Investment Rating - The report maintains a "Recommended" rating for the commercial aerospace industry, indicating a positive outlook for the sector's fundamentals and expectations for the industry index to outperform the benchmark index [3][9]. Core Insights - The commercial aerospace industry is experiencing significant growth, with the industry scale expected to reach 2.8 trillion yuan by 2025, representing a compound annual growth rate (CAGR) of over 26%, and a 180% increase compared to 2020 [6]. - The demand for testing equipment in the commercial aerospace sector is increasing, with higher requirements across all stages of satellite development, including environmental adaptability, electromagnetic compatibility, communication performance, network collaboration, reliability, and safety [6]. - Domestic companies are rapidly catching up to international competitors in the high-end testing equipment market, with substantial potential for domestic substitution, particularly in communication testing equipment [6]. Industry Overview - The commercial aerospace industry is characterized by three major trends: high standardization, high computing power integration, and multidisciplinary collaboration, which are driving structural opportunities in high-end instrument import substitution and the expansion of third-party laboratory capabilities [1]. - The industry is segmented into three main parts: upstream satellite manufacturing and rocket launch (approximately 10% of value), midstream ground equipment manufacturing (approximately 45%), and downstream satellite application services (approximately 45%) [6]. Related Companies - **Kunheng Shunwei**: Provides various high-end radio frequency testing and simulation instruments for the satellite industry, covering multiple downstream users in the satellite value chain [6]. - **Sushi Testing**: Offers a range of testing equipment and services throughout the entire lifecycle of aerospace products, including thermal vacuum, mechanics, climate, and comprehensive environmental testing [6]. - **Xicet Testing**: Achieved several international quality management certifications, indicating its capability in precision manufacturing for the aerospace sector [6]. - **Kangst**: Has provided calibration products to SpaceX from 2016 to 2024, although the financial impact is relatively small [6].

Investment Rating - The report maintains a "Strong Buy" rating for Guizhou Moutai [2][7] Core Insights - Guizhou Moutai has enhanced consumer reach through the launch of its i Moutai platform, addressing consumer pain points and establishing a four-dimensional channel system that benefits government, company, shareholders, distributors, and consumers [1][6] - The company is experiencing strong demand as it approaches the Spring Festival, with low channel inventory levels, which supports the ongoing market reform and cash returns [1][6][7] Summary by Sections Investment Rating - The report reiterates a "Strong Buy" rating, indicating confidence in the company's growth potential and market performance [2][7] Company Strategy - The launch of 500ml Flying Moutai and premium products on the i Moutai platform aims to improve consumer access and address the mismatch between supply and demand [6] - The new sales model combines self-sale, distribution, agency, and consignment, creating a win-win situation for all stakeholders involved [6] Market Dynamics - The i Moutai platform is expected to strengthen pricing power and mitigate concerns over wholesale price fluctuations, as it provides a reliable price benchmark for consumers [6] - Current market conditions show robust consumer demand, particularly among younger demographics, with low inventory levels reported across various sales channels [6][7] Financial Projections - The report forecasts earnings per share (EPS) for 2025, 2026, and 2027 to be 71.54, 73.49, and 76.96 yuan respectively, with a corresponding price-to-earnings (PE) ratio of 19x for 2026 [7][10] - Revenue and net profit are projected to grow steadily, with total revenue expected to reach 182.49 billion yuan in 2025, reflecting a year-on-year growth of 5% [10][19]

Quantitative Models and Construction Methods 1. Model Name: Multi-Cycle Timing Model for Domestic Interest Rates - **Model Construction Idea**: The model uses kernel regression algorithms to identify the support and resistance lines of interest rate trends. It evaluates the breakthrough patterns of interest rate movements across different investment cycles to generate timing signals[10][22][19] - **Model Construction Process**: - **Data Input**: Yield-to-Maturity (YTM) data for 5-year, 10-year, and 30-year government bonds[10][22] - **Cycle Definition**: - Long cycle: Monthly frequency - Medium cycle: Bi-weekly frequency - Short cycle: Weekly frequency[10][22] - **Signal Generation**: - A signal is generated when at least two out of three cycles show consistent directional breakthroughs (upward or downward) - For example, if two cycles show upward breakthroughs, the final signal is "bearish" for interest rates[10][22] - **Model Evaluation**: The model effectively captures multi-cycle resonance in interest rate trends and provides actionable timing signals[10][22] 2. Model Name: Multi-Cycle Timing Model for US Interest Rates - **Model Construction Idea**: The domestic multi-cycle timing model is applied to the US Treasury market to assess its effectiveness in a different market environment[19] - **Model Construction Process**: - **Data Input**: Yield-to-Maturity (YTM) data for 10-year US Treasury bonds[19] - **Cycle Definition**: - Long cycle: Monthly frequency - Medium cycle: Bi-weekly frequency - Short cycle: Weekly frequency[19] - **Signal Generation**: - A signal is generated when at least two out of three cycles show consistent directional breakthroughs - If no consistent breakthroughs are observed, the final signal is "neutral"[19] - **Model Evaluation**: The model demonstrates adaptability to the US market but currently shows no significant signals, indicating a "neutral" stance[19] --- Model Backtesting Results 1. Multi-Cycle Timing Model for Domestic Interest Rates - **5-Year YTM Model**: - Long-term annualized return: 5.46% - Maximum drawdown: 2.88% - Return-to-drawdown ratio: 1.9 - Short-term annualized return (since 2024): 2.04% - Maximum drawdown: 0.59% - Return-to-drawdown ratio: 3.47 - Long-term excess return: 1.06% - Short-term excess return: 0.74%[23][35] - **10-Year YTM Model**: - Long-term annualized return: 6.03% - Maximum drawdown: 2.74% - Return-to-drawdown ratio: 2.2 - Short-term annualized return (since 2024): 2.3% - Maximum drawdown: 0.58% - Return-to-drawdown ratio: 3.98 - Long-term excess return: 1.63% - Short-term excess return: 1.2%[26][35] - **30-Year YTM Model**: - Long-term annualized return: 7.28% - Maximum drawdown: 4.27% - Return-to-drawdown ratio: 1.7 - Short-term annualized return (since 2024): 2.44% - Maximum drawdown: 0.92% - Return-to-drawdown ratio: 2.66 - Long-term excess return: 2.39% - Short-term excess return: 2.29%[31][35] 2. Multi-Cycle Timing Model for US Interest Rates - **10-Year YTM Model**: - Current signal: Neutral - No significant breakthroughs observed in long, medium, or short cycles[19][21] --- Quantitative Factors and Construction Methods 1. Factor Name: Interest Rate Structure Indicators (Level, Term, Convexity) - **Factor Construction Idea**: Transform YTM data into structural indicators to analyze the interest rate market from a mean-reversion perspective[7] - **Factor Construction Process**: - **Level Structure**: - Formula: $ \text{Level} = \text{Average YTM across maturities} $ - Current value: 1.64% - Historical percentiles: 29% (3 years), 17% (5 years), 9% (10 years)[7] - **Term Structure**: - Formula: $ \text{Term} = \text{YTM (10-year)} - \text{YTM (1-year)} $ - Current value: 0.59% - Historical percentiles: 56% (3 years), 41% (5 years), 48% (10 years)[7] - **Convexity Structure**: - Formula: $ \text{Convexity} = \text{Second derivative of YTM curve} $ - Current value: 0.14% - Historical percentiles: 53% (3 years), 32% (5 years), 32% (10 years)[7] - **Factor Evaluation**: These indicators provide a comprehensive view of the interest rate market's structural dynamics and are useful for mean-reversion analysis[7] --- Factor Backtesting Results 1. Interest Rate Structure Indicators - **Level Structure**: Current value: 1.64%, historical percentiles: 29% (3 years), 17% (5 years), 9% (10 years)[7] - **Term Structure**: Current value: 0.59%, historical percentiles: 56% (3 years), 41% (5 years), 48% (10 years)[7] - **Convexity Structure**: Current value: 0.14%, historical percentiles: 53% (3 years), 32% (5 years), 32% (10 years)[7]

Investment Rating - The report maintains a recommendation for the REITs industry [2] Core Insights - The REITs market has seen a total of 78 public REITs listed with a total market capitalization of 223.3 billion yuan and a circulating market value of 124.7 billion yuan [2] - The overall performance of the market in 2025 showed a cumulative increase of 4.3% in the CSI REITs total return index, with a notable rise of 16.2% in the first half of the year, followed by a decline of 10.2% in the second half due to various negative factors [7][8] - The average P/NAV for the REITs market at the end of 2025 was 1.14 times, indicating a return to historical average valuation levels [7] - The report suggests that the current REITs valuation has returned to a central position, indicating a potential opportunity for increased allocation [7] Market Overview - The secondary market performance in 2025 was characterized by a strong first half, driven by macro liquidity easing, followed by a weaker second half due to valuation corrections and negative market sentiment [8] - The average daily turnover rate for the market decreased throughout the year, reflecting a decline in trading enthusiasm, with an average of 0.67% for the year and dropping to 0.4% in December [9] - The report highlights that the IDC and consumer sectors outperformed the market, with increases of 44% and 33% respectively, while the energy sector showed the weakest performance [12][15] Primary Market Review - In 2025, the total number of new issuances and expansions was 25, with a total issuance amount of 47.3 billion yuan, representing a year-on-year decrease of 14% in the number of issuances and 27% in the total amount [16][17] - The average absolute return for newly listed REITs was 27% over the first four days of trading, with a 10.5% probability of "breaking" [21] Policy Review - Key policies in 2025 included the expansion of asset categories for infrastructure REITs to include commercial office buildings, hotels, and sports venues, as well as the initiation of commercial real estate REITs pilot programs [26][27][28] - The report notes that the regulatory environment is becoming more favorable for REITs, with efforts to streamline approval processes and broaden the scope of eligible assets [29][30]

Investment Rating - The report maintains a recommendation for the banking sector, indicating a cautious outlook on the industry as it navigates through changing deposit dynamics and regulatory environments [6]. Core Insights - The report highlights that approximately 74 trillion yuan of household time deposits are set to mature in 2026, with expected flows directed towards insurance, wealth management, and public funds [1][3]. - Regulatory changes are underway, with the central bank focusing on enhancing liquidity mechanisms for non-bank institutions and tightening controls on virtual currencies [14]. - The banking sector is experiencing a mixed performance, with some city commercial banks and rural commercial banks showing resilience, while larger state-owned and joint-stock banks face pressure [18]. Summary by Sections Market Dynamics - The A-share market saw a significant increase of 5.1%, while the banking sector faced a decline of 1.88%, indicating a divergence in performance among different banking institutions [1][18]. - The central bank has conducted substantial net withdrawals from the market, totaling 1.7 trillion yuan, leading to a general decline in funding rates [2][20]. Deposit Maturity and Flow - As of November 2025, total deposits in China reached 282.5 trillion yuan, with household deposits accounting for 163 trillion yuan. The report estimates that 114 trillion yuan in deposits will mature in 2026, with 74 trillion yuan being household time deposits [3][4]. - The report anticipates that the re-pricing of deposits will lead to significant reductions in deposit rates, potentially shifting household preferences towards higher-yielding financial products [4]. Investment Opportunities - The insurance sector is expected to benefit from the migration of funds, as it offers competitive rates compared to traditional deposits. The report predicts continued growth in the insurance market [4]. - Wealth management products are projected to see a moderate increase, with an estimated growth of 3 trillion yuan in 2026, despite potential volatility in net asset values [4]. - Retail public funds, particularly money market funds, are expected to maintain a growth rate of over 10%, driven by their liquidity and competitive yields compared to bank deposits [4].

新房网签面积同比降幅扩大，二手房网签面积同比降幅收窄 ——样本城市周度高频数据全追踪 周期/房地产 一、核心要点 图 1：样本城市新房及二手房网签面积同比（截至 1 月 8 日） 资料来源：Wind、房管局、招商证券等 证券研究报告 | 行业定期报告 2026 年 01 月 11 日 资料来源：Wind、房管局、招商证券等 前瞻及佐证指标： 二手及租金价格：2025 年 11 月，北京和广州二手成交价格同比降幅扩大幅度 均大于租金同比降幅扩大幅度；上海二手成交价格同比降幅扩大，租金同比降 幅收窄；深圳二手成交价格同比降幅扩大幅度大于租金同比增幅收窄幅度； 二手带看人数：2025 年 12 月，12 个样本城市平均带看人数较 11 月环比转负 至-5.1%，同比降幅较 11 月收窄 4.3 PCT 至-7.6%； 流动性前瞻：根据招商证券房地产组流动性前瞻指标判断，2026 年 1 月，宏 观层面流动性环比紧缩力度扩大，同比转向紧缩； 挂牌价调涨占比：2025 年 12 月，12 个样本城市挂牌价调涨房源占比从 11 月 的 5.4%上升 0.4 PCT 至 5.8%，同比降幅较 11 月收窄 15.8 PCT ...

证券研究报告 | 行业简评报告 2026 年 01 月 11 日 卫星星座扩容，打开商业航天市场天花板 商业航天事件点评 中游制造/军工 事件： 近日，国际电信联盟（ITU）官网显示，中国提交了新增 20.3 万颗的卫星申请， 此次申报涵盖 14 个卫星星座，其中 CTC-1 和 CTC-2 两个星座各自申请 96,714 颗。 评论： 相对于"GW"星座与千帆星座，本次卫星申请大幅度提升了星座的数量及卫星 的总量，或将有效的提升商业航天整体的市场空间。 商业航天加速了航天产业链的发展。商业航天，是指以市场为主导、具有商业 盈利模式的航天活动。近年来，中国商业航天力量如雨后春笋般涌现，展现出 令人瞩目的实力，为加快发展新质生产力不断注入新的动能，或将可以有效的 带动国内通信、能源、新材料等产业的发展。 海南国际商业航天发射中心发射工位持续增加。根据海南国际商业航天发射中 心党委副书记郭强介绍，一期按照 2 个中型液体工位和 2 个固体小型工位来进 行规划的。中型液体工位每年打 16 发火箭，固体工位一个打几十发火箭。为了 适应现在市场的需要，后面有二期、三期和更大的计划。目前，海南商业航天 发射场二期在文昌开 ...

Domestic Economic Indicators - December PPI exceeded expectations, recording a month-on-month increase of +0.2%, the highest growth rate of the year[1] - January PPI is expected to narrow significantly to around -1.2% year-on-year[1] Overseas Economic Indicators - U.S. unemployment rate fell to 4.4% from 4.6%, with non-farm payrolls adding 50,000 jobs in December, diminishing expectations for a Fed rate cut in January[1][16] - Trump plans to increase the U.S. defense budget by 50% to $1.5 trillion by 2027[1][16] Currency and Asset Market Insights - The central bank emphasized "preventing excessive exchange rate fluctuations," with the probability of the RMB breaking 7 earlier than expected increasing[1] - If the RMB maintains strength, Hong Kong stocks may enter a favorable performance period[1] Monetary Policy and Liquidity - From January 4 to 9, the central bank conducted a net withdrawal of 14,550 billion CNY through reverse repos, with a 7-day reverse repo injection of 1,387 billion CNY[2][17] - The average funding rates for various instruments decreased, with DR001 down 0.4273 basis points to 1.2670%[3][18] Government Debt Financing - Local government debt net financing reached 1176.64 billion CNY, while national debt net financing was 4950 billion CNY, totaling 6126.64 billion CNY[19] - Upcoming planned issuance for local government bonds is 702.01 billion CNY and national bonds is 1670 billion CNY, with a net financing of approximately -3299.39 billion CNY expected[19] Market Performance Overview - A-share market showed strong bullish sentiment with the Shanghai Composite Index rising 3.82%[32] - The Hang Seng Index demonstrated clear signs of bottom rebound, increasing by 2.35%[32]

Quantitative Models and Construction Methods 1. Model Name: DTW Timing Model - **Model Construction Idea**: The DTW timing model is based on a similarity approach, analyzing the similarity between current index trends and historical trends. It selects historical segments with high similarity as references and calculates the weighted average future returns and standard deviations of these segments to generate trading signals [20][22]. - **Model Construction Process**: 1. Use the DTW (Dynamic Time Warping) distance algorithm instead of Euclidean distance to measure similarity, as DTW is better suited for time series problems by addressing sequence misalignment issues [22]. 2. Calculate the weighted average future returns and standard deviations of selected historical segments, where weights are the inverse of the DTW distance [20]. 3. Generate trading signals based on the average future returns and standard deviations [20]. 4. To address the "pathological matching" issue in traditional DTW algorithms, improved DTW algorithms with boundary constraints (e.g., Sakoe-Chiba and Itakura Parallelogram) are applied [24][26][28]. - **Model Evaluation**: The DTW timing model demonstrates stable excess returns in general market conditions but may underperform during periods of sudden macroeconomic policy changes [9]. 2. Model Name: Foreign Capital Timing Model - **Model Construction Idea**: This model leverages information embedded in the price movements of two offshore assets related to A-shares: FTSE China A50 Index Futures (Singapore market) and the Southbound A50 ETF (Hong Kong market) [30]. - **Model Construction Process**: 1. Construct two indicators using FTSE China A50 Index Futures: basis and price divergence [30]. 2. Construct a price divergence indicator using the Southbound A50 ETF [30]. 3. Combine the timing signals from the two assets to form the foreign capital timing signal [30]. - **Model Evaluation**: The model achieves strong performance, with annualized returns of 18.96% (long-short strategy) and 14.19% (long-only strategy) over the full sample period (2014-2024). It also exhibits a high win rate (close to 55%) and a profit-loss ratio exceeding 2.5 [13]. --- Model Backtesting Results 1. DTW Timing Model - **Absolute Return**: 35.52% since November 2022 [9] - **Excess Return (relative to CSI 300)**: 8.60% [9] - **Maximum Drawdown**: 21.32% [9] 2. Foreign Capital Timing Model - **Annualized Return (Long-Short Strategy)**: 18.96% (2014-2024) [13] - **Annualized Return (Long-Only Strategy)**: 14.19% (2014-2024) [13] - **Maximum Drawdown**: 25.69% (Long-Short), 17.27% (Long-Only) [13] - **Win Rate**: Close to 55% [13] - **Profit-Loss Ratio**: Exceeds 2.5 [13] - **Absolute Return (2024)**: 31.33% (Long-Only Strategy) [17] - **Maximum Drawdown (2024)**: 8.23% [17] --- Quantitative Factors and Construction Methods 1. Factor Name: DTW Distance - **Factor Construction Idea**: DTW distance is used as a similarity measure for time series, addressing sequence misalignment issues that arise with traditional Euclidean distance [22]. - **Factor Construction Process**: 1. Compute the DTW distance between the current index trend and historical trends [22]. 2. Use the inverse of the DTW distance as weights to calculate the weighted average future returns and standard deviations of historical segments [20]. 3. Generate trading signals based on these weighted averages [20]. - **Factor Evaluation**: DTW distance is more effective for time series problems compared to Euclidean distance, as it resolves sequence misalignment and improves model performance [22]. 2. Factor Name: Basis and Price Divergence (Foreign Capital Timing Model) - **Factor Construction Idea**: These factors are derived from offshore assets to capture information about A-share market trends [30]. - **Factor Construction Process**: 1. Calculate the basis and price divergence indicators using FTSE China A50 Index Futures [30]. 2. Calculate the price divergence indicator using the Southbound A50 ETF [30]. 3. Combine these indicators to form the foreign capital timing signal [30]. - **Factor Evaluation**: These factors effectively capture offshore market signals and contribute to the strong performance of the foreign capital timing model [13]. --- Factor Backtesting Results 1. DTW Distance - **Absolute Return**: 35.52% since November 2022 [9] - **Excess Return (relative to CSI 300)**: 8.60% [9] - **Maximum Drawdown**: 21.32% [9] 2. Basis and Price Divergence - **Annualized Return (Long-Short Strategy)**: 18.96% (2014-2024) [13] - **Annualized Return (Long-Only Strategy)**: 14.19% (2014-2024) [13] - **Maximum Drawdown**: 25.69% (Long-Short), 17.27% (Long-Only) [13] - **Win Rate**: Close to 55% [13] - **Profit-Loss Ratio**: Exceeds 2.5 [13] - **Absolute Return (2024)**: 31.33% (Long-Only Strategy) [17] - **Maximum Drawdown (2024)**: 8.23% [17]

Investment Rating - The report maintains a "Recommended" rating for the automotive industry, indicating a positive outlook for the sector's fundamentals and expectations for the industry index to outperform the benchmark index [5][28]. Core Insights - The automotive industry experienced an overall increase of 2.7% from January 4 to January 10, 2026, with all secondary segments within the automotive sector also showing positive growth [1][2][9]. - Key developments include GAC Group signing a comprehensive cooperation framework with Huawei, and Geely obtaining an L3 level autonomous driving road test license, indicating advancements in smart driving technologies [1][23]. - The market is witnessing a promotional battle led by luxury brands like Tesla and BMW, with various automakers offering significant discounts and financing options to stimulate sales [20][21]. Market Performance Overview - The Shanghai Composite Index rose by 3.8%, while the Shenzhen Composite Index increased by 5.1%, and the ChiNext Index saw a 3.9% rise during the same period [2][9]. - Within the automotive sector, the automotive services segment led with a weekly increase of 6.0%, while the passenger vehicle segment had the lowest increase at 0.3% [2][9]. Individual Stock Performance - Notable stock performances include JunDa Co., which increased by 29.4%, JinGu Co. by 26.3%, and KaiZhong Co. by 23.3% [3][13]. - Among covered stocks, DaoShi Technology saw a rise of 29.5%, XuSheng Group by 18.0%, and XinQuan Co. by 16.2% [3][15]. Recent Vehicle Launches - Key new vehicle launches include the Xiaopeng P7+ with advanced driving capabilities and the Wuling Xingguang 560, which offers multiple powertrain options [18][19]. Industry News and Policies - The Ministry of Commerce projects over 11.5 million vehicles to be replaced under the old-for-new policy by 2025, with significant sales expected in related sectors [20]. - GAC Group and Huawei's collaboration aims to enhance smart vehicle technologies, while Chery Group targets a sales goal of 3.2 million vehicles for 2026, reflecting a 14.03% increase from 2025 [22][23].