Group 1 - The announcement states that from August 11, 2025, Guotai Haitong Securities will begin selling certain funds managed by the company [1] - The applicable fund range is subject to compliance with the fund contract, prospectus, and related business announcements [1][4] - The announcement includes a list of various sales institutions that will also start selling the company's funds from the same date [5][6][7] Group 2 - Investors can consult details through the websites and customer service numbers provided for each sales institution [4][5][6][7] - The company emphasizes that the specific dates, times, processes, and any fee discount activities for fund sales will be determined by the sales institutions [1][4]

Core Insights - The new policy for technology innovation bonds has led to a significant issuance of 883.16 billion yuan in just three months, with financial institutions accounting for nearly 36% of this total [1][2] - The issuance of technology innovation bonds has expanded to include more small and private enterprises, alongside the traditional dominance of central and state-owned enterprises [1][2] - The average coupon rate for newly issued technology innovation bonds is 1.9282%, with some bonds having rates as low as 0.01% [1][3] Issuance Details - From May 7 to August 10, a total of 700 technology innovation bonds were issued, amounting to 883.16 billion yuan, compared to 197 bonds totaling 208.11 billion yuan in the same period last year, indicating a significant policy impact [1][2] - Financial institutions have issued 314.27 billion yuan of the total, with banks leading at 230.3 billion yuan across 32 banks, including major players like Agricultural Bank of China and Industrial and Commercial Bank of China [2] - Securities companies have collectively issued 54.1 billion yuan, with the largest issuers being China Merchants Securities and CITIC Securities [2] Characteristics of New Bonds - The newly issued technology innovation bonds predominantly have longer maturities, with 76.23% of the total issuance being bonds with maturities of three years or more [3] - The majority of the bonds were issued by central and local state-owned enterprises, with 203 bonds from central SOEs and 369 from local SOEs, while private enterprises issued 94 bonds [3]

Core Viewpoint - The new policy for technology innovation bonds (科创债) has led to a significant increase in issuance, with a total of 883.16 billion yuan in new bonds over the past three months, indicating a strong market response to regulatory support [1][2]. Group 1: Issuance Scale and Participants - The total issuance scale of technology innovation bonds reached 883.16 billion yuan, with financial institutions accounting for nearly 36% of this amount [1][2]. - Among the financial institutions, banks led the issuance with 230.3 billion yuan, followed by 38 securities companies that collectively issued 54.1 billion yuan [2]. - The participation of small and medium-sized institutions and private enterprises has increased, with various smaller banks and private equity firms also issuing technology innovation bonds [2]. Group 2: Characteristics of New Bonds - The average coupon rate for newly issued technology innovation bonds was 1.9282%, which is notably low compared to other credit bonds of similar ratings [3]. - A significant portion of the new bonds has a maturity of over three years, with 76.23% of the total issuance (673.22 billion yuan) falling into this category [3]. - The majority of the issuers are central and local state-owned enterprises, with 203 bonds issued by central state-owned enterprises and 369 by local state-owned enterprises [3].

Quantitative Models and Construction Methods 1. Model Name: Volume Timing Signal - **Model Construction Idea**: The core idea is that "the decline in a shrinking volume market is significantly greater than the rise in a shrinking volume market, so avoiding shrinking volume signals can achieve higher trading odds"[3][22][24] - **Model Construction Process**: 1. Calculate the rolling 60-day average and standard deviation of the turnover and turnover rate of the index or market[23] 2. Standardize the daily turnover data: - If the turnover is within ±2 standard deviations, map the score to -1~+1 - If the turnover exceeds ±2 standard deviations, assign a score of +1/-1 3. Combine the scores of turnover and turnover rate equally[23] 4. Generate signals based on the combined score: - Method 1: Go long if the score > 0, stay out if the score < 0 - Method 2: Use the rolling 5-year or 3-year percentile of the score; go long if above the 50th percentile, stay out if below[23] 5. The report adopts the simpler method of directly judging whether the score is greater than 0[23] - **Model Evaluation**: The model is not a high-win-rate strategy but achieves relatively high odds by avoiding significant market adjustments during shrinking volume periods[24] 2. Model Name: Growth-Value Style Rotation Model - **Model Construction Idea**: The model evaluates the relative attractiveness of growth and value styles based on macroeconomic cycles, valuation differences, and market sentiment[52][54] - **Model Construction Process**: 1. **Fundamentals**: - Growth is favored when the profit cycle slope is steep, interest rate levels are low, and the credit cycle is rising - Value is favored under the opposite conditions[52] 2. **Valuation**: - Growth is favored when the PE and PB valuation differences between growth and value are in the lower percentiles and mean-reverting upward[52] 3. **Sentiment**: - Growth is favored when turnover and volatility differences between growth and value are low[52] 4. Combine signals from fundamentals, valuation, and sentiment to determine the allocation between growth and value[52] - **Model Evaluation**: The model has shown significant improvement over the benchmark in terms of annualized returns and risk-adjusted performance[53][55] 3. Model Name: Small-Cap vs. Large-Cap Style Rotation Model - **Model Construction Idea**: The model evaluates the relative attractiveness of small-cap and large-cap styles based on macroeconomic cycles, valuation differences, and market sentiment[56][58] - **Model Construction Process**: 1. **Fundamentals**: - Small-cap is favored when the profit cycle slope is steep, interest rate levels are low, and the credit cycle is rising - Large-cap is favored under the opposite conditions[56] 2. **Valuation**: - Large-cap is favored when the PE and PB valuation differences between small-cap and large-cap are in the higher percentiles and mean-reverting downward[56] 3. **Sentiment**: - Small-cap is favored when turnover differences are high - Large-cap is favored when volatility differences are mean-reverting downward[56] 4. Combine signals from fundamentals, valuation, and sentiment to determine the allocation between small-cap and large-cap[56] - **Model Evaluation**: The model has shown significant improvement over the benchmark in terms of annualized returns and risk-adjusted performance[57][60] 4. Model Name: Four-Style Rotation Model - **Model Construction Idea**: Combines the conclusions of the growth-value and small-cap-large-cap rotation models to allocate across four styles: small-cap growth, small-cap value, large-cap growth, and large-cap value[61][63] - **Model Construction Process**: 1. Use the growth-value model to determine the allocation between growth and value 2. Use the small-cap-large-cap model to determine the allocation between small-cap and large-cap 3. Combine the two models to allocate across the four styles[61] - **Model Evaluation**: The model has shown significant improvement over the benchmark in terms of annualized returns and risk-adjusted performance, with consistent outperformance in most years[61][63] --- Model Backtest Results 1. Volume Timing Signal - **Win Rate**: 47.34%[24] - **Odds**: 1.75[24] - **Annualized Excess Return**: 6.87% (based on next-day open price)[34] - **Maximum Drawdown**: 31.40%[34] - **Return-to-Drawdown Ratio**: 0.4634[34] 2. Growth-Value Style Rotation Model - **Annualized Return**: 11.76%[55] - **Annualized Volatility**: 20.77%[55] - **Maximum Drawdown**: 43.07%[55] - **Sharpe Ratio**: 0.5438[55] - **Return-to-Drawdown Ratio**: 0.2731[55] 3. Small-Cap vs. Large-Cap Style Rotation Model - **Annualized Return**: 12.45%[60] - **Annualized Volatility**: 22.65%[60] - **Maximum Drawdown**: 50.65%[60] - **Sharpe Ratio**: 0.5441[60] - **Return-to-Drawdown Ratio**: 0.2459[60] 4. Four-Style Rotation Model - **Annualized Return**: 13.37%[63] - **Annualized Volatility**: 21.51%[63] - **Maximum Drawdown**: 47.91%[63] - **Sharpe Ratio**: 0.5988[63] - **Return-to-Drawdown Ratio**: 0.2790[63]

Core Viewpoint - Guangdong Provincial Academy of Building Research Group Co., Ltd. (hereinafter referred to as "Guangdong Jian Ke") is preparing for its initial public offering (IPO) on the ChiNext board, with a focus on providing high-tech services in the construction engineering field, particularly in inspection and testing [1][2]. Group 1: Company Overview - The registered capital of Guangdong Jian Ke is 31.39 million yuan, and it was established on December 25, 2013, with its shares incorporated on December 16, 2014 [1]. - The company is recognized as a large-scale construction technology service provider in Guangdong Province and has received multiple national honors, including "National High-tech Enterprise" and "National Model Enterprise for Scientific and Technological Reform" [2][3]. Group 2: Main Business and Services - Guangdong Jian Ke's primary business involves inspection and testing technology services in the construction engineering sector, which is a key area supported by the national government [3][4]. - The company has developed over 4,100 recognized testing standards and holds various qualifications, including comprehensive Class A qualifications for highway engineering and all five categories of Class A qualifications for water conservancy engineering [3][4]. Group 3: Technological Capabilities - The company emphasizes technological research and development, having established multiple provincial and national-level innovation platforms, including the only national green building quality inspection and testing center in South China [5][6]. - Guangdong Jian Ke has participated in over 20 national scientific and technological projects and has received 89 national and provincial-level scientific and technological awards [6][7]. Group 4: Industry Impact and Recognition - The company has provided inspection and testing services for major projects such as the Hong Kong-Zhuhai-Macao Bridge and Guangzhou Baiyun International Airport, contributing to significant economic and social benefits [6][7]. - Guangdong Jian Ke has been awarded titles such as "National AAA Credit Enterprise in the Construction Industry" and "National Green Building Pioneer Award," reflecting its strong reputation in the industry [6][7].

Core Viewpoint - The stability of information systems in the securities industry is essential for ensuring the safe operation of financial markets, prompting the China Securities Association to seek industry feedback on the "Stability Assurance System Standard for the Securities Industry" [1][2]. Group 1: Background and Purpose - The initiative aims to integrate best practices from securities firms to create a practical stability assurance framework, promoting the digital and standardized development of technical capabilities across the industry [1]. - The project for drafting the standard began in November 2023, with participation from 14 securities firms, including major players like GF Securities and CITIC Securities [1]. Group 2: Current Challenges - There are four main challenges identified: 1. Lack of resilience design in system development, leading to high operational risk prevention costs due to insufficient monitoring and automation capabilities [2]. 2. Predominantly reactive risk perception during operations, lacking proactive data-driven risk identification capabilities [2]. 3. Emergency response relies heavily on individual expert experience, lacking data-driven human-machine collaborative capabilities [2]. 4. Insufficient depth of intelligent technology application, resulting in a gap between abnormal response efficiency and real-time business requirements [2]. Group 3: Proposed Framework - The "Stability Assurance System Standard" proposes a "three-in-one" framework for stability assurance, focusing on organizational, institutional, and process guarantees [3]. - Organizational guarantees include defining the structure, personnel competency requirements, and management objectives [3]. - Institutional guarantees encompass regulations, technical support, operational procedures, and timelines to ensure management requirements are actionable and traceable [3]. - Process guarantees focus on ten core processes related to stability management, including monitoring, alerting, and fault management, with mechanisms for evaluation and key activities [3]. - The standard emphasizes a shift towards proactive operations management to meet non-functional requirements like resilience and maintainability, utilizing digital methods to enhance defense capabilities [3].

Quantitative Models and Construction Methods DTW Timing Model - **Model Name**: DTW Timing Model - **Model Construction Idea**: The model is based on the principle of similarity and the DTW algorithm, focusing on price and volume timing[1][5][14] - **Model Construction Process**: - The model examines the similarity between current index trends and historical trends, selecting several historical segments with high similarity as references[25] - It calculates the weighted average future price change and weighted standard deviation of the selected historical segments (weights are the inverse of the distance)[25] - Based on the average future price change and standard deviation, trading signals are generated[25] - The model uses the DTW distance algorithm instead of the Euclidean distance for similarity measurement, as DTW distance can better handle time series mismatches[27] - Improved DTW algorithms such as Sakoe-Chiba and Itakura Parallelogram are introduced to overcome the "over-bending" issue in traditional DTW algorithms[29][30][35] - **Model Evaluation**: The model has shown stable excess returns in general market conditions, although it faced some drawdowns during periods of sudden macroeconomic policy changes[16] Foreign Capital Timing Model - **Model Name**: Foreign Capital Timing Model - **Model Construction Idea**: The model is based on the divergence between foreign and domestic related assets[1][14] - **Model Construction Process**: - The model uses two foreign-listed assets related to A-shares: FTSE China A50 Index Futures (Singapore market) and Southern A50 ETF (Hong Kong market)[34] - It constructs two indicators from FTSE China A50 Index Futures: premium and price divergence, forming the FTSE China A50 Index Futures timing signal[34] - It constructs a price divergence indicator from Southern A50 ETF, forming the Southern A50 ETF timing signal[34] - The timing signals from both assets are combined to form the foreign capital timing signal[34] - **Model Evaluation**: The model has shown good performance with high annualized returns and low maximum drawdowns[20][23] Model Backtest Results DTW Timing Model - **Absolute Return**: 25.79% since November 2022[5][16] - **Excess Return**: 16.83% relative to CSI 300[5][16] - **Maximum Drawdown**: 21.32%[5][16] - **Absolute Return (2024)**: 23.98% on CSI 300[18] - **Excess Return (2024)**: 2.76%[18] - **Maximum Drawdown (2024)**: 21.36%[18] - **Win Rate (2024)**: 53.85%[18] - **Profit-Loss Ratio (2024)**: 2.93[18] Foreign Capital Timing Model - **Absolute Return (2024)**: 29.11% for long strategy[5][23] - **Maximum Drawdown (2024)**: 8.32% for long strategy[5][23] - **Annualized Return (2014-2024)**: 18.96% for long-short strategy, 14.19% for long strategy[20] - **Maximum Drawdown (2014-2024)**: 25.69% for long-short strategy, 17.27% for long strategy[20] - **Daily Win Rate (2014-2024)**: Nearly 55%[20] - **Profit-Loss Ratio (2014-2024)**: Both exceed 2.5[20]

Core Viewpoint - The recent internal conflict at Jingqi Investment has escalated, involving allegations of financial misconduct and mismanagement, with the company’s founder and fund manager Fan Siqi at the center of the controversy [2][3][4]. Group 1: Company Operations and Allegations - Jingqi Investment's basic account experienced a significant abnormal fund transfer on July 2, which has severely impacted the company's financial operations [3]. - The company claims that there have been illegal uses of forged corporate seals and unauthorized actions regarding fund establishment and liquidation, implicating its custodian, China Merchants Securities, for failing to fulfill its due diligence obligations [4]. - Jingqi Investment has filed formal complaints with the China Securities Regulatory Commission and the Asset Management Association of China regarding these allegations [4]. Group 2: Management Disputes - The company is currently undergoing a change in its legal representative, with Fan Siqi allegedly using his authority to alter the management of the company's WeChat account during this transition [6]. - There are conflicting narratives between the founders, with Fan Siqi asserting that he was unfairly removed from his positions and that his actions were in defense of the company [5][6]. - The other founder, Tang Jingren, claims that Fan Siqi has not been involved in the company's daily operations for nearly three years and has been living in Japan, which has contributed to the management issues [7][8]. Group 3: Financial Management and Structure - Jingqi Investment was established on March 9, 2015, and currently manages between 1 billion to 2 billion yuan, with 56 funds under management [5]. - The company has faced scrutiny over its operational practices, particularly regarding the management of its funds and the legitimacy of its financial transactions [4][5].

Core Viewpoint - The recent internal conflict at the well-known quantitative private equity firm Jingqi Investment has escalated, leading to risk warning announcements and account irregularities, with招商证券 being implicated in the turmoil [1] Group 1: Internal Conflict - Jingqi Investment's founder and fund manager Fan Siqi has issued statements regarding significant abnormal transfers from the company's main account and allegations of illegal activities such as forgery of corporate seals and unauthorized fund establishment and liquidation [1] - Another founder, Tang Jingren, stated that the company is currently undergoing a change in legal representative, and Fan Siqi has misused his authority to alter the management of the company's WeChat account [1] - Fan Siqi's actions are reportedly aimed at pressuring other shareholders due to differing management philosophies, including maliciously liquidating company fund products and misplacing company seals [1] Group 2: Involvement of 招商证券 - 招商证券 has been identified as the custodian for three of Jingqi Investment's products, which are not involved in trading at the firm, and all product establishment and operation matters have been confirmed as compliant with legal regulations [1] - A representative from 招商证券 clarified that there are no violations of fund laws and regulations concerning their custodial responsibilities [1]

Core Viewpoint - The internal conflict within the well-known quantitative private equity firm Jingqi Investment has escalated, involving allegations of financial misconduct and mismanagement by its founders, particularly concerning the handling of company accounts and legal authority [1][2][4]. Group 1: Internal Conflict and Allegations - Jingqi Investment has issued multiple risk warning announcements regarding significant abnormal fund transfers from its main account, which have severely impacted its financial operations [2][3]. - Founder Fan Siqi has been accused of unauthorized actions, including the illegal use of the company seal and signatures to establish and liquidate funds without proper authorization [1][2][3]. - The company is currently undergoing a change in its legal representative, which has led to disputes over control and management rights between the founders [6][7]. Group 2: Company Operations and Management - Jingqi Investment was established on March 9, 2015, with a management scale between 1 billion and 2 billion yuan, overseeing 56 funds [4]. - The firm has faced scrutiny regarding its compliance with fund regulations, particularly concerning the Jingqi Tiangong Jupei Exclusive No. 1 Private Securities Investment Fund, which allegedly operated without proper authorization [3][4]. - The company has reported that its main account operations have been frozen online, but offline transactions can still be conducted under strict conditions [2][3]. Group 3: Stakeholder Responses - The other founder, Tang Jingren, has publicly stated that Fan Siqi's actions are intended to pressure other shareholders and disrupt the company's operations [6][7]. - Tang Jingren and another shareholder have issued a statement to investors regarding the removal of Fan Siqi from his positions, indicating ongoing legal processes to formalize this change [6][7]. - Fan Siqi has claimed that he has been sidelined from company operations and has not agreed to the current business direction, which he believes lacks transparency [6][7].