Investment Rating - The report maintains a "Buy" rating for the company [1] Core Views - The company has secured significant orders, indicating the initial formation of its business model, which is set to disrupt traditional paradigms in drug discovery [7] - The collaboration with DoveTree LLC, which includes substantial upfront payments and potential milestone payments, highlights the value of the company's AI and robotics technology in drug discovery [7] - The endorsement from a renowned Harvard professor suggests promising future growth for the company [7] - The company is identified as a rare player in the AI for Science sector, with its business model beginning to take shape, paving the way for future commercial orders and rapid revenue growth [7] - The financial forecasts have been revised upwards due to the unexpected scale of the collaboration, with projected revenues for 2025-2027 being 5.52 billion, 9.24 billion, and 15.03 billion respectively [7] Financial Projections - Total revenue is expected to grow from 266.43 million in 2024 to 1,502.54 million by 2027, reflecting a compound annual growth rate of 62.62% [1] - The company is projected to achieve a net profit of 62.87 million by 2027, after losses in the preceding years [1] - The earnings per share (EPS) is expected to improve from -0.38 in 2024 to 0.02 in 2027 [1] - The price-to-earnings (P/E) ratio is projected to shift from -17.48 in 2024 to 421.67 in 2027, indicating a significant change in valuation as the company approaches profitability [1]

- The "Information Distribution Uniformity" (UID) factor is introduced as part of the "volatility stock selection factor" series, aiming to improve traditional volatility factors by leveraging high-frequency minute-level data to construct a more effective stock selection factor[6][7][10] - The construction process of the UID factor involves calculating daily high-frequency volatility using minute-level stock data and then deriving the UID factor to measure the uniformity of information distribution. This factor is designed to outperform traditional volatility factors in stock selection[6][10] - The formula for constructing the UID factor is not explicitly provided in the report, but the methodology emphasizes the use of high-frequency data and the removal of market style and industry interference to ensure the purity of the factor[6][10] - The UID factor demonstrates strong performance metrics in backtesting, with an annualized return of 26.53%, annualized volatility of 9.92%, an information ratio (IR) of 2.68, a monthly win rate of 79.14%, and a maximum monthly drawdown of 6.05% over the period from January 2014 to July 2025[7][10] - In July 2025, the UID factor's 10-group long portfolio achieved a return of 0.61%, the short portfolio achieved a return of 0.44%, and the long-short hedged portfolio achieved a return of 0.17%[10]

- Factor Name: Turnover Distribution Uniformity (UTD) Factor[1][6] - Factor Construction Idea: The UTD factor is constructed based on minute-level trading volume data to improve the traditional turnover factor by reducing the misjudgment rate of stock samples and enhancing stock selection performance[1][6] - Factor Construction Process: 1. Collect minute-level trading volume data for individual stocks[1][6] 2. Calculate the turnover distribution uniformity for each stock[1][6] 3. Construct the UTD factor by evaluating the uniformity of turnover distribution[1][6] - Factor Evaluation: The UTD factor significantly reduces the misjudgment rate of stock samples and performs better in stock selection compared to traditional factors[1][6] Factor Backtesting Results - UTD Factor, Annualized Return: 19.96%[1][6][11] - UTD Factor, Annualized Volatility: 7.44%[1][6][11] - UTD Factor, Information Ratio (IR): 2.68[1][6][11] - UTD Factor, Monthly Win Rate: 76.98%[1][6][11] - UTD Factor, Maximum Monthly Drawdown: 5.51%[1][6][11] - UTD Factor, July 2025 Long Portfolio Return: 0.81%[1][10] - UTD Factor, July 2025 Short Portfolio Return: 0.25%[1][10] - UTD Factor, July 2025 Long-Short Portfolio Return: 0.56%[1][10]

Quantitative Factors and Construction Factor Name: Stability of Turnover Rate (STR) - **Factor Construction Idea**: The STR factor is designed to evaluate the stability of daily turnover rates. It aims to identify stocks with stable turnover rates, as opposed to focusing solely on low or high turnover rates. This approach addresses the limitations of traditional turnover rate factors, which may misjudge stocks with high turnover but significant future returns [1][8]. - **Factor Construction Process**: - The STR factor is constructed using daily turnover rate data. - The stability of turnover rates is calculated, inspired by the Uniformity of Turnover Rate Distribution (UTD) factor, which measures turnover rate volatility at the minute level. - The STR factor is then adjusted to remove the influence of common market styles and industry effects, ensuring a "pure" factor signal [8]. - **Factor Evaluation**: The STR factor demonstrates strong stock selection capabilities, even after controlling for market and industry influences. It is considered an effective and straightforward factor [6][8]. Traditional Turnover Rate Factor (Turn20) - **Factor Construction Idea**: The Turn20 factor calculates the average daily turnover rate over the past 20 trading days. It assumes that stocks with lower turnover rates are more likely to outperform in the future, while those with higher turnover rates are more likely to underperform [6][7]. - **Factor Construction Process**: - At the end of each month, the daily turnover rates of all stocks over the past 20 trading days are averaged. - The resulting values are neutralized for market capitalization to eliminate size effects [6]. - **Factor Evaluation**: While the Turn20 factor has historically performed well, its logic has limitations. Specifically, stocks with high turnover rates exhibit significant variability in future returns, leading to potential misjudgments of high-performing stocks within this group [7]. --- Backtesting Results of Factors STR Factor - **Annualized Return**: 40.75% [9][10] - **Annualized Volatility**: 14.44% [9][10] - **Information Ratio (IR)**: 2.82 [9][10] - **Monthly Win Rate**: 77.02% [9][10] - **Maximum Drawdown**: 9.96% [9][10] - **July 2025 Performance**: - Long Portfolio Return: 1.29% [10] - Short Portfolio Return: -0.02% [10] - Long-Short Portfolio Return: 1.32% [10] Turn20 Factor - **Monthly IC Mean**: -0.072 [6] - **Annualized ICIR**: -2.10 [6] - **Annualized Return**: 33.41% [6] - **Information Ratio (IR)**: 1.90 [6] - **Monthly Win Rate**: 71.58% [6]

Group 1: Report Industry Investment Rating - No relevant content provided Group 2: Core Viewpoints of the Report - Microguide Convertible Bonds (118058.SH) started online subscription on August 6, 2025, with a total issuance scale of 1.17 billion yuan. After deducting issuance fees, the net raised funds will be used for the construction project of an intelligent factory for semiconductor thin - film deposition equipment [3]. - The current bond floor valuation is 99.08 yuan, and the YTM is 2.25%. The conversion parity is 100.6 yuan, and the parity premium rate is - 0.62%. The bond floor protection is good, and the terms of the convertible bonds are standard. The dilution rate of the total share capital is 7.03%, with relatively small dilution pressure on the equity [3]. - It is expected that the listing price of Microguide Convertible Bonds on the first day will be between 128.84 - 143.03 yuan, and the subscription rate is expected to be 0.0036%. It is recommended to actively subscribe [3]. Group 3: Summary by Directory 1. Convertible Bond Basic Information - The issuance and subscription schedule of Microguide Convertible Bonds is from August 4 to August 12, 2025, including steps such as publishing announcements, online roadshows, priority subscription for original shareholders, and online subscription [9]. - The basic terms of Microguide Convertible Bonds include a 6 - year term, AA/AA credit rating, a face value of 100 yuan, specific coupon rates from the first to the sixth year, and corresponding down - revision, redemption, and put - back terms [10]. - The raised funds will be used for the construction of an intelligent factory for semiconductor thin - film deposition equipment, the expansion of a R & D laboratory, and supplementary working capital [11]. - The bond - related indicators show a pure bond value of 99.08 yuan, a pure bond premium rate of 0.93%, and a pure bond YTM of 2.25%. The equity - related indicators show a conversion parity of 100.63 yuan and a parity premium rate of - 0.62% [11]. 2. Investment Subscription Suggestions - By referring to comparable targets in terms of parity, rating, and scale, as well as recent listed convertible bonds and an established empirical model, it is expected that the conversion premium rate of Microguide Convertible Bonds on the first - day of listing will be around 35%, and the listing price will be between 128.84 - 143.03 yuan [14][15]. - It is expected that the priority subscription ratio of original shareholders will be 74.28%, and the online subscription rate will be 0.0036% [16]. 3. Analysis of the Underlying Stock's Fundamental Aspects 3.1 Financial Data Analysis - Microguide Nano is a global high - end micro - nano equipment manufacturer in the semiconductor and pan - semiconductor fields. Its products have achieved large - scale industrial applications in the semiconductor and photovoltaic sectors [17]. - Since 2020, the company's revenue has steadily increased, with a compound growth rate of 71.44% from 2020 - 2024. In 2024, the revenue was 2.7 billion yuan, a year - on - year increase of 60.74%. In Q1 2025, the revenue and net profit attributable to the parent company were 510 million yuan and 84 million yuan respectively [18][19]. - The company's revenue mainly comes from photovoltaic and semiconductor equipment, with an annual adjustment in product structure. The proportion of photovoltaic sales revenue in the main business revenue has slightly decreased, while the sales scale of semiconductors has gradually increased [20]. - The company's net sales margin has recently rebounded, the gross sales margin has decreased, the sales expense ratio has decreased, the financial expense ratio has recently increased, and the management expense ratio has recently decreased [24]. 3.2 Company Highlights - Microguide Nano is a leader in providing efficient battery technology and equipment. It emphasizes R & D, has formed 11 core technologies in the thin - film deposition technology field centered around ALD technology, and has achieved deep integration of scientific and technological achievements and the industry [29].

Quantitative Factors and Construction Methods 1. Factor Name: UTR (U-Turnover Rate) - **Construction Idea**: The UTR factor combines two sub-factors, "Turn20" (volume-small factor) and "STR" (volume-stable factor), using a scoring method to address the issue of "1+1<2" in factor integration. The key idea is to prioritize stocks with stable volumes while favoring higher turnover within this stable group [6] - **Construction Process**: 1. At the end of each month, calculate the "Turn20" and "STR" values for all stocks [6] 2. Rank all stocks by the "STR" factor in ascending order and assign scores from 1 to N (N is the total number of stocks), referred to as "Score 1" [6] 3. For the top 50% of stocks ranked by "STR", rank them by "Turn20" in descending order and assign scores from 1 to N/2, referred to as "Score 2". The final score for these stocks is "Score 1 + Score 2" [6] 4. For the bottom 50% of stocks ranked by "STR", rank them by "Turn20" in ascending order and assign scores from 1 to N/2, referred to as "Score 3". The final score for these stocks is "Score 1 + Score 3" [6] 5. The resulting factor is named "UTR" [6] - **Evaluation**: The UTR factor effectively integrates the two sub-factors, achieving the goal of favoring higher turnover within stable-volume stocks [6] 2. Factor Name: UTR2.0 (U-Turnover Rate 2.0) - **Construction Idea**: UTR2.0 improves upon the original UTR factor by transitioning from ordinal scale to ratio scale for factor values. Additionally, it introduces a coefficient for the "Turn20" factor, which is a function of "STR", to better capture the varying impact of "Turn20" across different stability levels. The softsign activation function from neural networks is used to model this relationship [7] - **Construction Process**: 1. Transition from ordinal scale to ratio scale for factor values to retain more information [7] 2. Define the coefficient for "Turn20" as a function of "STR", where the coefficient increases with stability (positive impact) and decreases with instability (negative impact) [7] 3. Use the softsign activation function to model the relationship: $$ \mathrm{UTR2.0} = \mathrm{STR} + \text{softsign}(\mathrm{STR}) \cdot \mathrm{Turn20} $$ $$ \text{softsign}(x) = \frac{x}{1 + |x|} $$ [7] - **Evaluation**: Compared to the original UTR factor, UTR2.0 achieves lower returns but demonstrates superior volatility, information ratio (IR), and monthly win rate, making it a more robust factor [7][9] --- Factor Backtesting Results 1. UTR2.0 Factor - **Annualized Return**: 40.36% [9] - **Annualized Volatility**: 14.97% [9] - **Information Ratio (IR)**: 2.70 [9] - **Monthly Win Rate**: 75.74% [9] - **Maximum Drawdown**: 11.03% [9] 2. July 2025 Performance (UTR2.0 Factor) - **Long Portfolio Return**: 1.29% [9] - **Short Portfolio Return**: -0.06% [9] - **Long-Short Portfolio Return**: 1.35% [9]

Quantitative Factors and Construction Methods 1. Factor Name: Stability of the Growth Rate of Turnover Rate (GTR) - **Factor Construction Idea**: The GTR factor identifies stocks with stable growth or decline in turnover rate, which may indicate potential for future price increases. The factor captures the "acceleration" of turnover rate changes and emphasizes stability in these changes[6][7]. - **Factor Construction Process**: The GTR factor is derived from turnover rate data, focusing on the stability of its growth rate. Specific details on the mathematical formula or calculation process are not provided in the report[6][7]. - **Factor Evaluation**: The GTR factor demonstrates low correlation (less than 0.1) with other turnover rate factors in the same series, enhancing its uniqueness and effectiveness in stock selection[6]. 2. Factor Name: Purely Enhanced TPS_Turbo - **Factor Construction Idea**: The TPS_Turbo factor is created by applying a "purely enhanced" method to combine the GTR factor with other turnover-related factors (Turn20 and STR), aiming to improve stock selection performance[6]. - **Factor Construction Process**: The TPS_Turbo factor is constructed by integrating the GTR factor with Turn20 and STR using a purely enhanced methodology. The exact mathematical process or formula is not detailed in the report[6]. - **Factor Evaluation**: The TPS_Turbo factor exhibits strong stock selection capabilities, as evidenced by its high performance metrics in backtesting[6]. 3. Factor Name: Purely Enhanced SPS_Turbo - **Factor Construction Idea**: Similar to TPS_Turbo, the SPS_Turbo factor is derived by combining the GTR factor with other turnover-related factors using the purely enhanced methodology, with a focus on further improving stock selection[6]. - **Factor Construction Process**: The SPS_Turbo factor is constructed by integrating the GTR factor with other turnover-related factors using the same purely enhanced methodology as TPS_Turbo. Specific details on the formula are not provided[6]. - **Factor Evaluation**: The SPS_Turbo factor demonstrates the highest stock selection performance among the factors discussed, with superior backtesting results[6]. --- Factor Backtesting Results 1. Stability of the Growth Rate of Turnover Rate (GTR) - **Annualized Return**: 13.29%[7][11] - **Annualized Volatility**: 10.24%[7][11] - **IR**: 1.30[7][11] - **Monthly Win Rate**: 67.09%[7][11] - **Maximum Drawdown**: 10.81%[7][11] 2. Purely Enhanced TPS_Turbo - **Annualized Return**: 36.31%[7][11] - **Annualized Volatility**: 13.21%[7][11] - **IR**: 2.75[7][11] - **Monthly Win Rate**: 78.63%[7][11] - **Maximum Drawdown**: 9.86%[7][11] 3. Purely Enhanced SPS_Turbo - **Annualized Return**: 37.33%[7][11] - **Annualized Volatility**: 10.88%[7][11] - **IR**: 3.43[7][11] - **Monthly Win Rate**: 81.62%[7][11] - **Maximum Drawdown**: 7.22%[7][11] --- Monthly Performance (July 2025) 1. Stability of the Growth Rate of Turnover Rate (GTR) - **Long Portfolio Return**: 0.96%[14] - **Short Portfolio Return**: 0.36%[14] - **Long-Short Portfolio Return**: 0.60%[14] 2. Purely Enhanced TPS_Turbo - **Long Portfolio Return**: 1.15%[15] - **Short Portfolio Return**: 0.03%[15] - **Long-Short Portfolio Return**: 1.12%[15] 3. Purely Enhanced SPS_Turbo - **Long Portfolio Return**: 1.17%[19] - **Short Portfolio Return**: 0.11%[19] - **Long-Short Portfolio Return**: 1.06%[19]

Quantitative Factors and Construction Methods 1. Factor Name: TPS (Turn20 conformed by PLUS) - **Factor Construction Idea**: The TPS factor is designed to improve the traditional turnover rate factor by incorporating price-volume dynamics and addressing the stability of daily turnover rates. It uses shadow line differences as a price factor to complement the turnover rate factor, aiming to better capture market sentiment and improve stock selection performance[6][9]. - **Factor Construction Process**: 1. The traditional turnover rate factor (Turn20) is calculated as the average turnover rate over the past 20 trading days, followed by cross-sectional market capitalization neutralization[6]. 2. The TPS factor integrates the shadow line difference as a price factor to complement Turn20. The shadow line difference is used to represent intraday market sentiment, as it reflects the difference between the opening and closing prices[9]. 3. The final TPS factor is constructed by combining the Turn20 factor with the shadow line difference, using a double-group scoring method to optimize the results[9]. - **Factor Evaluation**: The TPS factor significantly outperforms traditional turnover rate factors in terms of stock selection ability. It remains effective even after removing the influence of common market styles and industry factors[1][9]. 2. Factor Name: SPS (STR conformed by PLUS) - **Factor Construction Idea**: Similar to the TPS factor, the SPS factor is designed to improve the traditional turnover rate factor by incorporating price-volume dynamics and addressing the stability of daily turnover rates. It also uses shadow line differences as a price factor to complement the STR (Stable Turnover Rate) factor[9]. - **Factor Construction Process**: 1. The STR factor was introduced to address the limitations of the traditional Turn20 factor, focusing on the stability of turnover rates. However, it still exhibited monotonicity issues in group standard deviations[7]. 2. The SPS factor integrates the shadow line difference as a price factor to complement the STR factor. The shadow line difference is used to better represent intraday market sentiment[9]. 3. The final SPS factor is constructed by combining the STR factor with the shadow line difference, using a double-group scoring method to optimize the results[9]. - **Factor Evaluation**: The SPS factor demonstrates strong stock selection ability, outperforming both the traditional turnover rate and STR factors. It remains effective after removing the influence of common market styles and industry factors[1][9]. --- Factor Backtesting Results 1. TPS Factor - **Annualized Return**: 39.56%[1][10] - **Annualized Volatility**: 15.70%[1][10] - **Information Ratio (IR)**: 2.52[1][10] - **Monthly Win Rate**: 77.78%[1][10] - **Maximum Drawdown**: 18.19%[1][10] - **July 2025 Performance**: - Long Portfolio Return: 0.96% - Short Portfolio Return: -0.04% - Long-Short Portfolio Return: 1.00%[1][12] 2. SPS Factor - **Annualized Return**: 43.26%[1][12] - **Annualized Volatility**: 13.15%[1][12] - **Information Ratio (IR)**: 3.29[1][12] - **Monthly Win Rate**: 83.76%[1][12] - **Maximum Drawdown**: 11.58%[1][12] - **July 2025 Performance**: - Long Portfolio Return: 1.22% - Short Portfolio Return: -0.14% - Long-Short Portfolio Return: 1.09%[1][14]

Investment Rating - The report maintains a "Buy" rating for the company [1] Core Insights - The ASC30 pipeline has successfully completed patient enrollment for the Phase IIa trial, with top-line data expected in Q4 2025. This compound has patent protection in the U.S. and globally until 2044 [7] - ASC30 has shown superior efficacy in previous trials, achieving a maximum weight loss of 6.5% over four weeks, outperforming a competitor's product [7] - The company has multiple promising pipelines, including ASC47 and ASC50, which are expected to have strong business development potential [7] - Revenue forecasts for 2025-2027 are projected at 0, 0.4, and 1 billion RMB respectively, with an updated target price of 14.02 RMB [7] Financial Summary - Total revenue for 2023 is projected at 566.9 million RMB, with a significant decline expected in 2024 [1] - The company is expected to incur net losses, with a projected net profit of -300.94 million RMB in 2024 and -454.44 million RMB in 2025 [1] - The price-to-earnings ratio is forecasted to improve from -49.48 in 2023 to -15.76 in 2025 [1][8]

Macro Strategy - The report analyzes three historical cases of capacity adjustment over a century, highlighting the transition from imbalance to rebalancing in supply and demand [1][13] - It concludes that capacity imbalance can lead to a negative feedback loop lasting 20-30 years if not controlled, emphasizing the need for government intervention rather than relying solely on market forces [1][13] - Effective rebalancing requires simultaneous efforts in controlling capacity, restoring credit, and stabilizing employment, rather than relying on supply or demand policies alone [1][13] Fixed Income - The report discusses the current state of urban investment bonds in Shaanxi Province, noting that the bond market is experiencing a downward trend due to macroeconomic uncertainties, but urban investment bonds still hold strong allocation value [2][14] - Shaanxi's GDP is projected to reach approximately 3.55 trillion yuan in 2024, with a growth rate of 5.30%, indicating a robust economic environment [2][14] - The report suggests a cautious approach to investing in lower-rated bonds due to compressed credit spreads, recommending a focus on higher-rated bonds with good liquidity [2][16] Industry Analysis - The report highlights Scale AI as a leading company in the AI data labeling sector, with significant revenue growth driven by demand from large enterprises and government [4][16] - Scale AI's revenue is projected to reach $20 billion by 2025, with a gross margin of 49%, indicating strong market potential despite current EBITDA losses [4][16] - The report emphasizes the importance of data quality and neutrality in the AI training data market, recommending investment in leading companies in high-quality data sets [4][16] Stock Recommendations - Pony.ai is identified as a leader in the Robotaxi sector, with significant cost reductions and safety improvements expected to drive commercialization [5][18] - Revenue forecasts for Pony.ai are projected at $0.78 billion, $1.05 billion, and $3.42 billion for 2025-2027, with a "buy" rating based on strong growth potential [5][18] - Yutong Bus is expected to maintain revenue growth of 15%-16% from 2025 to 2027, with a "buy" rating supported by a strong market position and recent contract wins [6][19]