Group 1 - The capital market has been active recently, with brokers conducting research on 440 A-share companies this year, predominantly in the electronics and machinery sectors, while the power equipment and chemical sectors have seen a surge in interest [1] - According to Founder Securities, brokers are still in a "lagging" phase, but ROE is on an upward trend, indicating that sector performance, although delayed, is expected to improve [1] - The capital market is projected to remain robust in 2025, with an average daily stock trading volume of 20.8 trillion yuan, a year-on-year increase of 70.2%, and an average margin balance of 2.08 trillion yuan, up 32.7% year-on-year [1] Group 2 - The 国证证券龙头指数 (399437) has shown a strong increase of 1.98%, with notable gains in constituent stocks such as 财通证券 (6.50%), 兴业证券 (4.95%), and 华泰证券 (3.52%) [1] - The 证券ETF鹏华 (159993) closely tracks the 国证证券龙头指数 and aims to reflect the market performance of quality listed companies in the securities theme [2] - As of December 31, 2025, the top ten weighted stocks in the 国证证券龙头指数 account for 79.13% of the index, including companies like 东方财富, 中信证券, and 华泰证券 [2]

Group 1 - The A-share securities sector experienced a short-term surge on January 26, with notable increases in stock prices [2] - Citic Securities saw a rise of over 7%, while Huatai Securities and Industrial Securities increased by more than 3% [2] - Other companies such as GF Securities and Huaxin Securities also showed significant upward movement [2]

Core Viewpoint - The A-share securities sector experienced a short-term surge, with notable increases in stock prices for several securities firms [1] Group 1: Company Performance - Caitong Securities saw a rise of over 7% in its stock price [1] - Huatai Securities and Industrial Securities both increased by more than 3% [1] - Other firms such as GF Securities and Huaxin Securities also experienced significant stock price increases [1]

Core Viewpoint - Huatai Securities Co., Ltd. announced a plan to list a guaranteed medium-term note program with a total face value increased from $3 billion to $10 billion [1][2] Group 1 - The issuer of the plan is Pioneer Reward Limited, with Huatai Securities providing an unconditional and irrevocable guarantee [1][2] - An application has been submitted to the Hong Kong Stock Exchange for approval to list the program with the increased total face value for a period of 12 months starting from September 10, 2025 [2] - The notes under this program will be issued only to professional investors as defined in the Hong Kong Stock Exchange Listing Rules [2]

Group 1 - Huatai Securities has elected Wang Huaiqing as the new chairman and Zhou Yi continues as CEO, marking a smooth transition in the core management team [1] - Wang Huaiqing, aged 55, has extensive experience in finance and state-owned asset management, which is expected to enhance the company's strategic layout and governance structure [1] - The leadership changes are anticipated to boost investor confidence and solidify Huatai's leading position among top brokerages, contributing positively to market sentiment [1] Group 2 - Huatai Securities Asset Management has completed its executive adjustments, appointing Jiang Xiaoyang as chairman and Zhu Qian as general manager, both of whom are seasoned professionals within the company [2] - The new leadership is expected to ensure strategic continuity and team stability, positively impacting the development of Huatai's asset management business [2] - The smooth transition in management is likely to enhance operational efficiency in the securities sector, driving high-quality industry development [2] Group 3 - Since the beginning of 2026, 76 new funds have been established, raising a total of 71.939 billion yuan, with an average fund size of 9.47 billion yuan [3] - The market has seen a significant increase in fund issuance, with 12 blockbuster funds raising a total of 39.033 billion yuan, accounting for 54.3% of the total fundraising [3] - The strong performance of newly established funds indicates increased investor confidence in the equity market, which may lead to enhanced activity and positive support for overall market sentiment [3]

Core Viewpoint - The A-share market experienced a divergence in capital sentiment last week, with small-cap stocks leading in gains, and industry rotation continuing. The focus is on the elasticity of capital and the direction of future rotations [1] Group 1: Market Dynamics - Since mid-January, the outflow of capital from broad-based ETFs has been relatively high, but there are still inflows from insurance funds and arbitrage demands from investors, indicating ongoing market momentum [1] - The rotation direction may gradually shift from thematic investments to sectors with performance validation, as historically, industries with sustained recovery capabilities during earnings forecast disclosures tend to yield excess returns [1] Group 2: Sector Focus - Current recovery signals are primarily concentrated in price increase chains, high-end manufacturing, and AI-related sectors. Specific attention is recommended for power equipment, basic chemicals, and semiconductor equipment, with a moderate increase in allocation towards cyclical dividends [1]

Group 1 - The macro environment shows easing external pressures from US-Europe relations, with a rebound in the Fed's interest rate cut trades and stable domestic macro data, alongside improvements in real estate high-frequency indicators [1] - Foreign and southbound capital continue to flow in, with public fund positions in Hong Kong stocks dropping to 23% in Q4, significantly reducing potential selling pressure [1] - The sentiment index has returned to a neutral range, with bullish expectations increasing, indicating a continued potential for a rebound in the first quarter [1] Group 2 - Focus on the AI chain (semiconductors, software) and innovative pharmaceuticals, while gradually accumulating quality consumer leaders and overweighting the upstream of the cyclical and power chains [1]

Group 1 - The core viewpoint of the articles highlights the increasing internationalization of Chinese securities firms, with firms like Huatai Securities and GF Securities actively investing in their international subsidiaries to enhance competitiveness in the global market [1][2]. - Huatai Securities plans to increase its investment in its wholly-owned subsidiary, Huatai International Financial Holdings, by up to 9 billion HKD to support overseas business development [1]. - Huatai International has become a key platform for Huatai Securities' international operations, with significant revenue contributions, reporting 3.762 billion HKD in revenue and 1.145 billion HKD in net profit for the first half of 2025 [1]. Group 2 - The internationalization strategy is seen as a crucial approach for Chinese securities firms to expand their profit margins, with several firms, including GF Securities, also announcing substantial capital increases for their overseas subsidiaries [2]. - Analysts suggest that increasing capital for international subsidiaries will enhance the capital strength of Chinese securities firms, improving their competitiveness and market share in the international arena [2]. - The focus of international business development is shifting from mere scale expansion to value cultivation, with firms aiming to provide comprehensive financial services and support for domestic enterprises going global [3].

Investment Rating - The industry investment rating is "Overweight" (maintained) [1] Core Insights - The report indicates a significant improvement in market trading volume and new fund issuance at the beginning of 2026, which is favorable for the fundamentals of financial IT and brokerage sectors. Brokerage firms are expected to continue rapid growth in their brokerage business, while investment banking, asset management, and overseas expansion are likely to enhance the return on equity (ROE) of leading brokerage firms. The insurance sector has also seen a strong start in both individual and bank-insurance channels, with a continued trend of deposit migration, suggesting a positive outlook for the insurance sector in the spring market [4][6]. Summary by Sections Brokerage Sector - Daily average trading volume for stock funds reached 3.44 trillion, down 16% week-on-week; however, the average trading volume since the beginning of 2026 is 3.64 trillion, a 105% increase compared to Q1 2025 [4] - New stock and mixed fund issuance in January 2026 totaled 44.3 billion, a 56% year-on-year increase [4] - The "Public Fund Performance Benchmark Guidelines" was officially released on January 23, 2026, establishing stricter standards for benchmark selection and changes, enhancing performance evaluation and compensation management systems [4] Insurance Sector - The fourth quarter of 2025 saw a stable research value for ordinary life insurance products at 1.89%, slightly down from 1.90% in the previous quarter, indicating a trend towards stability [6] - The individual insurance channel is under pressure due to various factors, but the strong start in 2026 is expected to improve new policy growth, aided by favorable market conditions [6] - The stabilization of long-term interest rates and a favorable equity market are expected to enhance net assets and profitability for insurance companies, with a potential valuation recovery towards 1x PEV for leading firms [6] Recommended Stocks - Recommended stocks include Guangfa Securities, Guotai Junan, Huatai Securities, and China International Capital Corporation H, as well as China Life, China Pacific Insurance, and Ping An Insurance [7]

Quantitative Models and Construction Methods 1. Model Name: A-Share Technical Scoring Model - **Model Construction Idea**: The model aims to fully explore technical information to depict market conditions, breaking down the abstract concept of "market state" into five dimensions: price, volume, volatility, trend, and crowding. It generates a comprehensive score ranging from -1 to +1 based on equal-weighted voting of signals from 10 selected indicators across these dimensions[9][14] - **Model Construction Process**: 1. Select 10 effective market observation indicators across the five dimensions[14] 2. Generate long/short timing signals for each indicator individually 3. Aggregate the signals through equal-weighted voting to form a comprehensive score between -1 and +1[9] - **Model Evaluation**: The model provides a straightforward and timely way for investors to observe and understand the market[9] 2. Model Name: Style Timing Model (Small-Cap Crowding) - **Model Construction Idea**: The model uses a crowding-based trend approach to time large-cap and small-cap styles. Crowding is measured by the difference in momentum and trading volume ratios between small-cap and large-cap indices[3][20] - **Model Construction Process**: 1. Calculate the momentum difference between the Wind Micro-Cap Index and the CSI 300 Index across 10/20/30/40/50/60-day windows 2. Compute the trading volume ratio between the two indices over the same windows 3. Derive crowding scores for small-cap and large-cap styles by averaging the highest and lowest quantiles of the above metrics, respectively 4. Combine the momentum and volume scores to obtain the final crowding score. A score above 90% indicates high small-cap crowding, while below 10% indicates high large-cap crowding[25] - **Model Evaluation**: The model effectively captures the dynamics of style crowding and provides actionable insights for timing decisions[20][25] 3. Model Name: Industry Rotation Model (Genetic Programming) - **Model Construction Idea**: The model applies genetic programming to directly extract factors from industry indices' price, volume, and valuation data, without relying on predefined scoring rules. It uses a dual-objective approach to optimize factor monotonicity and top-group performance[28][32][33] - **Model Construction Process**: 1. Use NSGA-II algorithm to optimize two objectives: |IC| (information coefficient) and NDCG@5 (normalized discounted cumulative gain for top 5 groups) 2. Combine weakly collinear factors using a greedy strategy and variance inflation factor to form industry scores 3. Select the top 5 industries with the highest multi-factor scores for equal-weight allocation, rebalancing weekly[32][34] - **Model Evaluation**: The dual-objective genetic programming approach enhances factor diversity and reduces overfitting risks, making it a robust tool for industry rotation[32][34] 4. Model Name: China Domestic All-Weather Enhanced Portfolio - **Model Construction Idea**: The model adopts a macro-factor risk parity framework, emphasizing risk diversification across underlying macro risk sources rather than asset classes. It actively overweights favorable quadrants based on macro momentum[39][42] - **Model Construction Process**: 1. Divide macro risks into four quadrants based on growth and inflation expectations: growth above/below expectations and inflation above/below expectations 2. Construct sub-portfolios within each quadrant using equal-weighted assets, focusing on downside risk 3. Adjust quadrant risk budgets monthly based on macro momentum indicators, which combine buy-side momentum from asset prices and sell-side momentum from economic forecast surprises[42] - **Model Evaluation**: The strategy effectively integrates macroeconomic insights into portfolio construction, achieving enhanced performance through active allocation adjustments[39][42] --- Model Backtesting Results 1. A-Share Technical Scoring Model - Annualized Return: 20.78% - Annualized Volatility: 17.32% - Maximum Drawdown: -23.74% - Sharpe Ratio: 1.20 - Calmar Ratio: 0.88[15] 2. Style Timing Model (Small-Cap Crowding) - Annualized Return: 28.46% - Maximum Drawdown: -32.05% - Sharpe Ratio: 1.19 - Calmar Ratio: 0.89 - YTD Return: 11.85% - Weekly Return: 5.25%[26] 3. Industry Rotation Model (Genetic Programming) - Annualized Return: 32.92% - Annualized Volatility: 17.43% - Maximum Drawdown: -19.63% - Sharpe Ratio: 1.89 - Calmar Ratio: 1.68 - YTD Return: 6.80% - Weekly Return: 3.37%[31] 4. China Domestic All-Weather Enhanced Portfolio - Annualized Return: 11.93% - Annualized Volatility: 6.20% - Maximum Drawdown: -6.30% - Sharpe Ratio: 1.92 - Calmar Ratio: 1.89 - YTD Return: 3.59% - Weekly Return: 1.54%[43] --- Quantitative Factors and Construction Methods 1. Factor Name: Small-Cap Crowding Factor - **Factor Construction Idea**: Measures the crowding level of small-cap style based on momentum and trading volume differences between small-cap and large-cap indices[20][25] - **Factor Construction Process**: 1. Calculate momentum differences and trading volume ratios for multiple time windows 2. Derive crowding scores by averaging the highest and lowest quantiles of these metrics 3. Combine momentum and volume scores to obtain the final crowding score[25] 2. Factor Name: Industry Rotation Factor (Genetic Programming) - **Factor Construction Idea**: Extracts factors from industry indices using genetic programming, optimizing for monotonicity and top-group performance[32][34] - **Factor Construction Process**: 1. Perform cross-sectional regression of standardized daily trading volume against daily price gaps to obtain residuals (Variable A) 2. Identify the trading day with the highest standardized volume in the past 9 days (Variable B) 3. Conduct time-series regression of Variables A and B over the past 50 days to obtain intercepts (Variable C) 4. Compute the covariance of Variable C and standardized monthly opening prices over the past 45 days[38] --- Factor Backtesting Results 1. Small-Cap Crowding Factor - YTD Return: 11.85% - Weekly Return: 5.25%[26] 2. Industry Rotation Factor (Genetic Programming) - Training Set IC: 0.340 - Factor Weight: 18.7% - YTD Return: 6.80% - Weekly Return: 3.37%[31][38]