Quantitative Models and Construction - **Model Name**: FIFAA (Flexible Indeterminate Factor Asset Allocation) **Model Construction Idea**: Combines quantitative academic rigor with subjective forward-looking flexibility, using historical data (ex-post) and subjective views (ex-ante) to derive asset-factor exposure and optimize portfolio allocation[2][15][74] **Model Construction Process**: 1. **Factor Selection**: Select tradable, low-correlation macroeconomic factors with clear economic logic. Factors include global equities (economic growth), U.S. Treasuries (interest rate/defensive), credit, inflation protection, and currency protection[15][16][20] 2. **Asset-Factor Mapping**: Use LASSO regression to calculate historical beta exposure, then adjust using subjective views derived from professional investor interviews. Subjective single-factor beta is converted into multi-factor beta using matrix transformations[16][35][39] - Formula for historical beta regression: $$y\,=\,X W\,=\,w_{1}x_{1}+\cdots+w_{n}x_{n}$$[32] Loss function for Ridge regression: $$L(w)\,=\,\sum_{i=1}^{n}(y_{i}-\sum w_{j}x_{i j})+\lambda\sum w_{j}^{2}$$[33] Subjective beta transformation: $$\beta_{f}^{*}\,=\,(1\quad F_{f})\,{\binom{\beta_{f}}{\beta_{!f}}}$$[35] $$\beta=F^{-1}\beta^{*}$$[39] 3. **Factor Exposure Optimization**: Optimize factor exposure based on subjective risk/reward judgment or quantitative methods[17] 4. **Portfolio Optimization**: Maximize expected returns while minimizing factor exposure differences. Constraints include absolute exposure differences ≤ 10% of the larger exposure value[44] - Optimization formula: $$m a x(w^{T}r)$$ $$s.\,t.\,w^{T}I\;=\;1$$ $$a b s(w^{T}\beta_{i}-w^{T}\beta_{j})<0.1*m a x(a b s(w^{T}\beta_{i}),a b s(w^{T}\beta_{j}))$$[44] 5. **Rebalancing**: Allow slight deviations in factor exposure to reduce transaction costs and frequency[18] **Model Evaluation**: Provides higher returns and risk-adjusted performance compared to equal-weighted portfolios. Simplified implementation demonstrates practical feasibility[2][74] Model Backtesting Results - **Default Parameters**: - Historical beta optimization: Annualized return 13.63%, annualized volatility 11.47%, max drawdown -18.97%[49][50] - Adjusted beta optimization: Annualized return 15.43%, annualized volatility 16.46%, max drawdown -33.86%[49][50] - Equal-weight portfolio: Annualized return 10.32%, annualized volatility 11.91%, max drawdown -25.27%[49][50] - **Different Adjustment Coefficients**: - Coefficient range (0.1-0.5): Annualized return varies between 15.16%-15.43%, annualized volatility between 15.73%-16.46%, max drawdown between -30.51% to -37.50%[57][59] - **Different Expected Returns**: - Neutral expected return scenarios (5%, 10%, 15%): Annualized return ranges from 13.63%-15.90%, annualized volatility from 11.47%-16.45%, max drawdown from -18.97% to -36.67%[69][70][71][72] Quantitative Factors and Construction - **Factor Name**: Macroeconomic Factors (Economic Growth, Interest Rate, Inflation) **Factor Construction Idea**: Represent macroeconomic trends using tradable indices to ensure simplicity and reduce calculation errors[15][20][30] **Factor Construction Process**: - Economic growth: Represented by stock indices (e.g., Wind All A Index, S&P 500)[30] - Interest rate: Represented by bond indices (e.g., China Bond Treasury Wealth Index)[30] - Inflation: Composite of commodity indices (e.g., Nanhua Industrial, Agricultural, Energy, and Black Metal indices)[20][30] **Factor Evaluation**: Tradable and low-correlation factors ensure practical applicability and reduce subjective judgment uncertainty[15][16][20] Factor Backtesting Results - **Macroeconomic Factor Correlation Matrix**: - Wind All A vs. S&P 500: 0.15 - Wind All A vs. China Bond Treasury: -0.12 - Wind All A vs. Commodity Composite: 0.30[28][30] - **Factor Performance**: - Economic growth factor (Wind All A): Annualized return 13.63%-15.43% depending on optimization method[49][50][69] - Inflation factor (Commodity Composite): Adjusted beta optimization shows higher returns during inflationary periods[49][50][69]

（责任编辑：徐自立） 中国经济网北京11月20日讯 东北证券(000686.SZ)今日股价下跌，截至收盘报9.59元，跌幅 8.05%。今日，证券板块跌0.42%，东北证券为该板块跌幅最大的上市公司。 ...

证券之星消息，11月20日证券板块较上一交易日下跌0.47%，东北证券领跌。当日上证指数报收于 3931.05，下跌0.4%。深证成指报收于12980.82，下跌0.76%。证券板块个股涨跌见下表： | 代码 | 名称 | 主力净流入(元) | 主力净占比 游资净流入 (元) | | 游资净占比 散户净流入(元) | | 散户净占比 | | --- | --- | --- | --- | --- | --- | --- | --- | | 600958 | 东方证券 | 1.12亿 | 5.87% | -1.55 Z | -8.07% | 4213.68万 | 2.20% | | 601136 | 首创证券 | 5081.34万 | 4.17% | -5623.50万 | -4.61% | 542.16万 | 0.44% | | 601881 | 中国银河 | 4412.62万 | 3.89% | 4741.91万 | 4.18% | -9154.53万 | -8.06% | | 601901 | 方正证券 | 4170.46万 | 4.27% | -3837.52万 | -3.93% | -332.93万 ...

Core Points - The case of Lu Xuan highlights the issue of securities professionals engaging in illegal trading activities, despite regulations prohibiting such actions [1][2] - Lu Xuan was penalized for using her mother's accounts to conduct stock trading over nearly ten years, with a total trading amount of 27.73 million yuan and a profit of only 181,300 yuan, reflecting an annualized return of less than 2% [1] - The regulatory authorities demonstrated a zero-tolerance approach to violations of the Securities Law, emphasizing the importance of maintaining market fairness [2] Summary by Sections Regulatory Actions - Lu Xuan was fined 180,000 yuan and had her illegal gains of 181,300 yuan confiscated, as per the Securities Law [2] - The case serves as a warning to industry professionals about the consequences of violating trading regulations [2] Industry Implications - The incident underscores the need for strict adherence to professional conduct among securities personnel, as they possess information advantages that necessitate restrictions on trading [2] - Despite the potential for information advantages, Lu Xuan's trading results indicate that such advantages did not translate into significant profits [2]

Core Points - Yingjian Technology (盈建科) is currently trading at 29.61 yuan, reflecting a decline of 5.10% and is in a state of breaking its initial public offering price [1] - The company was listed on the Shenzhen Stock Exchange's ChiNext board on January 20, 2021, with an initial issuance of 14.13 million shares at a price of 56.96 yuan per share [1] - On its first trading day, the stock reached a peak price of 190.00 yuan, marking the highest price since its listing [1] - The total funds raised from the initial public offering amounted to 804.84 million yuan, with a net amount of 737.36 million yuan after deducting issuance costs [1] - The final net fundraising amount exceeded the original plan by 458 million yuan [1] - The company planned to use the raised funds for various projects, including the development of a Building Information Modeling (BIM) software platform, bridge design software, a technology research center, and the expansion of its marketing and service network [1] - The issuance costs for the initial public offering were 67.48 million yuan, which included an underwriting and sponsorship fee of 47.24 million yuan [1] Dividend Distribution - In the annual equity distribution plan for 2021, the company announced a cash dividend of 8 yuan for every 10 shares held, along with a capital reserve conversion of 4 additional shares for every 10 shares held [2]

Core Viewpoint - Northeast Securities initiates coverage of Guangdong-Hong Kong Bay Holdings (01396.HK) with a "Buy" rating, highlighting the company's strategic shift towards becoming a digital ecosystem operator through the acquisition of TianDun Data, a leading computing power enterprise [1] Group 1: Company Overview - Guangdong-Hong Kong Bay Holdings was listed on the Hong Kong Stock Exchange on October 31, 2013, and emphasizes long-termism while strengthening its industrial foundation and enhancing technological empowerment [1] - The company plans to implement a dual-driven business development strategy focusing on infrastructure and AI following the acquisition of TianDun Data on October 23, 2025 [1] Group 2: Strategic Acquisition - The acquisition of TianDun Data aligns with the company's capabilities in urban development, transforming idle factories and land resources into high-performance intelligent computing centers and AI computing infrastructure [1] - This strategic move is expected to fundamentally change the profitability logic of traditional industry operations [1] Group 3: Growth Potential - The integration of high-value B-end resources from major cloud service providers and leading AI companies into TianDun Data's client base opens new growth avenues for Guangdong-Hong Kong Bay Holdings [1] - The acquisition is anticipated to reconstruct capital logic, creating a dual-driven model of "industrial operation asset securitization + computing power operation revenue," which will reshape the company's valuation [1]

Core Insights - Zhejiang Apac Mechatronics Co., Ltd. (referred to as "the company") held a research meeting with nine institutions, discussing capacity planning, EMB product progress, corner module solutions, and gross margin changes, indicating that corner module products have disrupted traditional steering modes, laying the foundation for intelligent driving [1][5]. Group 1: Capacity and Production - The company maintains a high capacity utilization rate, with production directly linked to vehicle sales. It plans to adjust production lines and expand capacity based on market demand for specific projects [3]. - The company has completed technical reserves for its Electronic Mechanical Brake (EMB) products but has not yet entered mass production. The market launch date will depend on customer project timelines [4]. Group 2: Product Innovation - The corner module solution integrates multiple systems, including wheel hub motors, EMB, steering systems, active suspension, and chassis domain controllers, enabling independent control of vehicle systems and significantly expanding application scenarios for intelligent driving [5]. Group 3: Financial Performance - The company reported an increase in gross margin, driven by two main factors: growth in domestic vehicle sales and new international projects, along with ongoing product structure optimization and internal cost reduction efforts [6]. - To address the annual price reduction pressures faced by vehicle manufacturers, the company plans to optimize product structure and enhance internal management efficiency [7]. Group 4: Market Position and Strategy - The company emphasizes its advantages as a domestic leader in the automotive brake system industry, including customized development for specific vehicle models, higher cost-performance ratio, and faster service response [9]. - There is a growing trend among domestic and foreign vehicle manufacturers to increase local procurement, presenting favorable development opportunities for domestic component manufacturers [10].

Group 1 - The core viewpoint of the news is that Asia-Pacific Holdings (SZ 002284) has announced an investor research meeting scheduled for November 17, 2025, where the company's vice president and board secretary will participate and address investor inquiries [1] - For the first half of 2025, the company's revenue composition is entirely from automotive parts, with a 100.0% share [1] - As of the report date, Asia-Pacific Holdings has a market capitalization of 9 billion yuan [2]

Core Viewpoint - Northeast Securities initiates a "Buy" rating for Guangdong-Hong Kong Bay Holdings (01396), highlighting its successful entry into the AI computing sector through acquisitions, marking a strategic upgrade from a traditional real estate developer to a "digital ecosystem operator" [1] Group 1: Strategic Transformation - The company is positioned as a new type of "urban-rural ecological service provider" deeply rooted in the Guangdong-Hong Kong-Macao Greater Bay Area, focusing on residential and urban renewal projects [1] - The strategic transformation from a traditional real estate developer to an "urban-rural ecological service provider" has been ongoing, with a significant acquisition planned for October 23, 2025, to convert idle factory and land resources into high-performance computing centers [1] Group 2: Major Asset Acquisition - On October 23, the company announced the completion of the acquisition of Wisdom Knight Holdings Limited for a total price of HKD 977 million, which controls Shenzhen Tiandun Data Technology Co., Ltd., a leading operator in AI computing and green energy computing services in China [2] Group 3: Business Model and Financial Health - The traditional business has become a driver for growth, with the company completing a USD 440 million debt-to-equity swap on May 7, 2025, significantly reducing its interest-bearing debt ratio from 45% to 7% [3] - The dual business model of Tiandun Data, focusing on "multi-source computing power services + AIDC construction operations," has been commercially validated, enhancing operational efficiency and profitability [3] Group 4: New Growth Opportunities - The "green energy computing" model developed by Tiandun Data aligns perfectly with the company's urban development capabilities, transforming idle resources into high-performance computing centers and fundamentally changing the profitability logic of traditional industries [4] - The influx of high-value B-end resources from major cloud service providers and leading AI companies opens up new growth avenues for the company [4] - The company aims to establish a diversified income structure through AI computing services, energy management revenues, and computing space operation income, significantly enhancing its risk resistance and profitability resilience [4] Group 5: Profit Forecast and Investment Recommendation - The company is projected to achieve net profits attributable to shareholders of RMB 718 million, RMB 579 million, and RMB 789 million for 2025-2027, reflecting year-on-year growth rates of +139.13%, -19.41%, and +36.41%, respectively [5] - Corresponding price-to-earnings ratios are expected to be 9x, 11x, and 8x, with a first-time coverage and a "Buy" rating recommended [5]

Core Viewpoint - Northeast Securities has initiated a "buy" rating for Guangdong-Hong Kong-Macau Holdings (01396), highlighting its successful entry into the AI computing sector through acquisitions, marking a strategic upgrade from a traditional real estate developer to a "digital ecosystem operator" [1] Group 1: Strategic Transformation - The company is positioned as a new type of "urban and industrial ecological service provider" deeply rooted in the Guangdong-Hong Kong-Macau Greater Bay Area, focusing on residential and urban renewal projects [1] - The strategic transformation from a traditional real estate developer to an "urban and industrial ecological service provider" has been ongoing, with a significant acquisition planned for October 23, 2025, to convert idle factory and land resources into high-performance computing centers [1][2] Group 2: Major Acquisition - On October 23, the company announced the completion of its acquisition of Wisdom Knight Holdings Limited for a total price of HKD 977 million, which controls Shenzhen Tiandun Data Technology Co., Ltd., a leading operator in AI computing and green energy computing services in China [2] Group 3: Business Model and Financial Health - The traditional business has become a driver for growth, with the company achieving a 98.33% approval rate for a USD 440 million debt-to-equity swap, significantly reducing its interest-bearing debt ratio from 45% to 7% [3] - The dual business model of Tiandun Data, focusing on "multi-source computing power services + AIDC construction operations," has been commercially validated, enhancing operational efficiency and profitability [3] Group 4: New Growth Opportunities - The "green energy computing" model developed by Tiandun Data aligns perfectly with the company's urban development capabilities, transforming idle resources into high-performance computing centers and fundamentally changing the profitability logic of traditional industries [4] - The influx of high-value B-end resources from major cloud service providers and leading AI companies opens up new growth avenues for the company, enhancing its revenue structure and resilience against risks [4] Group 5: Profit Forecast and Investment Recommendation - The company is projected to achieve net profits attributable to shareholders of RMB 718 million, RMB 579 million, and RMB 789 million for 2025-2027, reflecting year-on-year growth rates of +139.13%, -19.41%, and +36.41%, respectively, with corresponding P/E ratios of 9x, 11x, and 8x [5]