Group 1: Macro Trends - The global monetary and financial systems may undergo significant changes in the next 5 to 10 years, driven by the development of stablecoins and Real World Assets (RWA) [2] - Stablecoins and RWA could create a parallel, decentralized monetary and financial system outside the current centralized frameworks [2] - The transformation brought by stablecoins and RWA may be as impactful as the advancements in AI on the global economy [2] Group 2: Stablecoins - The trust in centralized accounting systems is declining due to excessive issuance of fiat currencies, particularly after the 2008 financial crisis [16] - Stablecoins, primarily backed by fiat currencies like the US dollar, account for 99% of the stablecoin market since 2014 [17] - The emergence of stablecoins addresses the volatility of cryptocurrencies, allowing for decentralized circulation while maintaining a degree of stability [19] Group 3: RWA (Real World Assets) - RWA represents the tokenization of real-world assets on the blockchain, similar to Asset-Backed Securities (ABS) but utilizing decentralized platforms [24] - The development of RWA could establish a new financial market on the blockchain, allowing investors to manage wealth without reverting to centralized financial systems [25] - RWA can function as a form of currency, enabling transactions without the need to convert assets into fiat currency [30]

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The AI industry is witnessing significant advancements with major companies like Meta and Google launching new products and features, indicating a competitive landscape and innovation drive [1][4][7][21] - Notable funding activities include Delphi's $16 million Series A round led by Sequoia and Thinking Machines Lab's record $2 billion seed round, highlighting investor confidence in AI startups [5][6] - The introduction of Tesla's Robotaxi service marks a significant step in autonomous vehicle deployment, with initial operations in Austin, Texas [17] Summary by Sections 1. AI Industry Dynamics - Meta has recruited four key researchers from OpenAI, which may enhance its AI capabilities following the release of Llama 4 [4] - The competition between Meta and OpenAI has intensified, with significant financial incentives being offered for talent acquisition [4] 2. AI Application Insights - Anthropic has updated its Claude chatbot to allow users to create AI applications without programming knowledge, broadening accessibility [7] - Google has launched the open-source Gemini CLI, which offers extensive features for developers, including high usage limits [8] - The AlphaGenome tool from Google can read large DNA sequences, significantly advancing genetic research capabilities [9] 3. AI Large Model Insights - Microsoft's Mu model, with only 330 million parameters, achieves performance comparable to models with ten times the parameters, showcasing efficiency in AI model design [22] - Sakana AI's new "Reinforcement Learning Teacher" paradigm demonstrates improved training efficiency for AI models, reducing training time significantly [23] 4. Technology Frontiers - CMU has developed a compiler that optimizes large language models, reducing inference latency significantly [24] - Netflix is expanding its VR experiences with a new immersive space, indicating a growing trend in entertainment technology [25] - Microsoft has made a breakthrough in quantum computing, significantly reducing error rates in quantum bits [26]

Group 1 - The report indicates a slight decrease in leverage in the interbank bond market, with a mixed performance in the primary market and overall positive sentiment in the secondary market, leading to an increase in bond duration and active trading of ultra-long bonds [2][4][7] - In the funding market, the demand for expansion has cooled, with a decrease in net inflow for major borrowing parties and an increase in net inflow for major lending parties. The total balance of repos in the interbank market has risen, while the leverage ratio has slightly decreased [4][7][8] - The primary market saw a divergence in bidding multiples, with a rise in the bidding multiple for 10-year government bonds, while the multiples for policy bonds decreased. The spread between primary and secondary prices has widened [17][19] Group 2 - The secondary market has shown active trading in ultra-long bonds, with an increase in turnover rates for 30-year government bonds and a rise in the average duration of medium- and long-term pure bond funds. The total borrowing volume for bonds has decreased, and the proportion of active bonds has also declined [26][30] - Major buyers have increased net purchases of ultra-long bonds, while net purchases of short, medium, and long-term bonds have decreased. Major sellers have increased net sales of medium and long-term bonds, while the selling pressure on short and ultra-long bonds has weakened [26][30][33] - The report highlights that large commercial banks have continued to net buy short-term bonds within 3 years, while maintaining significant net selling pressure on ultra-long bonds of 10 years and above [34][36] Group 3 - In June, the data on wealth management did not show a significant seasonal decline, with a slight increase in wealth management scale during the week of June 22. The total wealth management scale decreased by 204.2 billion yuan, primarily due to a reduction in fixed-income products [34][36] - The fund scale increased by 299.9 billion yuan in June, with both equity and bond funds seeing significant increases. However, the issuance of new bond funds saw a slight decline compared to the previous week [36][37]

Industry Developments - Kolon Industries announced an expansion of its optical PVA film production line in Saijo, Japan, to meet the growing demand for larger polarizer screens, with an expected annual output of 38 million square meters, increasing total capacity from 296 million to 334 million square meters by December 2027[1] - Xinjiang Shuguang Greenhua's 100,000 tons/year BDO and 120,000 tons PBAT project successfully passed acceptance inspection, enhancing the chemical new materials industry base in southern Xinjiang[1] Investment and Financing - Puxin Crystal completed nearly 500 million yuan in B+ round financing, aimed at developing ultra-pure polymer specialty materials, with funds allocated for production line completion and market expansion[1] - Shenzhen Sufang New Energy Technology Co., Ltd. announced the completion of a 10 million yuan angel round financing, focusing on the development of lithium-rich manganese-based cathode materials[2] Market Performance - The Wande New Materials Index (884057.WI) rose by 5.12% during the week of June 23-27, 2025, while the CSI 300 Index increased by 1.95%[3]

偃旗息鼓:全球风险偏好反弹上行 -- 大类资产配置周度点评(20250630) 王子翌(分析师) 02 -386 /6666 本报告导读: 我们调整此前的战术性大类资产配置观点。我们维持对 A 股的战术性标配观点,维 持对国债的战术性标配观点,下修黄金的战术性配置观点至标配,维持对美元的战 术性低配观点。 投资要点: ne Hill - S 黨略 经济修复节奏以及市场对经济景气的预期相对企稳,权益市场表现 较好在一定程度上限制了债市的相对吸引力。此外,资金利率的不 确定性以及市场对央行操作的高度博弈亦限制了利率的下行动能。 参研究报 请务必阅读正文之后的免责条款部分 策略研究 / 2025.06.30 登记编与 □ 我们维持对 A 股的战术性标配观点。投资者对于政策的不确定性消 除提振市场风险偏好中枢,无风险利率的下行有利于A股表现。定 价资金"以我为主",而对复杂多变的外部宏观背景逐渐钝化。总量 政策层面,财政积极发力、货币政策维持宽松;产业层面,中国科 技的突破有利于企业增加信心并增加资本开支。近期市场对 A 股定 价因子的预期亦相对稳定。 我们维持对国债的战术性标配观点。在融资需求与信贷供给不平衡 D ...

Market Overview - The overall trading activity in the market has significantly increased, with the average daily trading volume rising from 1.2 trillion to 1.5 trillion CNY[1] - The Shanghai Composite Index turnover rate has increased to the 85th percentile, while the STAR Market turnover rate has reached the 40th percentile[1] - The proportion of stocks rising has increased to 88.6%, with a median weekly return of 4.4%[3] Capital Flow Insights - Net inflow of southbound funds has risen to 28.4 billion CNY, marking a 96th percentile since 2022[3] - Foreign capital has seen a net outflow of 3.74 million USD from the A-share market[39] - Financing funds have net bought 25.6 billion CNY, with the total margin balance increasing to over 1.8 trillion CNY[3] Fund Issuance and Performance - The issuance scale of new equity funds has decreased to 15.9 billion CNY, down from 25.7 billion CNY[31] - The private equity confidence index has slightly declined, while the positions have marginally increased[37] - The average return of funds has shown a significant improvement, with most funds reporting positive returns year-to-date[33] Sector Performance - The trading concentration in certain sectors has increased, with seven industries having turnover rates above 90%, including comprehensive finance and defense[2] - The electronic and computer sectors have the highest average daily trading volumes, at 1829.61 billion CNY and 1684.80 billion CNY respectively[20] - Notable inflows in financing funds were observed in the computer sector (+4.94 billion CNY) and non-bank financials (+3.93 billion CNY), while real estate saw outflows (-0.24 billion CNY)[3] Risk Considerations - There are potential risks related to data collection methods and measurement errors, as well as biases from third-party data sources[3]

Investment Rating - The report does not explicitly provide an investment rating for the new materials industry Core Insights - The new materials industry is experiencing significant developments, including the expansion of production capacities by companies like Kolon Industries, which plans to increase its optical PVA film production line in Japan to meet the growing demand for larger screen sizes. The new production line is expected to have an annual capacity of 38 million square meters, raising Kolon’s total capacity from 296 million square meters to 334 million square meters by December 2027 [1] - The successful completion of the 100,000 tons/year BDO and 120,000 tons PBAT project by Xinjiang Shuguang Greenhua marks a significant milestone, contributing to the development of an integrated industrial chain in the region [1] - Recent financing activities in the industry include a nearly 500 million yuan B+ round for Porcine Crystal, aimed at enhancing production capabilities for ultra-pure polymer materials, and a million yuan angel round for Shenzhen Sufang New Energy Technology, focusing on the development of lithium-rich manganese-based cathode materials [2] Summary by Sections Industry Development Dynamics - Kolon Industries announced an expansion of its optical PVA film production line in Japan, with a new line set to be operational by December 2027, increasing annual capacity to 38 million square meters [1] - Xinjiang Shuguang Greenhua's BDO and PBAT project has passed construction acceptance, enhancing the local chemical new materials industry [1] Investment and Financing Dynamics - Porcine Crystal completed a nearly 500 million yuan B+ round financing to support the construction and market expansion of its ultra-pure polymer materials production line [2] - Shenzhen Sufang New Energy Technology secured a million yuan angel round financing for the development of lithium-rich manganese-based cathode materials [2] Secondary Market Dynamics - The Wande New Materials Index rose by 5.12% during the week of June 23-27, 2025, while the CSI 300 Index increased by 1.95% [2]

Group 1 - The report maintains a tactical benchmark view on A-shares, citing the elimination of policy uncertainty and a decline in risk-free interest rates as factors that enhance market performance [4][11][13] - The tactical benchmark view on government bonds is upheld, with the report noting an imbalance between financing demand and credit supply, which limits the downward movement of interest rates [4][11][13] - The tactical allocation view on gold is downgraded to benchmark, as geopolitical tensions have eased and market risk appetite has rebounded, reducing gold's appeal as a safe-haven asset [4][11][13] - A tactical underweight view on the US dollar is maintained, with concerns over fluctuating policies and persistent fiscal deficit issues impacting the dollar's credibility [4][14] Group 2 - The report highlights that the recent market sentiment is stable, with expectations for economic recovery and a favorable environment for equity assets due to declining risk-free rates and high trading volumes [11][12] - The report indicates that the geopolitical situation in the Middle East and improved China-US relations have boosted global risk appetite, suggesting structural opportunities within equity markets [11][12] - The report emphasizes that the current macroeconomic environment limits the potential for significant downward adjustments in bond yields, as the market has already priced in the prevailing interest rate levels [11][12]

Quantitative Models and Construction Methods 1. Model Name: GRU(50,2)+NN(10) Factor - **Model Construction Idea**: This factor leverages a deep learning architecture combining Gated Recurrent Units (GRU) and Neural Networks (NN) to capture high-frequency trading patterns and predict stock returns[4][55] - **Model Construction Process**: - The GRU(50,2) component processes sequential high-frequency data with 50 units and 2 layers - The NN(10) component is a fully connected neural network with 10 neurons in the output layer - The model is trained on historical high-frequency data to predict stock returns, optimizing for multi-class classification or regression tasks[4][55] - **Model Evaluation**: Demonstrates robust performance in capturing high-frequency trading signals and generating stable returns[4][55] 2. Model Name: Multi-Granularity Model (5-Day Label) - **Model Construction Idea**: This model uses multi-granularity data to predict stock returns over a 5-day horizon, leveraging bidirectional AGRU (Attention-based GRU) for feature extraction[57][60] - **Model Construction Process**: - Input data is segmented into multiple granularities (e.g., daily, intraday) - Bidirectional AGRU is applied to extract temporal features from the data - A 5-day label is used as the prediction target, and the model is trained to optimize for this horizon[57][60] - **Model Evaluation**: Effective in capturing medium-term trading patterns and generating consistent returns[57][60] 3. Model Name: Multi-Granularity Model (10-Day Label) - **Model Construction Idea**: Similar to the 5-day label model, this version extends the prediction horizon to 10 days, using bidirectional AGRU for feature extraction[60][65] - **Model Construction Process**: - Multi-granularity data is processed with bidirectional AGRU - A 10-day label is used as the prediction target, and the model is trained to optimize for this extended horizon[60][65] - **Model Evaluation**: Provides a longer-term perspective on trading patterns, with slightly lower returns compared to the 5-day model but still effective[60][65] --- Model Backtesting Results GRU(50,2)+NN(10) Factor - **IC**: Historical: 0.066, 2025: 0.039[4][55] - **e^(-RankMAE)**: Historical: 0.336, 2025: 0.334[4][55] - **Long-Short Return**: Weekly: 0.70%, June: 3.58%, 2025 YTD: 19.78%[4][55] - **Long-Only Excess Return**: Weekly: -0.30%, June: 0.92%, 2025 YTD: -1.06%[4][55] Multi-Granularity Model (5-Day Label) - **IC**: Historical: 0.081, 2025: 0.070[57][60] - **e^(-RankMAE)**: Historical: 0.344, 2025: 0.343[57][60] - **Long-Short Return**: Weekly: 1.56%, June: 5.97%, 2025 YTD: 35.45%[57][60] - **Long-Only Excess Return**: Weekly: 0.40%, June: 2.16%, 2025 YTD: 11.87%[57][60] Multi-Granularity Model (10-Day Label) - **IC**: Historical: 0.074, 2025: 0.065[60][65] - **e^(-RankMAE)**: Historical: 0.342, 2025: 0.343[60][65] - **Long-Short Return**: Weekly: 1.66%, June: 5.76%, 2025 YTD: 33.44%[60][65] - **Long-Only Excess Return**: Weekly: 0.71%, June: 2.06%, 2025 YTD: 11.11%[60][65] --- Quantitative Factors and Construction Methods 1. Factor Name: Intraday Skewness Factor - **Factor Construction Idea**: Measures the skewness of intraday returns to capture asymmetry in price movements[4][10] - **Factor Construction Process**: - Calculate intraday returns for each stock - Compute the skewness of these returns using the formula: $ Skewness = \frac{E[(X - \mu)^3]}{\sigma^3} $ where $X$ is the return, $\mu$ is the mean, and $\sigma$ is the standard deviation[4][10] - **Factor Evaluation**: Effective in identifying stocks with asymmetric return distributions, though performance varies across periods[4][10] 2. Factor Name: Downside Volatility Ratio - **Factor Construction Idea**: Focuses on the proportion of downside volatility relative to total volatility to capture risk-averse behavior[4][14] - **Factor Construction Process**: - Calculate downside volatility as the standard deviation of negative returns - Compute the ratio of downside volatility to total volatility[4][14] - **Factor Evaluation**: Useful for identifying stocks with higher downside risk, though returns are sensitive to market conditions[4][14] 3. Factor Name: Opening Buy Intensity - **Factor Construction Idea**: Measures the intensity of buy orders during the opening period to capture early trading sentiment[4][17] - **Factor Construction Process**: - Aggregate buy orders in the first 30 minutes of trading - Normalize by total trading volume during the same period[4][17] - **Factor Evaluation**: Captures short-term sentiment effectively, though performance is volatile[4][17] --- Factor Backtesting Results Intraday Skewness Factor - **IC**: Historical: 0.027, 2025: 0.047[4][10] - **e^(-RankMAE)**: Historical: 0.324, 2025: 0.330[4][10] - **Long-Short Return**: Weekly: -0.51%, June: 1.48%, 2025 YTD: 14.73%[4][10] - **Long-Only Excess Return**: Weekly: -0.03%, June: 0.18%, 2025 YTD: 2.59%[4][10] Downside Volatility Ratio - **IC**: Historical: 0.025, 2025: 0.046[4][14] - **e^(-RankMAE)**: Historical: 0.324, 2025: 0.328[4][14] - **Long-Short Return**: Weekly: -0.04%, June: 1.86%, 2025 YTD: 12.84%[4][14] - **Long-Only Excess Return**: Weekly: 0.09%, June: 0.50%, 2025 YTD: 1.07%[4][14] Opening Buy Intensity - **IC**: Historical: 0.031, 2025: 0.028[4][17] - **e^(-RankMAE)**: Historical: 0.322, 2025: 0.322[4][17] - **Long-Short Return**: Weekly: 0.77%, June: 1.85%, 2025 YTD: 11.44%[4][17] - **Long-Only Excess Return**: Weekly: 0.04%, June: 0.61%, 2025 YTD: 5.91%[4][17]

Investment Rating - The report maintains an "Accumulate" rating for the company with a target price of 14.00 [6][12]. Core Views - The company demonstrates operational resilience in its board segment, while the non-board segment is shifting towards higher value products. The trend of cost reduction remains positive, and there is a concentrated risk of impairment at year-end. The value of high shareholder returns continues to be highlighted [2][12]. Financial Summary - The company is projected to achieve revenues of 9,063 million in 2023, with a slight increase to 9,189 million in 2024, and further growth to 11,555 million by 2027, reflecting a compound annual growth rate (CAGR) of approximately 8.2% from 2024 to 2027 [4][13]. - Net profit attributable to the parent company is expected to decrease from 689 million in 2023 to 585 million in 2024, before recovering to 1,003 million by 2027, indicating a significant growth of 54.7% in 2025 [4][13]. - Earnings per share (EPS) is forecasted to decline from 0.83 in 2023 to 0.70 in 2024, then rise to 1.21 by 2027 [4][13]. - The return on equity (ROE) is projected to decrease from 21.5% in 2023 to 19.2% in 2024, before increasing to 24.8% by 2027 [4][13]. Revenue Breakdown - The board segment is expected to maintain strong double-digit growth in 2024, while other decorative materials are projected to generate approximately 21.4 billion in revenue, reflecting a year-on-year increase of about 7.6% [12]. - The customized home segment is anticipated to decline by 18.73%, primarily due to the contraction of the Yufeng Hantang scale [12]. Cost Management - The company is expected to reduce management expenses by approximately 0.54 billion in 2024, with financial expenses also decreasing by about 0.21 billion [12]. - The trend of decreasing absolute costs is expected to continue into 2025, showcasing effective internal cost control [12]. Shareholder Returns - The company announced a profit distribution plan for the end of 2024, proposing a cash dividend of 3.2 yuan per 10 shares, amounting to a total cash dividend of 4.93 billion, which corresponds to a dividend yield of approximately 6% [12].