Investment Rating - The investment rating for the company is upgraded to "Buy" from "Hold" [5] Core Views - The company has a solid revenue growth trajectory, with a focus on smart display technologies, including smart TVs, interactive displays, and innovative display products [1][15] - The smart TV segment is expected to benefit from emerging market growth, leveraging flexible supply chain advantages [2][50] - The interactive display business is driven by stable core customers and supportive policies, indicating potential for growth [3] - The innovative display segment shows strong revenue growth, with a compound annual growth rate (CAGR) of 90.1% from 2022 to 2024 [4] Summary by Sections Company Overview - The company, established in 1995, has a diverse product portfolio including smart interactive panels, innovative display products, professional display products, and smart TVs [1][15] - Revenue increased from 6.85 billion to 15.59 billion yuan from 2018 to 2024, with a CAGR of 14.7% [1][28] Smart TV Business - The smart TV segment is a stable revenue source, with revenue growing from 4.236 billion yuan in 2018 to 9.528 billion yuan in 2024, representing a CAGR of 14.5% [53] - The company ranks among the top three in global TV shipments for 2024, with a shipment increase of 12% in the first five months of 2025 [54] - The business primarily serves emerging markets, focusing on small to medium regional brands, which allows for stable margins [59] Interactive Display Business - The interactive display products are mainly sold to major global brands, with significant market shares held by SMART and Promethean [3] - The company has established stable partnerships with leading educational display brands, driving growth in this segment [3] Innovative Display Products - Revenue from innovative display products is projected to grow from 420 million yuan in 2022 to 1.519 billion yuan in 2024, with a CAGR of 90.1% [4] - The company is actively developing new products, including high-end OLED screens and AI interactive glasses, enhancing its product matrix [4] Financial Forecast and Valuation - The company is expected to achieve revenues of 17.575 billion, 19.591 billion, and 21.461 billion yuan in 2025, 2026, and 2027, respectively, with year-on-year growth rates of 12.8%, 11.5%, and 9.5% [8] - Projected net profits for 2025, 2026, and 2027 are 1.05 billion, 1.27 billion, and 1.46 billion yuan, with corresponding year-on-year growth rates of 25.8%, 21.2%, and 15.1% [8]

证券研究报告|宏观点评报告 [Table_Date] 2025 年 06 月 25 日 [Table_Title] 资产配置日报：担心踏空 | [Table_Title2] 国内市场表现 | | | | | | --- | --- | --- | --- | --- | | 指 数 | 收 盘 | 涨 跌 | 幅度（%） | 五日走势 | | 上证指数 | 3455.97 | 35.41 | 1.04% | | | 沪 深300指 数 | 3960.07 | 56.03 | 1.44% | | | 中证可转债指数 | 441.46 | 3.50 | 0.80% | | | 7-10年国开债指数 | 266.85 | -0.20 | -0.07% | | | 3-5年隐含AA+信用指数 | 189.95 | -0.03 | -0.01% | | 复盘与思考: 6 月 25 日，权益市场放量上涨，一定程度上与稳市资金的参与相关，更关键的是资金"跟注"倾向显现， 担心"踏空"的情绪有所发酵；股市情绪持续压制，叠加跨季资金面边际收敛，债市收益率进一步回调，长端品 种弱于短端。 复盘各类资产表现，股市，大盘股指中，上证 ...

Investment Rating - The report assigns a "Buy" rating to the company with a target price of HKD 120, compared to the latest closing price of HKD 78 [4]. Core Viewpoints - The company, Dekang Agriculture and Animal Husbandry, is recognized as a rising star in the industry, demonstrating strong learning and innovation capabilities. It has creatively developed a family farm model for pig breeding and fattening, achieving leading breeding results [1][2]. - The company’s service-enabled family farms have increased from 2,011 households at the end of 2020 to 2,608 households by May 2023, with the number expected to grow significantly in the coming years [2]. - The report highlights the company's cost advantages, with a projected total cost of approximately HKD 12.27 per kilogram by April 2025, leading to a per-head profit of HKD 348, positioning it as a leader in the industry [2][4]. Summary by Sections 1. Family Farm Model - The family farm model is seen as highly viable under the national rural revitalization strategy, providing significant policy advantages and reducing environmental and disease risks compared to large-scale self-breeding operations [3][16]. - The model allows for smaller-scale operations, which are less prone to environmental and disease challenges, thus enhancing overall industry efficiency and supporting rural revitalization [3][22]. 2. Cost Leadership - The company has achieved a leading position in cost control due to its advanced breeding systems, excellent management, and light-asset model, with total costs decreasing consistently over the years [4][35]. - The breeding system has been developed through significant investment and has resulted in the company’s breeding performance ranking first in the nation for certain pig breeds [7][42]. 3. Growth Potential - The report anticipates that the number of family farms served by the company will continue to rise, with projections of 3,275, 4,500, and 6,200 households from 2025 to 2027, respectively [2][8]. - The company is expected to benefit from the ongoing transformation in the domestic pig farming industry, positioning itself as a potential growth leader [2][8]. 4. Financial Forecast - The projected total revenue for the company is expected to reach HKD 28.22 billion, HKD 33.75 billion, and HKD 46.32 billion from 2025 to 2027, with net profits of HKD 3.70 billion, HKD 3.67 billion, and HKD 6.97 billion, respectively [11][8]. - The report indicates that the company’s earnings per share (EPS) will be HKD 9.52, HKD 9.43, and HKD 17.92 for the same period, reflecting strong financial performance [11][8].

Market Overview - On June 24, the equity market experienced a significant surge, primarily driven by the ceasefire between Iran and Israel and the participation of stabilizing funds, with notable strength in the non-bank and technology sectors [2][3] - Major stock indices saw broad increases, with the Shanghai Composite Index rising by 1.15%, the CSI 300 by 1.20%, and the ChiNext Index by 2.30% [2] - The bond market continued its upward trend, with the yield on the 10-year government bond rising by 0.6 basis points and the 30-year bond by 1.35 basis points [2][4] Oil and Gold Market - Following the ceasefire announcement, market risk aversion decreased sharply, leading to significant declines in oil and gold prices, with WTI crude oil and Brent crude oil futures dropping by 8.95% and 7.62% respectively [3] - Gold prices also fell, retreating from a high of $3,367 per ounce to around $3,310 per ounce due to reduced geopolitical risks [3] Bond Market Dynamics - The central bank's substantial net injection of liquidity helped stabilize the funding environment as the market entered a cross-quarter week [4] - The overnight funding rates showed a downward trend, with the R001 and DR001 rates remaining stable at 1.44% and 1.37% respectively [4] - The issuance of long-term government bonds saw a slight increase in yield, with the 30-year bond yield rising to 1.85% [6] Equity Market Trends - The A-share market saw a volume increase, with the total trading volume reaching 1.45 trillion yuan, up by 301.1 billion yuan from the previous day [7] - The surge was attributed to the easing of geopolitical tensions and the influx of stabilizing funds, particularly in sectors that had previously underperformed [7] - The market's strong performance suggests a temporary alleviation of the "crisis" sentiment that had been building [7] Sector Performance - The non-bank financial sector saw a notable increase, with the SW Non-Bank Financial Index rising by 2.68%, indicating a shift in market dynamics [9] - The Hong Kong market also experienced gains, with the Hang Seng Index and Hang Seng Tech Index rising by 2.06% and 2.14% respectively [10] Future Outlook - The market is expected to remain within a consolidation framework established since mid-May, with potential upward pressure from profit-taking sentiments [8] - The upcoming military parade on September 3 may also influence market sentiment, particularly in sectors related to defense and technology [10]

[Table_Date] 2025 年 06 月 23 日 [Table_Title] 资产配置日报：主线未明 [Table_Title2] 复盘与思考: 6 月 23 日，权益行情迎来反弹，银行和小微盘显著上涨，"哑铃型"的市场结构再度回归；债市收益率先下 后上，整体延续窄幅震荡格局，各期限单日变化不到 0.5bp。 复盘各类资产表现，股市，大盘股指翻红，上证指数、沪深 300、中证红利分别上涨 0.65%、0.29%、 0.25%；国内科技板块小幅反弹，科创 50、创业板指分别上涨 0.38%、0.39%，港股的恒生科技上涨 1.05%；小微 盘明显上涨，中证 1000、万得微盘股指上涨 1.31%、2.38%。债市，10 年国债活跃券收益率小幅上行 0.2bp，30 年国债活跃券持平于 1.84%；10 年、30 年国债期货主力合约小幅下跌 0.01%、0.04%。 中东地缘政治局势继续扰动国际大宗商品市场，原油价格高开低走，黄金表现平淡。周日（6 月 22 日）， "美国攻击伊朗核设施"及"伊朗议会提议关闭霍尔木兹海峡"等消息持续发酵，全球避险情绪一度急剧升温。 受此推动，今日开盘后美国 WTI 原油 ...

证券研究报告|固收研究报告 [Table_Date] 2025 年 06 月 23 日 [Table_Title] 上行超 20bp，关注深圳地铁长债修复机会 [Table_Title2] 城投解惑系列之十四 [Table_Summary] ►长债高估值成交活跃，收益率一度上行超 20bp 2025 年 5 月以来，深圳市地铁集团有限公司（简称"深圳地铁"） 债券二级市场高估值成交迅速增加，长债成交高估值幅度更大。据 经纪商成交数据统计，2025 年 4-5 月深圳地铁 5 年内债券成交偏离 估值幅度不大，平均在 1bp 以内，而 10 年以上则高估值 2.1bp 和 10.86bp 成交，平均成交价格和期限也在近一月里快速抬升。密集 的高估值成交使深圳地铁长债收益率一度上行超 20bp，走出不同于 整体城投债的走势。背后的原因主要是部分机构投资者担忧作为万 科的第一大股东，深圳地铁频繁"输血"救助万科，股权投资造成 重大损失，信用资质可能会受万科拖累 ►地产舆情或扰动城投债估值，市场消化后利差多压缩 由于房地产市场持续低迷，近年来多家粤系民营房地产企业接连暴 雷。在此背景下，区域城投平台也出现了与地产相关的 ...

Investment Rating - The industry rating is "Recommended" [3] Core Insights - The report highlights that the sentiment in the pork market is supporting an upward shift in pork prices, with the average price for external three-line pigs at 14.20 CNY/kg, reflecting a week-on-week increase of 1.43% [2][12] - The report emphasizes the importance of increasing soybean and oilseed production, with a focus on enhancing yield through advanced agricultural practices and the promotion of genetically modified varieties [1][11] - The report suggests that while short-term consumer demand is recovering, supply remains relatively loose, but medium to long-term projections indicate that pork prices may exceed expectations in the second half of 2025 due to slow recovery in production capacity [2][12] Summary by Sections Planting Industry Chain - The Ministry of Agriculture and Rural Affairs held a meeting to discuss the production and demand situation for soybeans and oilseeds, emphasizing the need to enhance production capacity and implement key measures for yield improvement [1][11] - The report identifies potential beneficiaries in the planting sector, including Beidahuang and Suqian Agricultural Development, and recommends companies with a strong first-mover advantage in the seed industry such as Dabeinong and Longping High-Tech [1][11] Swine Farming - The average price of external three-line pigs is reported at 14.20 CNY/kg, with a significant increase in slaughter volume and consumer demand noted [2][12] - The report indicates that the number of breeding sows has decreased slightly, and the profitability of self-breeding operations has turned positive, suggesting a potential for recovery in the swine sector [2][12] - Recommended stocks in the swine farming sector include companies like Muyuan Foods, Wens Foodstuff Group, and DeKang Agriculture [2][12] Key Agricultural Product Data Tracking - Corn: The average price is 2412.94 CNY/ton, with a week-on-week increase of 0.54% [26] - Wheat: The average price is 2440.61 CNY/ton, with a week-on-week increase of 0.46% [29] - Soybeans: The average price is 3946.32 CNY/ton, with a week-on-week increase of 0.21% [40] - Cotton: The average price is 14760.00 CNY/ton, with a week-on-week increase of 0.15% [45] Feed and Vitamin Prices - The average price of pig feed is reported at 2.69 CNY/kg, with a week-on-week increase of 0.75% [51] - Vitamin E prices have decreased by 10.02% to 80.80 CNY/kg [51][59]

[Table_Summary] 近两周，利率债震荡下行，机构延续信用债利差挖掘思路，长久期品 种成为焦点，10 年信用利差大幅压缩。其中，6 月第二周 5 年、10年 信用利差分别收窄 6bp、8bp，6 月第三周 10 年利差继续收窄 6bp。 谁在买长久期信用债？从机构行为来看，近期基金和保险主要在买入 7-10 年信用债，其他资管产品对长久期信用债的需求也明显增加。基 金 6 月以来加大了长久期信用债的交易配置力度，尤其是 7-10 年这一 期限，净买入占比从 5 月的 2%升至 9%，近两周净买入量分别为 47、 57 亿元。此外，6 月第二、三周，保险净买入 7-10 年的规模也较大， 分别为 20、31 亿元，均占当周净买入总规模的 32%。其他资管产品 5 月仅净买入 9 亿元 5-30 年信用债，6 月以来增加至 139 亿元。 银行理财则在 6 月减少了 7 年以上长信用债的买入规模，或为跨季做 准备。5 月理财分别净买入 27、20 亿元 7-10 年、10-30 年信用债，占 当月净买入规模的7%、5%。6月以来，理财对长信用债的配置需求明 显转弱，7-10年、10-30年净买入规模降至 ...

Quantitative Models and Construction Methods 1. Model Name: Position Parameter Table - **Model Construction Idea**: The model aims to predict future index returns by identifying the relationship between historical price-volume patterns and future performance. It establishes a multi-to-one mapping between historical periods and future periods to construct a position parameter table[40][49]. - **Model Construction Process**: 1. Fix the future return period to 20 trading days for monthly portfolio construction[40]. 2. Traverse historical price-volume periods ranging from 5 to 240 days to identify the most effective historical period for prediction[40]. 3. Use polar coordinates to represent index states, where the radial distance (ρ) is calculated using the Mahalanobis distance: $ \rho = \sqrt{(x-y)^T \cdot \Sigma^{-1} \cdot (x-y)} $ Here, $x$ represents the current price and volume, $y$ represents historical price and volume, and $Σ$ is the covariance matrix[14][15]. 4. The polar angle (θ) is calculated using the arctangent function: $ \theta = \arctan2(\text{Volume Change}, \text{Price Change}) $[15]. 5. Divide the polar coordinate plane into 80 regions by segmenting the radial distance into 5 equal parts and the polar angle into 16 equal parts[31]. 6. Map each region to the average future 20-day return of indices within that region[46]. 7. Expand the table along two dimensions: - Dimension 1: Calculate the relationship between multiple historical periods and future returns for a single historical date[49]. - Dimension 2: Calculate the relationship between multiple historical dates and future returns for a single historical period[47][49]. - **Model Evaluation**: The model effectively captures historical price-volume patterns and their relationship with future returns, enabling the construction of robust ETF portfolios[40][49]. 2. Model Name: ETF Selection Based on Position Parameter Table - **Model Construction Idea**: This model selects ETFs by matching historical price-volume patterns with regions in the position parameter table that correspond to high future returns[51]. - **Model Construction Process**: 1. At each rebalancing point, calculate the price-volume patterns of indices over multiple historical periods[51]. 2. Match these patterns with the position parameter table to identify regions with the highest future return rankings[51]. 3. Select indices within these optimal regions to construct the ETF portfolio[51]. - **Model Evaluation**: The model demonstrates strong predictive power and adaptability, as evidenced by its performance across different time windows[51][53]. --- Model Backtesting Results 1. Position Parameter Table - **Annualized Return**: 17.27% (Full Sample), 14.65% (Fixed Window), 17.45% (Rolling Window)[65] - **Cumulative Return**: 351.83% (Full Sample), 264.93% (Fixed Window), 358.64% (Rolling Window)[65] - **Excess Return (2021-2025/6/20)**: - Fixed Window: 35.81% (ETF Portfolio: +15.82%, Equal-Weighted ETF: -14.72%)[57] - Rolling Window: 77.51% (ETF Portfolio: +51.38%, Equal-Weighted ETF: -14.72%)[60] 2. ETF Selection Based on Position Parameter Table - **Annual Returns**: - 2021: 6.11% (Fixed Window), 15.96% (Rolling Window), 13.31% (Equal-Weighted ETF)[65] - 2022: -9.28% (Fixed Window), -5.13% (Rolling Window), -22.15% (Equal-Weighted ETF)[65] - 2023: -4.51% (Fixed Window), -6.88% (Rolling Window), -8.35% (Equal-Weighted ETF)[65] - 2024: 16.03% (Fixed Window), 29.12% (Rolling Window), 7.18% (Equal-Weighted ETF)[65] --- Quantitative Factors and Construction Methods 1. Factor Name: Price-Volume Pattern (Polar Coordinates) - **Factor Construction Idea**: This factor quantifies the price-volume relationship of indices using polar coordinates to identify distinct movement patterns[15][19]. - **Factor Construction Process**: 1. Represent price and volume changes in a Cartesian coordinate system, dividing them into four quadrants: - Quadrant 1: Price up, Volume up (0°-90°) - Quadrant 2: Price down, Volume up (90°-180°) - Quadrant 3: Price down, Volume down (180°-270°) - Quadrant 4: Price up, Volume down (270°-360°)[19][20]. 2. Transition to polar coordinates, where the radial distance (ρ) measures the magnitude of change, and the polar angle (θ) indicates the direction of change[15][19]. 3. Use historical data to map price-volume patterns to future returns, identifying regions with high predictive power[28][31]. - **Factor Evaluation**: The factor provides a precise and intuitive representation of price-volume dynamics, enabling effective prediction of future index performance[19][31]. --- Factor Backtesting Results 1. Price-Volume Pattern (Polar Coordinates) - **Future 20-Day Return by Region**: - Regions with high radial distances and specific angular ranges (e.g., 0°-90° for strong upward momentum) exhibit higher average returns[28][31]. - Historical data shows that indices in regions corresponding to "Volume Up + Price Up" (0°-90°) and "Volume Down + Price Down" (180°-270°) tend to perform better in the future[25][28].

证券研究报告|行业点评报告 [Table_Date] 2025 年 06 月 22 日 [Table_Title] Marvell 上调预期，拉动海外算力链持续上涨 [Table_Title2] 通信行业 [Table_Summary] 1、Marvell 上调数据中心 Capex 与 ASIC 预期指引，引发海外算 力链持续上涨 美东时间 6 月 18 日，Marvell 举办 AI 投资者日，预计 2028 年 数据中心资本开支将超过一万亿美元。同时进一步上调数据中 心市场规模 2028 年预期至 940 亿美元，较 2024 年 4 月的预期 750 亿美元上调 26%，其中上调定制计算芯片（XPU 和 XPU 配套 芯片）市场规模指引 37%。 2、投资建议 算力需求在过去两年受益于算力芯片催生一波跳跃式需求增 长，受数据源限制、密度功耗、Scaling Law 效率递减等多重 因素影响下开源与闭源模型效用逐渐达到同一等级，在 DeepSeek 影响下训练算力成本大幅下降，对于主权算力以及算 力资本开支下滑的担忧不止。 尽管如此，OpenAI 其营收规模与商用付费客户也持续呈现快速 增长，包括 Ora ...