Quantitative Models and Construction Methods 1. Model Name: Multivariate CNN-LSTM - **Model Construction Idea**: The model leverages the advantages of CNN and LSTM in different scenarios to predict multiple parallel financial time series by considering the correlation between them[12][14]. - **Detailed Construction Process**: - **General Structure**: The model consists of an input layer, a one-dimensional convolutional layer, a pooling layer, an LSTM hidden layer, and a fully connected layer to produce the final prediction results[14]. - **Formula**: $$ {\hat{x}}_{k,t+h}=f_{k}(x_{1,t},\dots,x_{k,t},\dots,x_{1,t-1},\dots,x_{k,t-1},\dots) $$ This formula indicates that each variable depends not only on its past values but also on the past values of other variables[11]. - **Hyperparameters**: - Number of convolution filters: 64 - Convolution kernel size: 2 - Use of padding: Yes - Pooling layer window size: (2,2) - Number of hidden units in the first LSTM layer: 128 - Number of hidden units in the second LSTM layer: 128 - Activation method between LSTM layers: ReLU - Time series look-back window: 10 - Number of training epochs: 100[20] - **Evaluation Metric**: Root Mean Square Error (RMSE) $$ RMSE={\sqrt{\frac{1}{n}\sum_{i}({\hat{y_{i}}}-y_{i}\,)^{2}}} $$ where \( y_i \) represents the standardized index price, and \( \hat{y_i} \) represents the CNN-LSTM prediction value[21]. - **Model Evaluation**: The model achieved good tracking and high accuracy in predicting multiple parallel financial time series, similar to the performance in predicting stock indices in the Asia-Pacific market[14][17]. 2. Model Name: Grouped Multivariate CNN-LSTM - **Model Construction Idea**: To improve prediction accuracy, the industry indices are grouped based on investment attributes, and a separate prediction model is constructed for each group[26][27]. - **Detailed Construction Process**: - **Grouping**: The industry indices are divided into six groups: Consumer and Medicine, Upstream Resources and Materials, High-end Manufacturing, Real Estate and Infrastructure, Big Tech, and Big Finance[27]. - **Model Structure**: Each group of industry indices is predicted using a separate CNN-LSTM model, as shown in the general structure diagram[28]. - **Evaluation Metric**: The prediction accuracy is evaluated using RMSE, similar to the original model[33]. - **Model Evaluation**: Grouping and training different CNN-LSTM sub-models for each industry group improved the prediction accuracy, especially for industries with previously low prediction accuracy[30][32]. Model Backtesting Results 1. Multivariate CNN-LSTM Model - **Prediction Error (Training Phase)**: 1.52% to 3.18%[23] - **Prediction Error (Testing Phase)**: 1.56% to 3.30%[23][25] 2. Grouped Multivariate CNN-LSTM Model - **Prediction Error (Training Phase)**: 1.49% to 2.60%[33] - **Prediction Error (Testing Phase)**: 1.61% to 2.82%[33] Quantitative Factors and Construction Methods 1. Factor Name: Weekly Industry Rotation Signal - **Factor Construction Idea**: Use the predicted values from the multivariate CNN-LSTM model to estimate the future weekly returns of industry indices and select the top five industries with the highest expected returns for equal-weight allocation[3]. - **Detailed Construction Process**: - **Prediction**: Predict the future weekly returns of industry indices using the multivariate CNN-LSTM model[34]. - **Allocation**: Every five trading days, select the top five industries with the highest expected returns for equal-weight allocation[35]. - **Training**: Retrain the model at the beginning of each quarter using an extended window of historical data from March 2014 to the training point[35]. - **Factor Evaluation**: The annualized return of the industry rotation portfolio reached 15.6%, with an annualized excess return of approximately 11.6%, and the risk-return characteristics significantly improved compared to the benchmark[3][35]. Factor Backtesting Results 1. Weekly Industry Rotation Signal - **Annualized Return**: 15.6%[38] - **Annualized Volatility**: 25.6%[38] - **Maximum Drawdown**: -27.1%[38] - **Sharpe Ratio**: 0.7[38] - **Longest Drawdown Recovery Time**: 248 days[38]

Investment Rating - The industry investment rating is optimistic [1] Core Insights - The financial IT sector shows significant elasticity during the initial stages of a bull market, with notable price increases and valuation expansions [3] - The combination of technology and finance attributes leads to a "Davis Double Play" effect during bull markets, particularly highlighted in 2015 [4] - Current advancements in AI and new business developments are expected to drive further growth in the financial IT sector [5] Summary by Sections 2014-2015: Liquidity Explosion, Financial Technology Leads - The bull market from 2014 to 2015 was driven by ample liquidity and the rise of mobile internet, leading to significant gains in financial technology stocks [15][19] - Financial technology stocks experienced substantial price increases, with some stocks seeing gains close to 450% compared to mid-2014 levels [4] - The financial IT sector benefited from increased investor participation and software usage during the bull market [33] 2016-2018: Structural Bull Market, Varied Performance in Financial Technology - The period from 2016 to 2018 was characterized by a structural bull market influenced by supply-side reforms and foreign capital inflows [43] - Financial technology stocks underperformed compared to the broader market during this period, primarily due to high valuations and changing market preferences [46][52] - The financial IT sector faced challenges as the market shifted focus towards blue-chip and consumer stocks, leading to a decline in growth stocks [56] 2019-2021: Core Assets Drive Structural Bull Market - The financial technology sector saw a resurgence from 2019 to 2021, driven by global liquidity and domestic industrial upgrades [70] - The introduction of the Sci-Tech Innovation Board in 2019 significantly boosted the financial technology sector, with strong performance noted in various market phases [76][81] - Financial technology stocks outperformed the market during key periods, reflecting the sector's recovery and growth potential [82]

Investment Rating - The investment rating for the company is maintained as "Buy" [7] Core Views - The company achieved a revenue of 3.912 billion yuan in the first half of 2025, representing a year-on-year increase of 13.70%. The net loss attributable to the parent company was 226 million yuan, with a net loss of 232 million yuan after deducting non-recurring items. In Q2 2025, the company recorded a revenue of 2.369 billion yuan, a year-on-year increase of 38.20%, with a net loss of 28 million yuan, significantly reduced from approximately 216 million yuan in Q1 [1][2] - The rapid improvement in the company's Q2 performance reflects the industry's supply-demand dynamics, with expectations for continued revenue and profit growth in the latter half of the year due to favorable industry trends [2][3] - The global storage market is expected to recover, with a market size reaching 165.52 billion USD in 2024, a year-on-year increase of 79.3%. The demand for storage driven by AI technology is anticipated to provide significant growth opportunities for the semiconductor storage industry [3][4] Financial Summary - Revenue forecasts for 2025-2027 are 8.5 billion yuan, 10.8 billion yuan, and 14.2 billion yuan, respectively, with corresponding net profits of 420 million yuan, 1.13 billion yuan, and 1.58 billion yuan. The company maintains a "Buy" rating based on these projections [5][12]

Group 1: Key Recommendations - The report recommends 盛业 (06069) as a supply chain technology leader with a projected revenue growth of 24%/26%/24% and net profit growth of 43%/46%/33% from 2025 to 2027, with a target price of 21.65 HKD, indicating a potential upside of 62.9% [4] - 百亚股份 (003006) is highlighted as a leading regional sanitary napkin brand, with expected revenue growth of 26.33%/26.10%/25.11% and net profit growth of 28.20%/41.27%/37.43% from 2025 to 2027, driven by online strategy optimization and scale effects [5] - 日久光电 (003015) is identified as a leader in the membrane materials sector, with projected revenue growth of 36%/26%/20% and net profit growth of 112%/58%/32% from 2025 to 2027, benefiting from new product applications in automotive displays [6][9] Group 2: Industry Insights - The macroeconomic report indicates that excess household savings since 2020 amount to approximately 4.25 trillion, suggesting that the capital market may become a key outlet for these funds, potentially enhancing market liquidity and investor participation [10] - The A-share strategy report notes a divergence in index performance, with a "systematic slow bull" market outlook, suggesting that investors should maintain current positions and look for mid-term opportunities amidst potential short-term volatility [11][12]

1. Report Industry Investment Rating No investment rating for the industry is provided in the report. 2. Core Viewpoints - Since July, the convertible bond ETFs have significantly expanded. Investors share the returns of the equity market by betting on passive tools. Driven by the equity market and the inflow of fixed - income funds, the convertible bond index has reached a new high. At present, with both high prices and valuations, the anti - decline and protective properties of convertible bonds have weakened significantly. After the convertible bond index reaches new highs, it is recommended to adjust the structure instead of increasing the index position. Potential opportunities can be explored from three aspects: "anti - involution", underlying stock elasticity, and dividend allocation [1][2]. 3. Summary by Relevant Catalogs 3.1 1 转债周度思考 - In the past week, after adjustments, both the equity market and the convertible bond market rose again, and the convertible bond index reached a new high. The Shanghai Composite Index returned above 3600 points, the CSI Convertible Bond Index reached a new high, the Wind Convertible Bond Equal - Weighted Index rose 2.73% in the past week, and the underlying stock equal - weighted index of convertible bonds rose 3.00%. The median price of convertible bonds has exceeded 130 yuan, and the valuations of equity - like and balanced convertible bonds continue to expand [2]. - Since July, the convertible bond ETFs have significantly expanded. The share of two convertible bond ETFs has rapidly increased, with a 27% month - on - month increase compared to the end of June, and the scale has exceeded 5.72 billion yuan. Considering that some active funds are also making index - based layouts, the scale of index - based investment tools is expected to exceed 6.5 billion yuan. The holders of ETFs are mainly absolute - return funds such as banks and insurance companies, which invest in convertible bond ETFs to share the equity market's upward trend since late June and enhance returns by increasing positions in convertible bond indices [2]. - At present, with both high prices and valuations, the anti - decline and protective properties of convertible bonds have weakened significantly. Although the equity market is generally expected to be in a slow - bull state with a relatively low possibility of a large - scale pullback, the high point of the equity market within the year is unclear. After this round of increase, the price center of convertible bonds has generally risen, and the median has exceeded 130 yuan. With the continuous inflow of funds, the valuation has also been stretched. For some individual bonds in the 120 - 130 yuan price range that have risen with the market, the current median conversion premium rate is 40%, and the investment cost - effectiveness is average. Under the condition that the fundamentals of individual bonds cannot change significantly in the short term and the call - at - par - value - at - 130 clause is in place, the anti - decline and protective properties of these convertible bonds with a higher price center and premium rate have weakened significantly [2]. - After the convertible bond index reaches new highs, it is recommended to adjust the structure instead of increasing the index position. The state of convertible bonds in a relatively mild stock - bond market remains unchanged, and there are still opportunities for convertible bonds to perform. Since July, the number of callable convertible bonds has increased, and the supply - demand contradiction of convertible bonds still exists, which supports the valuation and performance of convertible bonds. Absolute - return funds can take partial profits or adjust the structure while keeping the overall position unchanged. It is recommended to explore opportunities along three lines: (1) Pay attention to industries where some backward production capacities are being cleared as "anti - involution" progresses in various industries; (2) Focus on equity - like and balanced convertible bonds with high - volatility and low - premium underlying stocks. Industries such as electronics and semiconductors are expected to experience marginal recovery due to tariff easing, and innovative drug convertible bond targets are scarce; (3) The allocation value of dividend assets remains high, and low - volatility bottom - position convertible bonds are worth attention [2]. 3.2 2 可转债市场跟踪 3.2.1 2.1 可转债行情方面 - The report provides the performance data of various convertible bond indices in different time periods, including the past week, two weeks, since July, one month, two months, half - year, and one year. For example, the Wind Convertible Bond Energy Index rose 2.60% in the past week, 6.81% since July, and 21.79% in the past year [12]. 3.2.2 2.2 转债个券方面 No specific analysis content for this part is provided in the text other than the section title. 3.2.3 2.3 转债估值方面 No specific analysis content for this part is provided in the text other than the section title. 3.2.4 2.4 转债价格方面 No specific analysis content for this part is provided in the text other than the section title.

Investment Rating - The investment rating for the company is "Buy" [6] Core Views - The company's Q2 revenue met expectations, but profit margins faced further pressure due to fluctuations in old customer orders and the ramp-up of new factories [1] - New customer orders saw significant growth year-on-year, although some old customer orders declined due to external factors such as consumer demand in Europe and the US, and tariff uncertainties [2] - The company's gross margin fluctuated due to the efficiency ramp-up of new factories and adjustments in production capacity among older factories [3] - The company is maintaining an aggressive capacity expansion strategy, with new factories in Vietnam and Indonesia expected to enhance profitability in the coming years [4] - Profit forecasts have been adjusted downward for the current year due to uncertainties in trade environments, but a recovery in profit margins is anticipated in 2026 as new factory efficiencies improve [5] Summary by Sections Financial Performance - For H1 2025, the company achieved revenue of 12.66 billion yuan, a year-on-year increase of 10.4%, while net profit was 1.664 billion yuan, a decrease of 11.4% [1] - In Q2 2025, revenue was 7.31 billion yuan, up 9.0% year-on-year, with net profit at 902 million yuan, down 17.3% [1] Customer Dynamics - The company experienced a significant increase in new customer orders, primarily from brands like Adidas and New Balance, contributing to a 6.14% increase in sports shoe sales to 11.5 million pairs in H1 2025 [2] Production and Capacity - The net profit margin for H1 2025 was 13.1%, down 3.2 percentage points year-on-year, with Q1 and Q2 margins at 14.2% and 12.3%, respectively [3] - The company is actively expanding production capacity with new factories, which typically take 1.5 to 2 years to reach full efficiency [4] Profit Forecasts - Revenue projections for 2025-2027 are 26.66 billion yuan, 30.15 billion yuan, and 34.18 billion yuan, with expected year-on-year growth rates of 11%, 13%, and 13% respectively [5]

Quantitative Models and Construction 1. Model Name: Fundamental Quantitative Model - **Model Construction Idea**: This model tracks the fundamental performance of industries, focusing on the transition from expectation-driven to data-driven analysis, particularly for cyclical sectors like coal and chemicals[3][13] - **Model Construction Process**: The model evaluates industry fundamentals by analyzing indicators such as industry prosperity and earnings expectations. It identifies sectors with improving fundamentals and aligns them with market sentiment shifts[3][13] - **Model Evaluation**: The model effectively captures the transition from speculative to fundamental-driven market dynamics, aligning with the observed recovery in cyclical sectors like coal and chemicals[3][13] 2. Model Name: Sentiment Quantitative Model - **Model Construction Idea**: This model measures market sentiment, particularly focusing on retail investor activity and trading dynamics in the TMT sector[3][13] - **Model Construction Process**: The model tracks metrics such as average daily turnover and retail investor participation. It identifies sectors with high trading activity and sentiment, such as TMT, which has seen sustained upward momentum since June[3][13] - **Model Evaluation**: The model successfully identifies sectors with strong trading sentiment, highlighting the TMT sector's resilience and potential for continued upward movement[3][13] 3. Model Name: Crowding Indicator Model - **Model Construction Idea**: This model assesses the crowding level in specific sectors, such as innovative drugs, to predict potential risks of pullbacks[3][13] - **Model Construction Process**: The model calculates crowding indicators based on historical data, comparing current levels to a 5-year range. For example, the crowding indicator for the innovative drug sector is at 94.93%, suggesting a high likelihood of a pullback in the next three weeks[3][13] - **Model Evaluation**: The model provides a robust framework for identifying overbought conditions, offering valuable insights for risk management in crowded sectors[3][13] --- Model Backtesting Results 1. Fundamental Quantitative Model - **Indicator: Industry Prosperity**: Coal and chemical sectors show improving fundamentals, aligning with the model's predictions for upward revisions in August[3][13] 2. Sentiment Quantitative Model - **Indicator: Average Daily Turnover**: The average daily turnover for the entire A-share market remains at approximately 1.75 trillion yuan, a historically high level, supporting the model's sentiment analysis[3][13] 3. Crowding Indicator Model - **Indicator: Crowding Level**: The crowding indicator for the innovative drug sector is at 94.93%, indicating a high risk of pullback within three weeks[3][13] --- Quantitative Factors and Construction 1. Factor Name: EP Value Factor - **Factor Construction Idea**: This factor identifies assets with high earnings-to-price ratios, which are expected to deliver superior returns[25][26] - **Factor Construction Process**: The factor is calculated as the ratio of earnings per share (EPS) to the stock price. It is used to rank assets based on their relative valuation attractiveness[25][26] - **Factor Evaluation**: The factor demonstrates strong performance, with high EP value assets delivering significant excess returns during the week[25][26] 2. Factor Name: Momentum Factor - **Factor Construction Idea**: This factor captures short-term price momentum, identifying stocks with strong recent performance[25][26] - **Factor Construction Process**: The factor is calculated based on the relative price performance of stocks over a defined short-term period. Stocks with the highest momentum scores are expected to outperform[25][26] - **Factor Evaluation**: The factor shows notable outperformance during the week, highlighting its effectiveness in capturing short-term trading opportunities[25][26] 3. Factor Name: Nonlinear Size Factor - **Factor Construction Idea**: This factor examines the nonlinear relationship between market capitalization and stock returns[25][26] - **Factor Construction Process**: The factor is derived by fitting a nonlinear regression model to the relationship between market capitalization and historical returns. It identifies deviations from the expected size-return relationship[25][26] - **Factor Evaluation**: The factor experienced a slight pullback during the week, indicating a temporary shift in market preferences away from size-based strategies[25][26] --- Factor Backtesting Results 1. EP Value Factor - **Weekly Return**: +0.2%[25][26] 2. Momentum Factor - **Weekly Return**: +0.3%[25][26] 3. Nonlinear Size Factor - **Weekly Return**: -0.3%[25][26]

Group 1 - The report identifies that the A-share market is currently experiencing its first "systematic slow bull" since 2005, driven by improved risk appetite and declining risk-free interest rates, alongside China's rise and advantages [1][3][22] - The report outlines that since the initiation of the "924" policy in September 2024, the market has established a long-term bottom, leading to the commencement of the fifth bull market in April 2025 [2][15][19] - The report emphasizes the importance of focusing on "big finance + broad technology" sectors for investment, suggesting a "1+X" allocation strategy to enhance win rates [1][4][22] Group 2 - The report highlights that the historical context of A-share markets includes four previous bull markets, with the first three being "systematic bull markets" characterized by steep upward slopes, while the fourth was a "structural bull market" with a more gradual increase [2][13][14] - It notes that the current "slow bull" market is supported by four key factors: the stable appreciation of the RMB against the USD, positive technical trends, a favorable chip structure, and differentiated sector performance [4][22] - The report suggests that the current market environment is conducive to investments in innovative pharmaceuticals and renewable energy, which are expected to benefit from external advantages and improving market conditions [1][4][22]

Investment Rating - The industry investment rating is "Positive" (maintained) [6] Core Insights - TI is expected to initiate a new round of price increases in August, focusing on industrial control, automotive, and computing-related chip products, which may signal a turning point for the domestic analog sector as demand continues to recover [1][2][4] - The price increase by TI is anticipated to end the price war in the analog industry, allowing domestic analog companies to accelerate their market share growth [2][3] - The price hikes are primarily driven by industrial control and automotive products, with over 40% of industrial control products seeing price increases, benefiting platform-type analog companies [3][4] Summary by Sections - **Price Increase Impact**: TI's price increase is expected to alleviate price pressure in the analog sector, opening up upward potential for domestic companies as demand remains strong [4] - **Key Companies**: Notable companies in the sector include: - Naxin Micro: Leader in automotive-grade analog chips - Sirepu: Leader in industrial control analog chips - Shengbang Co.: Leader in platform-type analog chips - Jiewate: Leader in computing analog chips [5] - **Market Dynamics**: The report indicates that the domestic analog companies have been under pressure due to TI's price competition, but the current price adjustments may lead to improved profitability and market positioning [3][4]

Investment Rating - The industry investment rating is optimistic [1] Core Viewpoints - The report suggests a strategy of buying on dips in anticipation of a peak season in September [1] Price Summary - The SW Steel Index is at 2,509, with a weekly increase of 2.5% and a year-to-date increase of 19.3% [4] - The SW General Steel Index is at 2,589, with a weekly increase of 2.7% and a year-to-date increase of 24.1% [4] - The price of rebar (HRB400 20mm) is 3,330 CNY/ton, showing a weekly decrease of 0.6% and a year-to-date decrease of 2.3% [4] - The iron ore Platts index is at 102 USD/ton, with a weekly increase of 2.2% and a year-to-date increase of 1.5% [4] Inventory Summary - Total social inventory of five major steel products is 962,000 tons, with a weekly increase of 2.2% and a year-to-date increase of 26.8% [5] - Total inventory at steel mills is 413,000 tons, with a weekly increase of 0.8% and a year-to-date increase of 17.9% [5] - Port inventory of iron ore is 13,715,000 tons, with a weekly increase of 0.4% and a year-to-date increase of 7.7% [5] Supply and Demand - The report indicates a steady production level, with weekly output of five major steel products at approximately 1,000,000 tons [9] - The average daily molten iron production is projected to remain stable [9] Stock Performance - The report highlights the stock performance of several companies, with notable increases in some stocks while others have seen declines [19]