: Analyze the impact of macroeconomic indicator trends (upward or downward) on asset returns[10] - **Factor Construction Process**: - Use historical moving averages to determine the trend of a macroeconomic indicator - Conduct a t-test to evaluate whether asset returns differ significantly under upward and downward trends - Formula: $ t = \frac{\overline{R_1} - \overline{R_2}}{\sqrt{\frac{(n_1-1)S_1^2 + (n_2-1)S_2^2}{n_1+n_2-2} \left(\frac{1}{n_1} + \frac{1}{n_2}\right)}} \sim t_{n_1+n_2-2} $ where $\overline{R_1}$ and $\overline{R_2}$ are the average monthly returns under upward and downward trends, $S_1$ and $S_2$ are the standard deviations, and $n_1$ and $n_2$ are the number of months in each trend[10] - **Factor Evaluation**: The factor effectively identifies significant differences in asset returns under different macroeconomic trends[10] 2. Factor Name: Trend Indicator Factor - **Factor Construction Idea**: Use historical price data to measure the trend of different asset classes[16] - **Factor Construction Process**: - For equities: $(\text{2-month LLT average monthly return} - \text{(T-12 to T-2) month average monthly return})$ - For bonds: $(\text{2-month closing price average monthly return} - \text{(T-12 to T-2) month average monthly return})$ - For industrial commodities: $(\text{2-month closing price average monthly return})$ - For gold: $(\text{6-month closing price average monthly return})$[16] - **Factor Evaluation**: The factor provides a robust method for identifying asset price trends[16] 3. Factor Name: Valuation Indicator Factor - **Factor Construction Idea**: Use the equity risk premium (ERP) to measure equity valuation levels[21][27] - **Factor Construction Process**: - Calculate ERP as the inverse of the CSI 800 Index PE (TTM) minus the 10-year government bond yield - Define the 5-year historical percentile of ERP as: $ \text{Percentile} = \frac{\text{Current ERP} - \text{5-year ERP Minimum}}{\text{5-year ERP Maximum} - \text{5-year ERP Minimum}} $ - Assign scores based on the percentile: - >90%: +2 - 70%-90%: +1 - 30%-70%: 0 - 10%-30%: -1 - <10%: -2[22] - **Factor Evaluation**: The factor effectively captures valuation levels, with higher percentiles indicating lower valuations[22] 4. Factor Name: Fund Flow Indicator Factor - **Factor Construction Idea**: Measure the net fund flow into the CSI 800 Index to assess market sentiment[27][32] - **Factor Construction Process**: - Calculate the monthly active net inflow as: $(\text{1-month active net inflow} - \text{6-month average monthly active net inflow})$ - Positive values indicate fund inflow, while negative values indicate fund outflow[27][32] - **Factor Evaluation**: The factor provides a clear signal of market sentiment based on fund flow dynamics[32] --- Factor Backtesting Results 1. Macroeconomic Trend Factor - Equity: PMI (3-month moving average) → Positive trend, score: +1[15] - Bond: PMI (3-month moving average) → Negative trend, score: -1[15] - Gold: US M2 YoY (12-month moving average) → Positive trend, score: +1[15] - Industrial Commodities: PMI (3-month moving average) → Positive trend, score: +1[15] 2. Trend Indicator Factor - Equity: 2-month LLT average return → 0.38%, upward trend, score: +1[21] - Bond: 2-month closing price average return → -0.15%, downward trend, score: -1[21] - Gold: 6-month closing price average return → 4.20%, upward trend, score: +1[21] - Industrial Commodities: 2-month closing price average return → -0.09%, downward trend, score: -1[21] 3. Valuation Indicator Factor - Equity: 5-year ERP percentile → 51.77%, neutral valuation, score: 0[27] 4. Fund Flow Indicator Factor - Equity: 1-month active net inflow → 1863 billion RMB, fund inflow, score: +1[32]

Core Viewpoint - The quantitative convertible bond portfolio performed well in December, achieving a return of 4.57% for the month and a cumulative return of 25.63% since 2025, outperforming the China Securities Convertible Bond Index by 6.97% [1]. Group 1: Portfolio and Performance - The quantitative convertible bond portfolio is generated based on three factor systems: fundamental factors, low-frequency price-volume factors, and high-frequency price-volume factors, with monthly rebalancing [5]. - The portfolio's performance in December 2025 showed a monthly return of 4.57% and an excess return of 2.43% compared to the benchmark [1]. Group 2: Convertible Bond Factors - A total of 32 fundamental factors, 80 low-frequency price-volume factors, and 32 high-frequency price-volume factors for convertible bonds are being tracked, with detailed data available for subscription [2]. - The report illustrates the latest data using the pricing deviation factor as an example, which measures the difference between market price and theoretical pricing [12]. Group 3: Convertible Bond Index Timing - The timing strategy for the China Securities Convertible Bond Index is based on price-volume models, pricing deviations, and bond elasticity, indicating a bullish signal at the end of December with a recommended position of 2/3 [4][16]. - The timing signals for December 2025 show a consistent bullish outlook based on pricing models, with a position recommendation of 67% from December 22 onwards [16]. Group 4: Risk Warnings - The report provides risk warnings for convertible bonds based on forced delisting and risk alert rules, identifying specific bonds with trading and financial delisting risks [3][14]. - Various convertible bonds are flagged for different types of risks, including trading-related delisting warnings and event-type credit risk alerts [15].

Group 1 - The core viewpoint of the article highlights the strong performance of domestic CTA products in Q4 2025, with an overall profitability ratio of 80.6% among the analyzed products [1][9][10] - In Q4 2025, 57 new CTA products were issued, maintaining a stable issuance rate [5] - The median annualized return for the analyzed CTA products was 5.82%, with a median Sharpe Ratio of 0.89 and a maximum drawdown of -3.78% [9][10] Group 2 - The A-share market experienced a narrow range of fluctuations in Q4, with weak profitability for trend-based CTAs, as the overall valuation level remains high [2][36] - The bond market is expected to remain in a range-bound state, with limited downward space for interest rates and upward pressure from domestic inflation [3][48] - The commodity market saw a significant price increase driven by metals, with a notable divergence among different sectors [4][62] Group 3 - In the stock index futures market, the average daily trading volume for major contracts showed a slight decline, with the basis reflecting a mild backwardation [11][20] - Various trading strategies, including trend-following and style arbitrage, faced challenges, with the trend strategy yielding a loss of 2.97% in Q4 [25][26][28] - The bond futures market's volatility remained low, with historical data indicating a stable trading environment [37][40] Group 4 - The commodity market's volatility increased in Q4, with precious metals and industrial metals leading the gains, while energy and agricultural products faced declines [49][52] - The average return for commodity trend-following strategies was 2.9%, with copper and asphalt showing particularly strong performance [60][61] - The outlook for Q1 2026 suggests continued high volatility in metal prices, with a focus on related products [62]

智通财经APP获悉，广发证券发布研报称，展望2026年光储行业，国内多省份容量电价机制有望落地， 储能经济性迎来拐点；海外数据中心建设带动储能需求快速增长，2026年AIDC进入"交付大年"，美国 新增13GW数据中心将拉动10.7-25GWh配储需求。光伏行业方面，在市场监管总局的进一步要求下，光 伏反内卷有望得到进一步落实与加强，行业盈利改善可期，看好光伏产业链下游组件环节的盈利改善； 需求端，预计2026年全球光伏新增装机近580GW，同比+6%。 国内市场：多省份容量电价机制有望落地，储能经济性迎来拐点。内蒙、甘肃、宁夏等地储能配套政策 延续稳定储能预期，容量电价政策对储能经济性影响较大，以甘肃为例，测算甘肃独立储能IRR 资本金 有望达9.9%。随着多省份出台容量电价机制，预计2025-2027年国内储能需求达154/254/337GWh，同比 +40.2%/65.2%/32.5%。 美国：数据中心建设带动储能需求快速增长。根据Trend Force，2025年是AIDC配储"需求元年"，2026 年进入"交付大年"，美国新增13GW数据中心将拉动10.7-25GWh 配储需求；欧洲：灵活性资源需求 ...

Core Viewpoint - The report from GF Securities projects Yum China (09987) to achieve net profits attributable to shareholders of $9.2 billion, $10.1 billion, and $10.9 billion for the years 2025-2027, respectively, with a strong expectation for expansion and high shareholder returns [1][5]. Group 1: Same-Store Performance and Expansion - The company has shown resilient same-store performance, outperforming the industry average, with guidance for same-store sales growth of 0-2% for 2026-2028, indicating strong anti-cyclical capabilities [2][5]. - The company aims to reach a total of 20,000, 25,000, and 30,000 stores by 2026, 2028, and 2030, respectively, supported by optimized capital expenditure per store, flexible store formats, and an increased focus on franchising [2][5][6]. Group 2: Drivers of Same-Store Sales Growth - Key drivers for same-store sales improvement include the introduction of new modules like KPRO, stable classic products, and the launch of new popular items that broaden the price range to attract more customers [6]. - The brand's marketing strategy, particularly the "Crazy Thursday" campaign, has become a significant IP, enhancing customer loyalty and repeat purchases through brand membership [6]. - The company is enhancing its delivery sales and expanding into new dining scenarios, such as single-person meals and meal-sharing options, to strengthen its market presence [6]. Group 3: Shareholder Returns - The company plans to maintain annual dividends and share buybacks of $1.5 billion for 2025-2026, translating to a current market return rate of 8.8% [3][6]. - For 2027 and beyond, the company anticipates shareholder returns to be approximately 100% of its free cash flow, with expected annual returns of at least $9-10 billion for 2027-2028, corresponding to a return rate of about 5.3%-5.8% [3][6].

Core Viewpoint - The wind power sector is entering a new cycle of multiple prosperity starting in 2026, driven by domestic policies and global demand growth, particularly in offshore wind energy [1][2]. Group 1: Domestic Wind Power Installation Forecast - It is projected that from 2025 to 2027, the annual new installation capacity for onshore wind in China will be approximately 100-105 GW, while offshore wind capacity will increase from 9.0 GW to 15.0 GW, with a CAGR of about 29.1% [1]. - The global wind power demand is expected to grow, with a projected CAGR of about 8.8% for new installations from 2025 to 2030, with China and Europe contributing 73% of the new capacity [1]. Group 2: Pricing and Profitability Trends - Since Q4 2024, domestic onshore wind bidding prices have significantly rebounded, expected to maintain in the range of 1600-1700 RMB/kW (excluding towers) in 2025, reflecting a year-on-year increase of 10% [2]. - The industry is entering a profitability uptrend characterized by dual recovery in pricing and structure, alongside a decrease in expense ratios [2]. Group 3: New Growth Trends - The trend of large-scale wind turbine production is slowing, which is expected to reduce risks and provide long-term benefits to cost structures [3]. - There is a significant increase in overseas wind power demand, transitioning from merely exporting products to exporting capabilities and production capacity [3]. - The inclusion of renewable energy non-electric consumption in national assessments is accelerating the layout of hydrogen and ammonia production by wind turbine manufacturers [3].

1月5日，广发证券盘中上涨2.18%，截至10:13，报22.50元/股，成交5.67亿元，换手率0.43%，总市值 1711.32亿元。 资金流向方面，主力资金净流出3122.33万元，特大单买入7423.98万元，占比13.09%，卖出9445.45万 元，占比16.66%；大单买入1.46亿元，占比25.78%，卖出1.57亿元，占比27.72%。 广发证券今年以来股价涨2.18%，近5个交易日涨2.27%，近20日涨7.40%，近60日跌2.56%。 资料显示，广发证券股份有限公司位于广东省广州市天河区马场路26号广发证券大厦，成立日期1994年 1月21日，上市日期1997年6月11日，公司主营业务涉及投资银行业务、财富管理业务、交易及机构业务 和投资管理业务。主营业务收入构成为：财富管理业务40.08%，交易及机构业务32.27%，投资管理业 务24.97%，投资银行业务2.14%，其他0.54%。 广发证券所属申万行业为：非银金融-证券Ⅱ-证券Ⅲ。所属概念板块包括：参股基金、低市盈率、证金 汇金、期货概念、养老金概念等。 分红方面，广发证券A股上市后累计派现396.04亿元。近三年，累计派现93 ...

Core Viewpoint - The report from GF Securities projects Yum China (09987) to achieve net profits of $9.2 billion, $10.1 billion, and $10.9 billion for the years 2025-2027, respectively, with a strong same-store performance and expansion expectations, maintaining a high shareholder return guidance [1] Group 1: Financial Projections - The expected net profits for Yum China are $9.2 billion in 2025, $10.1 billion in 2026, and $10.9 billion in 2027 [1] - The company maintains a target of 0-2% same-store sales growth for 2026-2028, indicating strong anti-cyclical capabilities [1] Group 2: Operational Strengths - The company is supported by excellent operational levels, strong brand momentum, and a comprehensive digital system and supply chain, facilitating rapid expansion [1] - The total number of stores is projected to reach 20,000 in 2026, 25,000 in 2028, and 30,000 in 2030, aided by optimized capital expenditure per store and flexible store formats [1] Group 3: Same-Store Sales Drivers - Key drivers for same-store sales improvement include new modules like KFC's KPRO, a solid lineup of classic products, and the introduction of new popular items [2] - The brand "Crazy Thursday" has become a significant marketing IP, enhancing customer loyalty through brand membership and collaborations [2] - The company is expanding its delivery sales and exploring new dining scenarios, such as single-person meals and meal-sharing options [2] Group 4: Shareholder Returns - The company plans to maintain annual dividends and buybacks of $1.5 billion for 2025-2026, with a current market value corresponding to a return rate of 8.8% [3] - For 2027 and beyond, the expected shareholder return is projected to be approximately 100% of the group's free cash flow, with annual returns of at least $9-10 billion anticipated for 2027-2028 [3]