Investment Rating - The investment rating for the company is "Buy" [1] Core Views - The company is undergoing a significant cloud transformation, which is expected to drive revenue growth and lead to a gradual narrowing of losses, with a forecast to achieve breakeven by 2025 [3][6] - The integration of AI capabilities into ERP systems is a key focus, with the launch of the DeepSeek model enhancing the company's SaaS applications [4][45] - The company has a strong competitive advantage in the SME market, with high renewal rates and significant growth in large enterprise cloud revenue [5][6] Summary by Sections 1. Cloud Transformation and Revenue Growth - The company has transitioned from traditional ERP to cloud services, with revenue increasing from 1.586 billion in 2015 to 5.679 billion in 2023, reflecting a CAGR of 17.29% [3][24] - Losses peaked at 360 million in 2020 due to increased R&D and the cessation of certain ERP product sales, but narrowed to 143 million in 2023, with expectations of breakeven by 2025 [3][25] 2. AI Integration in ERP - The company has been implementing AI strategies since 2017, with significant advancements in financial and HR management through partnerships and the development of large-scale AI models [4][46] - The launch of the "Cang Qiong GPT" model in 2023 represents a major step in enhancing the company's AI capabilities within its ERP offerings [4][46] 3. Competitive Positioning - The company has demonstrated a strong competitive edge in the SME market, achieving a cloud revenue of 1.642 billion in the first half of 2024, with renewal rates of 95% for SMEs and 92% for small enterprises [5][6] - In the large enterprise segment, cloud revenue reached 546 million in the first half of 2024, marking a year-on-year growth of 38.9% [5][6] 4. Financial Projections - Revenue projections for 2024, 2025, and 2026 are estimated at 6.484 billion, 7.561 billion, and 8.860 billion respectively, with net profits expected to turn positive by 2025 [6][10] - The company's subscription ARR reached 3.15 billion in the first half of 2024, indicating strong growth potential [5][38]

Investment Rating - The investment rating for the company is "Buy" [1] Core Views - The company is undergoing a significant cloud transformation, which is expected to drive revenue growth and lead to a gradual narrowing of losses, with a forecast to achieve breakeven by 2025 [3][6] - The integration of AI capabilities into ERP systems is positioned to enhance the company's competitive edge and facilitate intelligent transformation [4][5] Summary by Sections 1. Business Transformation and Growth - The company has transitioned from traditional ERP to cloud services, with revenue increasing from 1.586 billion yuan in 2015 to 5.679 billion yuan in 2023, reflecting a CAGR of 17.29% [3][24] - The cloud service revenue accounted for 83.25% of total revenue in the first half of 2024, indicating a rapid shift from traditional ERP services [26][29] - The company expects to narrow its losses to 0.78 billion yuan in 2024 and achieve a net profit of 1.97 billion yuan in 2025 [6][10] 2. AI Integration and Market Position - The company has integrated AI capabilities into its ERP offerings, launching the "DeepSeek" model to enhance its SaaS applications [4][45] - The AI-driven products are expected to optimize processes in financial and human resource management, improving efficiency and decision-making [45][46] - The ERP software market in China is projected to grow from 385 billion yuan in 2021 to 682 billion yuan by 2027, with a CAGR of approximately 11% [50] 3. Financial Performance and Projections - The company forecasts revenues of 6.484 billion yuan, 7.561 billion yuan, and 8.860 billion yuan for 2024, 2025, and 2026 respectively, with a return to profitability expected in 2025 [6][10] - The subscription ARR for cloud services reached 3.15 billion yuan in the first half of 2024, with a significant growth trajectory [38][40] - The company's gross margin is expected to recover as operational efficiencies improve, following a period of high R&D and sales expenses [34][36]

Investment Rating - The investment rating for the company is "Buy" (maintained) [1] Core Views - Recently, the company's subsidiary, Youka Technology, signed a strategic cooperation agreement with Tianyi Cloud to collaborate in areas such as intelligent networking, autonomous driving, and computing infrastructure, aiming to promote large-scale applications in the intelligent vehicle sector [4][5] - The partnership will focus on six dimensions, including autonomous driving, cloud security, edge computing, embodied intelligence, low-altitude economy, and industry standards [5] - The autonomous driving industry is accelerating, with developments from competitors like Tesla and BYD, which may enhance the company's market position [6][7] - The company is expected to benefit from supportive policies for vehicle networking and aims to expand its overseas business, targeting significant growth opportunities [10] Financial Summary - The company forecasts net profits for 2024-2026 to be 94 million, 204 million, and 303 million yuan, respectively, with corresponding EPS of 0.70, 1.52, and 2.26 yuan [11] - Revenue is projected to grow from 521 million yuan in 2023 to 1.531 billion yuan in 2026, reflecting a compound annual growth rate [13][16] - The gross margin is expected to stabilize around 40% in the coming years, with ROE increasing from 13.7% in 2023 to 29.1% in 2026 [13][17]

Quantitative Models and Construction Methods Model Name: MP-Adv-DRL-Cor - **Model Construction Idea**: The model uses convolutional neural networks (CNN) to capture dynamic patterns in asset prices and WaveNet to model cross-asset dependencies. It combines these inputs with deep reinforcement learning (DRL) to solve multi-period Bellman equations for optimal long-term portfolio allocation[2][24][25] - **Model Construction Process**: - **CNN for Dynamic Price Sequence Information Extraction**: CNN is used to extract dynamic features from asset price sequences. The process involves several layers including input, convolution, pooling, fully connected, and softmax layers[25][27] - **Convolution Layer Formula**: $$ \mathbf{y}_{j,n}=\delta\Bigg{(}\mathbf{b}+\sum_{l=0}^{Z}\sum_{m=0}^{M}\varpi_{l,m}\mathbf{x}_{j+l,n+m}^{\prime}\Bigg{)} $$ where $\delta$ is the activation function, $\mathbf{b}$ is the shared bias parameter, $Z$ and $M$ are the length and width of the local receptive field, $\varpi_{l,m}$ are the shared weight parameters, and $\mathbf{x}_{j+l,n+m}^{\prime}$ is the input matrix data[25] - **Activation Function Formula**: $$ \delta(x^{\prime})=ReLU(x^{\prime})=\left\{\begin{array}{c}x^{\prime},x^{\prime}\geq0\\ 0,x^{\prime}<0\end{array}\right. $$ ReLU function is used to prevent overfitting and enhance non-linear expression capability[25] - **WaveNet for Cross-Asset Dependency Information Extraction**: WaveNet captures time-varying dependencies between assets using convolution layers and causal convolutions with dilation operations[28] - **WaveNet Dependency Formula**: $$ \mathbf{q}_{i,t}(\mathbf{r}_{t})=\left(\varphi(\mathbf{r}_{i,t})\odot(\mathbf{1}\mathbf{\omega}_{0}^{\mathrm{T}})+\sum_{j=1}^{N}\varphi(\mathbf{r}_{j,t})\odot(\mathbf{1}\mathbf{\omega}_{j}^{\mathrm{T}})\right)\mathbf{1}+\mathbf{a} $$ where $\varphi$ is the neural network function, $\mathbf{a}$ is the bias term, and $\mathbf{r}_{t}$ is the input stream[28] - **DRL for Multi-Period Portfolio Decision Making**: Combines dynamic asset price features and dependency information as inputs for the deterministic policy gradient (DPG) model to optimize portfolio allocation[29] - **MDP and Multi-Period Bellman Equation**: $$ V_{\pi}(s)=E_{\pi}\left(U_{t,h}\left|s_{t}=s\right.\right)=E_{\pi}\left(\left.\sum_{k=1}^{h}\gamma^{k-1}u_{t+k}\left|s_{t}=s\right.\right) $$ where $V_{\pi}(s)$ is the state value function, $U_{t,h}$ is the multi-period utility function, and $\gamma$ is the time preference parameter[32] - **DRL Objective Function**: $$ \max_{\theta}J(\pi_{\theta})=\mathbb{E}_{\pi_{\theta}(h,n)}\big{(}U_{t,h}(u_{t+1}(\omega_{t+1}),u_{t+2}(\omega_{t+2}),\ \cdot\ \cdot\ \cdot,u_{t+h}(\omega_{t+h}))\big{)} $$ where $\theta$ are the neural network parameters[36] - **Model Evaluation**: The MP-Adv-DRL-Cor method generally outperforms other methods in terms of annual return, Sharpe ratio, and maximum drawdown across different holding periods, risk aversion levels, and transaction costs[3][52][56] Model Backtesting Results MP-Adv-DRL-Cor Model Performance Metrics - **Holding Period h = 1** - **Annual Return**: 12.48% (S&P 100), 8.808% (DJIA), 13.58% (S&P/TSX Composite)[53] - **Annual Volatility**: 24.57% (S&P 100), 21.43% (DJIA), 25.35% (S&P/TSX Composite)[53] - **Sharpe Ratio**: 0.508 (S&P 100), 0.411 (DJIA), 0.536 (S&P/TSX Composite)[53] - **Maximum Drawdown**: 39.80% (S&P 100), 35.34% (DJIA), 48.01% (S&P/TSX Composite)[53] - **Turnover**: 0.007 (S&P 100), 0.007 (DJIA), 0.008 (S&P/TSX Composite)[53] - **Holding Period h = 5** - **Annual Return**: 25.72% (S&P 100), 19.79% (DJIA), 17.91% (S&P/TSX Composite)[53] - **Annual Volatility**: 28.89% (S&P 100), 33.51% (DJIA), 21.58% (S&P/TSX Composite)[53] - **Sharpe Ratio**: 0.890 (S&P 100), 0.590 (DJIA), 0.830 (S&P/TSX Composite)[53] - **Maximum Drawdown**: 39.19% (S&P 100), 51.72% (DJIA), 37.94% (S&P/TSX Composite)[53] - **Turnover**: 0.087 (S&P 100), 0.080 (DJIA), 0.009 (S&P/TSX Composite)[53] - **Holding Period h = 22** - **Annual Return**: 22.37% (S&P 100), 19.23% (DJIA), 18.42% (S&P/TSX Composite)[53] - **Annual Volatility**: 37.08% (S&P 100), 32.49% (DJIA), 22.10% (S&P/TSX Composite)[53] - **Sharpe Ratio**: 0.603 (S&P 100), 0.592 (DJIA), 0.833 (S&P/TSX Composite)[53] - **Maximum Drawdown**: 44.13% (S&P 100), 52.63% (DJIA), 38.65% (S&P/TSX Composite)[53] - **Turnover**: 0.099 (S&P 100), 0.103 (DJIA), 0.020 (S&P/TSX Composite)[53] - **Holding Period h = 36** - **Annual Return**: 29.21% (S&P 100), 28.88% (DJIA), 21.38% (S&P/TSX Composite)[53] - **Annual Volatility**: 36.14% (S&P 100), 34.32% (DJIA), 27.08% (S&P/TSX Composite)[53] - **Sharpe Ratio**: 0.808 (S&P 100), 0.841 (DJIA), 0.790 (S&P/TSX Composite)[53] - **Maximum Drawdown**: 32.09% (S&P 100), 44.24% (DJIA), 40.83% (S&P/TSX Composite)[53] - **Turnover**: 0.170 (S&P 100), 0.109 (DJIA), 0.074 (S&P/TSX Composite)[53] - **Holding Period h = 66** - **Annual Return**: 27.51% (S&P 100), 17.40% (DJIA), 15.50% (S&P/TSX Composite)[53] - **Annual Volatility**: 39.43% (S&P 100), 31.32% (DJIA), 37.11% (S&P/TSX Composite)[53] - **Sharpe Ratio**: 0.698 (S&P 100), 0.555 (DJIA), 0.418 (S&P/TSX Composite)[53] - **Maximum Drawdown**: 66.10% (S&P 100), 36.22% (DJIA), 55.38% (S&P/TSX Composite)[53] - **Turnover**: 0.107 (S&P 100), 0.092 (DJIA), 0.197 (S&P/TSX Composite)[53] Quantitative Factors and Construction Methods Factor Name: Risk Aversion Coefficient (λ) - **Factor Construction Idea**: The risk aversion coefficient influences the

万马科技（ [Table_StockNameRptType] 300698） 公司点评 [Table_Author] 分析师：陈晶 执业证书号：S0010522070001 电话：15000930816 邮箱：chenjing@hazq.com [Table_CompanyReport] 相关报告 1.推出遨云自动驾驶方案，积极探索 robotaxi 商业落地 2024-11-02 2.盈利能力快速提升，自动驾驶落地 生花 2024-03-31 主要观点： ⚫[Table_Summary] 事件回顾： 战略合作天翼云，智驾能力赋能具身智能和低空出行 | 投资评级：买入（维持） [Table_Rank] | | --- | | 报告日期： 2025-03-13 | | [Table_BaseData] 收盘价（元） | 43.58 | | --- | --- | | 近 12 个月最高/最低（元） | 53.04/25.63 | | 总股本（百万股） | 134 | | 流通股本（百万股） | 119 | | 流通股比例（%） | 88.47 | | 总市值（亿元） | 58 | | 流通市值（亿元） | 52 ...

Investment Rating - The investment rating for the company is "Buy" (maintained) [1] Core Views - The recent strategic partnership between the company's subsidiary, Youka Technology, and Tianyi Cloud aims to enhance capabilities in intelligent connected vehicles, autonomous driving, and computing infrastructure, promoting large-scale applications in smart vehicles and other intelligent industries [4][5] - The company is actively exploring the commercial deployment of its "Aoyun" autonomous driving solution, which is positioned to compete with Tesla's Full Self-Driving (FSD) system, leveraging advantages such as 5G dual cards and private network services [6][7] - The integration of connected vehicle technology with autonomous driving capabilities is expected to extend into fields such as embodied intelligence and low-altitude travel, marking a significant shift in the smart automotive industry [7][10] Financial Summary - The company forecasts a net profit attributable to shareholders of 94 million, 204 million, and 303 million yuan for 2024, 2025, and 2026 respectively, with corresponding EPS of 1.52 and 2.26 yuan [11] - Revenue is projected to grow from 590 million yuan in 2024 to 1.531 billion yuan in 2026, reflecting a compound annual growth rate (CAGR) of 53.7% [13][16] - The gross margin is expected to stabilize around 40% by 2026, with a return on equity (ROE) projected to reach 29.1% [13][17]

[Table_StockNameRptType] 宝丰能源（600989） 公司点评 内蒙一期如期投产，煤炭价格下行带来盈利弹性 | 投资评级：买入（维持） [Table_Rank] | | | --- | --- | | 报告日期： | 2025-03-13 | | [Table_BaseData] 收盘价（元） | 17.49 | | 近 12 个月最高/最低（元） | 17.84/14.20 | | 总股本（百万股） | 7,333 | | 流通股本（百万股） | 7,333 | | 流通股比例（%） | 100.00 | | 总市值（亿元） | 1,283 | | 流通市值（亿元） | 1,283 | [公司价格与沪深 Table_Chart] 300 走势比较 -20% -10% 0% 10% 20% 30% 3/13 5/13 7/13 9/13 11/13 1/13 宝丰能源 沪深300 [Table_Author] 分析师：王强峰 [Table_Author] 分析师：王强峰 执业证书号：S0010522110002 电话：13621792701 邮箱：wangqf@hazq.com 执业证书 ...

Investment Rating - Investment Rating: Buy (Maintain) [2] Core Views - The company achieved a revenue of 32.983 billion yuan in 2024, a year-on-year increase of 13.21%, and a net profit attributable to shareholders of 6.338 billion yuan, up 12.16% year-on-year [5] - The fourth quarter saw a recovery in production and sales after maintenance in the third quarter, with a revenue of 8.708 billion yuan, a year-on-year decrease of 0.30%, but a quarter-on-quarter increase of 18.04% [6] - The company is expected to benefit from the commissioning of its Inner Mongolia project, which will significantly enhance its earnings elasticity in 2025 [12] Summary by Sections Financial Performance - In 2024, the company reported a net profit of 6.338 billion yuan, with a basic earnings per share of 0.87 yuan [5] - The fourth quarter's net profit was 1.801 billion yuan, reflecting a year-on-year increase of 2.33% and a quarter-on-quarter increase of 46.16% [6] - The company’s revenue is projected to grow significantly in the coming years, with estimates of 54.865 billion yuan in 2025 and 67.308 billion yuan in 2026 [13] Production and Cost Management - The company has optimized its coal procurement sources, resulting in a decrease in average procurement prices for various types of coal in 2024 [8] - The commissioning of new projects, including a 10 million tons/year ethylene project, is expected to provide stable low-cost raw material support [11] - The Inner Mongolia project will enhance the company's production capacity to 5.2 million tons/year, making it the largest coal-to-olefins facility globally [11] Future Outlook - The company is expected to see significant profit growth in 2025, with projected net profits of 13.305 billion yuan, reflecting a year-on-year increase of 109.9% [13] - The ongoing projects in Ningdong and Xinjiang are anticipated to provide long-term growth opportunities [12] - The company maintains a leading position in cost control within the industry, which is expected to solidify its status as a benchmark enterprise [12]

[Table_IndNameRptType] 基础化工 行业周报 国际油价持续回落，农药、制冷剂等价格上涨 [Table_IndRank] 行业评级：增持 报告日期： 2025-03-13 [Table_Chart] 行业指数与沪深 300 走势比较 -31% -17% -4% 10% 23% 37% 12/23 3/24 6/24 9/24 基础化工 沪深300 [Table_Author] 分析师：王强峰 执业证书号：S0010522110002 电话：13621792701 邮箱：wangqf@hazq.com 分析师：刘天其 执业证书号：S0010524080003 电话：17321190296 邮箱：liutq@hazq.com 主要观点： ⚫[Table_Summary] 行业周观点 本周（2025/3/1-2025/3/7）化工板块整体涨跌幅表现排名第 13 位， 涨跌幅为+2.27% ，走势处于市场整体走势中上游。上证综指涨跌幅 为+1.56%，创业板指涨跌幅为+1.61%，申万化工板块跑赢上证综指 0.71 个百分点，跑赢创业板指 0.66 个百分点。 ⚫ 2025 年化工行业景气度将延续分 ...

[Table_IndNameRptType] 基础化工 行业周报 国际油价持续回落，农药、制冷剂等价格上涨 [Table_IndRank] 行业评级：增持 报告日期： 2025-03-13 [Table_Chart] 行业指数与沪深 300 走势比较 -31% -17% -4% 10% 23% 37% 12/23 3/24 6/24 9/24 基础化工 沪深300 [Table_Author] 分析师：王强峰 执业证书号：S0010522110002 电话：13621792701 邮箱：wangqf@hazq.com 分析师：刘天其 执业证书号：S0010524080003 电话：17321190296 邮箱：liutq@hazq.com 主要观点： （2）配额政策落地在即，三代制冷剂有望进入高景气周期。24 年起 三代制冷剂供给进入"定额+持续削减"阶段，同时二代制冷剂加速削 减，四代制冷剂因为专利问题价格居高不下难以形成替代，制冷剂供 给端持续缩减。同时随着热泵、冷链市场发展以及空调存量市场持续 扩张，叠加东南亚国家制冷剂需求扩张等因素，需求端保持稳定增长。 未来制冷剂市场供需缺口将会持续扩大，制冷剂价格 ...