Economic Growth - The easing of tariffs has boosted some U.S. survey indicators in May, with the composite PMI rising by 1.7 to 52.5, driven by improvements in manufacturing and services PMI, both exceeding expectations at 52.3[3] - The first quarter GDP growth rate was revised up by 0.1 percentage points to -0.2%, with inventory and investment contributions adjusted upward, while consumption and net exports were revised downward[3] - Retail sales showed a slight decline in April, with the Redbook retail index indicating a further drop in May's year-on-year retail growth[3] Financial Conditions - Goldman Sachs' Financial Conditions Index (FCI) relaxed by 26 basis points from May 1 to May 30, with the S&P 500 rising by 6.2% during the same period[4] - Investment-grade corporate spreads narrowed by 23 basis points to 1.14%, while the 2-year and 10-year U.S. Treasury yields increased by 29 basis points and 24 basis points, respectively, to 3.89% and 4.41%[4] Inflation - April's PCE inflation remained moderate, with the core PCE unchanged at 0.1% month-on-month and a year-on-year decline of 0.2 percentage points to 2.5%[5] - The CPI core goods related to China showed a significant rebound in growth rates from March to April, indicating the impact of tariffs on prices[5] Labor Market - In April, non-farm payrolls increased by 177,000, surpassing expectations of 138,000, while the unemployment rate remained stable at 4.2%[6] - The labor force participation rate rose to 62.6%, but the job vacancy rate has shown signs of decline, indicating potential future hiring slowdowns[6][6] Risks - There is an increasing uncertainty regarding Trump's policies, which may lead to a continued slowdown in U.S. economic growth[7]

Quantitative Models and Construction Methods AI Industry Rotation Model - **Model Name**: AI Industry Rotation Model - **Model Construction Idea**: The model uses a full-spectrum volume-price fusion factor to score 32 primary industries and constructs a weekly rebalancing strategy, selecting the top 5 industries for equal-weight allocation[1][16][23] - **Model Construction Process**: 1. **Industry Pool**: Includes 32 primary industries, with some industries split into subcategories (e.g., food and beverage split into food, beverage, and liquor)[23] 2. **Factor**: Full-spectrum volume-price fusion factor, derived from deep learning models extracting information from multi-frequency volume-price data[16][23] 3. **Strategy Rules**: - Select the top 5 industries with the highest scores on the last trading day of each week - Equal-weight allocation - Buy at the next week's first trading day's closing price - Weekly rebalancing, no transaction costs considered[23] - **Model Evaluation**: The model leverages AI's feature extraction capabilities to identify patterns in multi-frequency volume-price data, complementing top-down strategies[16] AI Theme Index Rotation Model - **Model Name**: AI Theme Index Rotation Model - **Model Construction Idea**: The model uses a full-spectrum volume-price fusion factor to score 133 thematic indices and constructs a weekly rebalancing strategy, selecting the top 10 indices for equal-weight allocation[2][6][9] - **Model Construction Process**: 1. **Index Pool**: Includes 133 thematic indices tracked by thematic ETFs, based on Wind's ETF classification[9] 2. **Factor**: Full-spectrum volume-price fusion factor, scoring each thematic index based on its constituent stocks[9] 3. **Strategy Rules**: - Select the top 10 indices with the highest scores on the last trading day of each week - Equal-weight allocation - Buy at the next week's first trading day's opening price - Weekly rebalancing, transaction costs set at 0.04% for both sides[9] - **Model Evaluation**: The model effectively identifies high-performing thematic indices using AI-driven factor scoring[6] AI Concept Index Rotation Model - **Model Name**: AI Concept Index Rotation Model - **Model Construction Idea**: The model uses a full-spectrum volume-price fusion factor to score 72 concept indices and constructs a weekly rebalancing strategy, selecting the top 10 indices for equal-weight allocation[11][15] - **Model Construction Process**: 1. **Index Pool**: Includes 72 concept indices based on Wind's popular concept indices[15] 2. **Factor**: Full-spectrum volume-price fusion factor, scoring each concept index based on its constituent stocks[15] 3. **Strategy Rules**: - Select the top 10 indices with the highest scores on the last trading day of each week - Equal-weight allocation - Buy at the next week's first trading day's opening price - Weekly rebalancing, transaction costs set at 0.04% for both sides[15] - **Model Evaluation**: The model efficiently captures trends in concept indices using AI-based factor scoring[11] AI CSI 1000 Enhanced Portfolio - **Model Name**: AI CSI 1000 Enhanced Portfolio - **Model Construction Idea**: The portfolio is constructed using the full-spectrum volume-price fusion factor to enhance the CSI 1000 index[3][26][29] - **Model Construction Process**: 1. **Factor**: Full-spectrum volume-price fusion factor, combining high-frequency deep learning factors and low-frequency multi-task learning factors[26] 2. **Portfolio Construction Rules**: - Constituent stock weight ≥ 80% - Individual stock weight deviation limit: 0.8% - Barra exposure < 0.3 - Weekly rebalancing, turnover rate controlled at 30% - Transaction costs set at 0.4% for both sides[29] - **Model Evaluation**: The portfolio demonstrates strong enhancement capabilities relative to the CSI 1000 index, with high IR and controlled tracking error[28] Text-based FADT_BERT Stock Selection Portfolio - **Model Name**: Text-based FADT_BERT Portfolio - **Model Construction Idea**: The portfolio is based on the forecast_adjust_txt_bert factor, which upgrades text factors in earnings forecast adjustment scenarios[32] - **Model Construction Process**: 1. **Factor**: Forecast_adjust_txt_bert factor, derived from text analysis of earnings forecast adjustments[32] 2. **Portfolio Construction Rules**: - Top 25 stocks from the long side of the factor's base stock pool - Active quantitative stock selection strategy[32] - **Model Evaluation**: The portfolio effectively integrates text-based factors into stock selection, achieving high long-term returns[32] --- Model Backtesting Results AI Industry Rotation Model - Annualized return: 24.95% - Annualized excess return: 20.80% - Maximum drawdown of excess return: 12.43% - Excess Sharpe ratio: 2.00 - YTD return: 4.88% - YTD excess return: 1.11%[1][22][25] AI Theme Index Rotation Model - Annualized return: 16.03% - Annualized excess return: 13.10% - Maximum drawdown of excess return: 16.55% - Excess Sharpe ratio: 1.02 - YTD return: 9.86% - YTD excess return: 10.43%[2][8][9] AI Concept Index Rotation Model - Annualized return: 22.42% - Annualized excess return: 12.68% - Maximum drawdown of excess return: 17.96% - Excess Sharpe ratio: 1.07 - YTD return: 11.48% - YTD excess return: 7.61%[11][13][15] AI CSI 1000 Enhanced Portfolio - Annualized return: 17.31% - Annualized excess return: 22.17% - Annualized tracking error: 6.07% - Maximum drawdown of excess return: 7.55% - IR: 3.65 - Calmar ratio: 2.93[3][28][30] Text-based FADT_BERT Stock Selection Portfolio - Annualized return since inception: 39.29% - Annualized excess return since inception: 31.74% - Maximum drawdown: 48.69% - Sharpe ratio: 1.36 - Calmar ratio: 0.81[32][36][38]

Economic Overview - Export demand index (HDET) recorded approximately 0% year-on-year growth from May 1-30, indicating a recovery in export sentiment post-tariff reduction[2] - From January to May, net issuance of national and local bonds increased by CNY 3.66 trillion year-on-year, supporting domestic demand[2] PMI Analysis - Manufacturing PMI rose from 49% in April to 49.5% in May, aligning with Bloomberg consensus expectations[4] - The production index within the manufacturing PMI increased by 0.9 percentage points to 50.7%, while new orders and new export orders rose to 49.8% and 47.5%, respectively[4] - Employment index in manufacturing improved marginally to 48.1%, suggesting a slight recovery in labor demand[4] Sector Performance - High-tech industries maintained expansion with a PMI of 50.9%, while high-energy industries saw a decline in PMI to 47.0%[7] - Non-manufacturing business activity index slightly decreased to 50.3%, with new orders index rising to 46.1%[7] Price Trends - Raw material purchase and factory price indices fell by 0.1 percentage points to 46.9% and 44.7%, respectively, indicating pressure on corporate profits[8] - Prices for coal, rebar, and Brent crude oil decreased by 6.4%, 0.2%, and 3.7% month-on-month, while domestic copper and aluminum prices increased by 2.1% and 0.9%[8] Risks - Potential risks include unexpected escalation in US-China trade tensions and weaker-than-expected domestic demand[9]

Economic Growth - In May, the easing of tariffs boosted growth momentum, but the impact of tariffs may still need to be fully realized[1] - The US Markit Manufacturing and Services PMI both exceeded expectations, pushing the composite PMI up to 52.5[1] - The Eurozone's composite PMI fell to 49.5, dragged down by the services sector, while manufacturing PMI rose to 49.4[1] Inflation Trends - The US April core PCE inflation remained flat at 0.1% month-on-month and 2.5% year-on-year, meeting expectations[1] - Japan's April core CPI rose by 0.3 percentage points to 3.5%, exceeding the expected 3.4%[1] Market Performance - As of May 30, US stock indices rose significantly, with the S&P 500, Nasdaq, and Dow Jones increasing by 6.2%, 9.6%, and 3.9% respectively[2] - The 2-year and 10-year US Treasury yields rose by 29 basis points and 24 basis points to 3.89% and 4.41% respectively[2] Policy Developments - On May 12, a joint statement announced a reduction of tariffs from 125% to 34%, with 24% of tariffs deferred for 90 days[3] - The US House passed the "Beautiful Bill," which includes tax cuts and an increase in the debt ceiling, expected to raise the fiscal deficit by $3.1 trillion over ten years[3] Risks - There is uncertainty surrounding the reversal of Trump's tariff policies and increased geopolitical volatility[4]

Investment Rating - The report does not explicitly provide an investment rating for the A-share market but emphasizes the construction of a multi-dimensional timing framework to enhance investment decisions. Core Insights - The multi-dimensional timing framework developed from various indicators has shown a significant improvement in performance, with a Sharpe ratio of approximately 1 and an annualized return of about 22% compared to the 3.77% annualized return of the underlying assets during the same period [1][3][42]. Summary by Sections Single Indicator Testing: Valuation, Sentiment, Capital, and Technical - A series of indicators with timing capabilities and good complementarity were selected, including financing buy amounts, Bollinger Bands, individual stock price change ratios, options put-call ratios, implied volatility, and futures positions [2][11][16]. - These indicators provide insights into the current market state, but single indicators face issues such as excessive noise and inconsistent performance across different samples [2][42]. Multi-Dimensional Framework Construction: Layered Synthesis of Timing Signals - The report proposes a layered synthesis approach to combine multiple original signals, achieving a synergistic effect where 1+1>2 [3]. - The framework integrates valuation and sentiment indicators as left-side indicators, while capital and technical indicators form right-side indicators, balancing win rates and payoffs [3][39]. Evaluation and Analysis: Overfitting Risk and Generalization Ability - The multi-dimensional framework exhibits lower overfitting risk and higher applicability across major A-share indices, particularly benefiting small-cap stocks [4][39]. - The framework's adaptability allows investors to tailor it according to their specific needs, with valuation indicators being more suitable for large-cap stocks and capital and technical indicators being more effective for small-cap stocks [4][39].

Investment Rating - The report maintains a "Buy" rating for the company with a target price of 15.30 HKD [8][9]. Core Insights - The company reported a revenue of 16.98 billion USD for 4QFY25, representing a year-over-year increase of 22.8%, exceeding Bloomberg consensus expectations by 8.4% [1]. - Non-HKFRS net profit attributable to shareholders was 280 million USD, up 24.7% year-over-year, indicating business resilience despite tariff uncertainties [1]. - Revenue forecasts for FY26 and FY27 have been cautiously adjusted downwards by 5.1% and 3.1% to 75.44 billion USD and 81.69 billion USD, respectively, due to tariff impacts [1]. - The company is expected to maintain strong growth in high-margin businesses driven by the rollout of AI agent products [1]. Summary by Sections IDG (Intelligent Devices Group) - IDG revenue increased by 12.9% year-over-year, with a pre-tax profit margin of 6.8% [2]. - PC and smartphone shipments grew by 10.9% and 5.6% year-over-year, respectively, outpacing global shipment growth rates [2]. - Revenue from PCs rose by 13.2% year-over-year, driven by robust sales of gaming laptops and high-end workstations [2]. ISG (Infrastructure Solutions Group) - ISG revenue surged by 62.7% year-over-year, continuing its strong growth trajectory [3]. - The growth was primarily fueled by AI server demand, with "Neptune liquid cooling" revenue increasing by 68% year-over-year [3]. - FY26 revenue is projected to grow by 22.2% year-over-year to 17.74 billion USD [3]. SSG (Solutions and Services Group) - SSG achieved a pre-tax profit margin of 22.7%, the highest since FY22, indicating robust growth in AI solutions and services [4]. - AI solutions and "as-a-service" offerings accounted for 58% of SSG revenue, reflecting a 4 percentage point increase year-over-year [4]. - FY26 revenue is expected to grow by 10.0% year-over-year, driven by digital solutions and cloud services [4]. Financial Projections - The company anticipates FY26/27/28 net profits of 1.47 billion USD, 1.50 billion USD, and 1.53 billion USD, respectively, with year-over-year growth rates of 2.0%, 2.1%, and 2.1% [5]. - The projected EPS for FY26, FY27, and FY28 are 0.13 USD, 0.14 USD, and 0.15 USD, respectively [5]. - The report applies a 15x FY26 PE valuation, reflecting a premium over the average PE of comparable companies [5].

Investment Rating - The industry investment rating is "Overweight" [5] Core Views - The report highlights a positive outlook for the lithium battery supply chain, with a month-on-month increase in production driven by policies promoting electric vehicle (EV) demand and a favorable export environment for energy storage [1] - The domestic market for new energy vehicles (NEVs) is expected to grow significantly, with a year-on-year increase in retail sales and a notable rise in commercial vehicle electrification [2] - The energy storage market is supported by strong bidding volumes in China and continued growth in Europe and emerging markets, indicating robust future demand [3] Summary by Sections Lithium Battery Production - In June, battery production reached 107.7 GWh, a month-on-month increase of 2.9% - Positive trends in production for cathodes (133,000 tons, +9.1%), anodes (117,000 tons, +0.9%), separators (1.49 billion square meters, +4.3%), and electrolytes (76,000 tons, +6.6%) were noted [1] New Energy Vehicles - Domestic NEV retail sales reached 980,000 units in May, a year-on-year increase of 21.9% - Cumulative sales from January to May reached 4.306 million units, up 32.8% year-on-year - The penetration rate of new energy heavy trucks reached 23.0%, significantly exceeding previous expectations [2] Energy Storage Market - The bidding scale for energy storage in China reached 132.89 GWh from January to April, a year-on-year increase of 219.1% - The U.S. market saw a 105% year-on-year increase in large-scale storage installations, driven by favorable tariff expectations [3] Supply and Demand Dynamics - The report indicates tightening supply and demand dynamics, with expectations for improved capacity utilization and profitability for leading battery manufacturers [4] - Recommended companies include CATL, EVE Energy, and Sunwoda, which are expected to benefit from these trends [4]

Investment Rating - The report maintains a "Buy" rating for the companies mentioned, including Kingsoft Office, Foxit Software, Wangsu Science & Technology, and Dingjie Smart [10][13][15][17][18]. Core Insights - The R1-0528 model from DeepSeek has achieved a performance improvement of 15%-26% compared to its predecessor, with significant enhancements in mathematical and coding capabilities [1][3][4]. - The introduction of tool invocation in R1-0528 is a key development, enabling its use in complex agent processes, which could disrupt the current reliance on overseas models [1][4]. - The report highlights the potential for R1-0528 to drive advancements in the agent and MCP (Model Context Protocol) sectors, suggesting a positive outlook for related companies [5]. Summary by Sections Model Performance - R1-0528 shows a notable increase in reasoning depth and token usage, with an average of 23K tokens per question compared to 12K in the previous version [2]. - The model's hallucination rate has decreased by 45%-50%, addressing a significant issue present in the earlier version [3]. Tool Invocation - The support for tool invocation in R1-0528 is emphasized as a major highlight, allowing for broader applications in agent development [4]. - The model's performance in the Tau-Bench evaluation is comparable to OpenAI's models, although it still lags behind in some areas [4]. Recommended Companies - The report recommends investing in Kingsoft Office, Foxit Software, Wangsu Science & Technology, and Dingjie Smart due to their potential benefits from advancements in AI and agent technologies [5]. - Other companies in the industry chain are also highlighted, including Hehe Information and HanDe Information, which are positioned to benefit from the growing demand for agent solutions [5].

Investment Rating - The report maintains a "Buy" rating for the company with a target price of $159.87 per ADS [8][9]. Core Insights - The company reported a significant increase in Q1 2025 performance, with revenue of HKD 4.7 billion, up 81% year-over-year, and net profit of HKD 2.1 billion, up 107% year-over-year, driven by accelerated overseas customer acquisition and increased trading volumes in the Hong Kong and US stock markets [1][5]. - The company has achieved one-third of its annual customer acquisition target in Q1 2025, adding 260,000 new funded accounts, a 48% increase year-over-year [2]. - The trading activity in the Hong Kong and US markets remains robust, with total trading volume reaching HKD 3.22 trillion, a 140% increase year-over-year [3]. - Continuous innovation in products and services, including AI-driven investment assistants and new trading options, is strengthening the company's brand and product capabilities [4]. Summary by Sections Financial Performance - For 2025-2027, the company expects net profits of HKD 7.5 billion, HKD 8.4 billion, and HKD 9.2 billion respectively, reflecting an upward revision of 20%-26% from previous estimates [5][7]. - The estimated EPS for 2025 is HKD 6.52, with a projected PE ratio of 24x [5][7]. Customer Acquisition - The company has seen a strong influx of new customers, particularly from Hong Kong, Japan, the US, and Malaysia, with significant participation in recent IPOs [2]. Trading Activity - The trading environment is favorable, with a notable increase in trading volumes and customer asset turnover rates, indicating high market engagement [3]. Innovation and Product Development - The company is actively enhancing its service offerings, including the introduction of new trading products and platforms, which are crucial for attracting overseas customers [4].

Legal Implications - The U.S. International Trade Court ruled that Trump's tariffs under the IEEPA exceeded presidential authority, marking a significant limitation on his power to impose tariffs[1] - The ruling requires the Trump administration to terminate related tariffs by June 7, 2025, unless an appeal is granted[2] Tariff Adjustments - The probability of the U.S. adjusting tariffs on Mexico and Canada has increased, with a potential final tariff level closer to the lower end of 15%[10] - The U.S. may still impose tariffs on specific countries and industries, with the possibility of using other legal provisions to maintain a 10% global tariff temporarily[3] Revenue Projections - If the U.S. imposes a 10% tariff on its top 10-15 trade surplus countries, it could generate approximately $240-290 billion in annual tariff revenue[4] - The average U.S. tariff rate is expected to rise by about 4.5-5.4 percentage points due to strategic tariffs on key industries[5] Strategic Considerations - The U.S. is likely to maintain high tariffs on China, with cumulative tariffs expected to reach 30-40%, despite potential adjustments in structure[6] - The ongoing legal and political battles over tariffs indicate a shift of power back to Congress, although there remains a consensus within the current administration for certain tariff levels[7] Risks and Challenges - There is a risk of unexpected fluctuations in U.S. tariff policies, particularly in negotiations with China[8] - The interplay between tariff policies and capital outflows from the U.S. may create significant economic feedback loops, impacting future tariff decisions[7]