Report Information - Report Title: ETF Strategy Index Tracking Weekly Report, Public Fund Weekly Report [1] - Report Date: December 29, 2025 [1] Investment Ratings - Not provided in the report Core Views - The report presents several ETF strategy indices constructed by Huabao Securities, aiming to obtain excess returns relative to the market through different quantitative models and strategies. It also tracks the performance and positions of these indices on a weekly basis [4][5][12] Summary by Directory 1. ETF Strategy Index Tracking - **Overall Performance**: The table shows the performance of various ETF strategy indices last week, including the index name, last week's index return, comparison benchmark, last week's benchmark return, and excess return [13] | Index Name | Last Week's Index Return | Comparison Benchmark | Last Week's Benchmark Return | Excess Return | | --- | --- | --- | --- | --- | | Huabao Research Large - Small Cap Rotation ETF Strategy Index | 1.96% | CSI 800 | 2.50% | -0.54% | | Huabao Research Quantitative Fire - Wheel ETF Strategy Index | 4.18% | CSI 800 | 2.50% | 1.67% | | Huabao Research Quantitative Balance Technique ETF Strategy Index | 1.04% | SSE 300 | 1.95% | -0.91% | | Huabao Research SmartBeta Enhanced ETF Strategy Index | 3.94% | CSI 800 | 2.50% | 1.43% | | Huabao Research Hot - Spot Tracking ETF Strategy Index | 2.03% | CSI All - Share | 2.78% | -0.75% | | Huabao Research Bond ETF Duration Strategy Index | 0.03% | ChinaBond Aggregate Index | 0.04% | -0.01% | 1.1 Huabao Research Large - Small Cap Rotation ETF Strategy Index - **Strategy**: Uses multi - dimensional technical indicator factors and a machine - learning model to predict the return difference between the Shenwan Large - Cap Index and the Shenwan Small - Cap Index. The model outputs signals weekly to predict the strength of the indices in the next week and determines positions accordingly [4][14] - **Performance**: As of December 26, 2025, the excess return since 2024 is 19.71%, the excess return in the past month is - 0.63%, and the excess return in the past week is - 0.54% [4][14] - **Position**: Holds 100% of the SSE 300ETF (fund code: 510300.SH) [18] 1.2 Huabao Research SmartBeta Enhanced ETF Strategy Index - **Strategy**: Uses volume - price indicators to time self - built barra factors, and then maps the timing signals to ETFs based on the exposure of ETFs to 9 barra factors. The selected ETFs cover mainstream broad - based index ETFs and some style and strategy ETFs [4] - **Performance**: As of December 26, 2025, the excess return since 2024 is 22.50%, the excess return in the past month is - 1.98%, and the excess return in the past week is 1.43% [4] - **Position**: Holds 25.05% of the Huaxia Science and Technology Innovation Composite Index ETF (fund code: 589000.SH), 25.04% of the Fuguo Science and Technology Innovation Composite Index ETF (fund code: 589600.SH), 25.02% of the Southern GEM 200ETF (fund code: 159270.SZ), and 24.89% of the Wanjia GEM Composite ETF (fund code: 159541.SZ) [22] 1.3 Huabao Research Quantitative Fire - Wheel ETF Strategy Index - **Strategy**: Starts from a multi - factor perspective, including the grasp of medium - and long - term fundamental dimensions, the tracking of short - term market trends, and the analysis of the behavior of various market participants. It uses valuation and crowding signals to prompt industry risks and multi - dimensionally digs out potential sectors [22] - **Performance**: As of December 26, 2025, the excess return since 2024 is 38.65%, the excess return in the past month is 2.06%, and the excess return in the past week is 1.67% [22][25] - **Position**: Holds 20.97% of the Securities and Insurance ETF (fund code: 512070.SH), 20.60% of the Chemical ETF (fund code: 159870.SZ), 19.54% of the Steel ETF (fund code: 515210.SH), 19.49% of the Oil and Gas ETF (fund code: 159697.SZ), and 19.39% of the New Energy ETF (fund code: 516160.SH) [26] 1.4 Huabao Research Quantitative Balance Technique ETF Strategy Index - **Strategy**: Adopts a multi - factor system including economic fundamentals, liquidity, technical aspects, and investor behavior. It constructs a quantitative timing system to judge the trend of the equity market and establishes a prediction model for the market's large - and small - cap styles to adjust the equity market position distribution [26] - **Performance**: As of December 26, 2025, the excess return since 2024 is - 11.11%, the excess return in the past month is - 1.05%, and the excess return in the past week is - 0.91% [26][27] - **Position**: Holds 9.23% of the Ten - Year Treasury Bond ETF (fund code: 511260.SH), 6.11% of the 500ETF Enhanced (fund code: 159610.SZ), 5.98% of the CSI 1000ETF (fund code: 512100.SH), 32.84% of the 300 Enhanced ETF (fund code: 561300.SH), 22.94% of the Government Financial Bond ETF (fund code: 511520.SH), and 22.89% of the Short - Term Financing ETF (fund code: 511360.SH) [29] 1.5 Huabao Research Hot - Spot Tracking ETF Strategy Index - **Strategy**: Tracks and mines hot - spot index target products in a timely manner based on strategies such as market sentiment analysis, industry major event tracking, investor sentiment and professional views, policy and regulatory changes, and historical deduction. It constructs an ETF portfolio that can capture market hot spots in a timely manner [29] - **Performance**: As of December 26, 2025, the excess return in the past month is - 1.22%, and the excess return in the past week is - 0.75% [29][32] - **Position**: Holds 38.33% of the Non - Ferrous Metals 50ETF (fund code: 159652.SZ), 23.48% of the Boshi Hong Kong Stock Dividend ETF (fund code: 513690.SH), 19.50% of the Hong Kong Stock Connect Pharmaceutical ETF (fund code: 513200.SH), and 18.69% of the Short - Term Financing ETF (fund code: 511360.SH) [33] 1.6 Huabao Research Bond ETF Duration Strategy Index - **Strategy**: Uses bond market liquidity and volume - price indicators to screen effective timing factors and predicts bond yields through a machine - learning method. When the expected yield is lower than a certain threshold, it reduces the long - duration positions in the bond investment portfolio [6][33] - **Performance**: As of December 26, 2025, the excess return in the past month is 0.18%, and the excess return in the past week is - 0.01% [6][33] - **Position**: Holds 50.01% of the Ten - Year Treasury Bond ETF (fund code: 511260.SH), 25.00% of the Government Financial Bond ETF (fund code: 511520.SH), and 25.00% of the 5 - to 10 - Year Treasury Bond ETF (fund code: 511020.SH) [36]

ab 23 December 2025 Global Research Global Equity Strategy Quantitative Framework and Positioning Each month, we update the three key parts of our quantitative framework: Andrew Garthwaite Strategist Regions: This was covered in Part 1 of our outlook. The FTSE has moved to the top of our regional aggregate scorecard (up one place). Japan, where we remain underweight, is now second (down one place). It scores top on our MCI scorecard, but we see a sharp tightening of monetary conditions relative to other reg ...

夏瑜带领的康方生物，在生物药研发领域独树一帜。2025年，康方生物的双特异性抗体药物研发取得重 要突破。公司凭借其先进的抗体工程技术，开发出多个具有国际竞争力的双抗药物。在临床试验方面， 康方生物积极与国内外科研机构合作，加速药物的临床验证进程。 朱义领导的百利天恒药业，2025年在创新药研发上展现出强大的创新活力。公司聚焦于肿瘤治疗领域， 通过自主研发和合作创新相结合的方式，推进多个创新药项目的研发。百利天恒在药物递送技术方面取 得重要进展，开发出新型的药物递送系统，提高了药物的靶向性和生物利用度。 专题：为中国经济点赞——企业家之夜2025 "为中国经济点赞——企业家之夜"已于12月17日正式启动，目前点赞活动正在火热进行中。 在科技飞速发展的当下，创新药研发作为生命科学领域的关键战场，承载着人类对抗疾病、追求健康的 美好愿景。药明康德董事长李革、江苏恒瑞医药董事长孙飘扬、康方生物主席夏瑜、百利天恒药业董事 长朱义，谁将为人类赢得下一场生命之战？ 【点击链接为TA点赞】 李革领导的药明康德，一直是创新药研发服务领域的领军者。2025年，药明康德持续加大研发投入，进 一步完善其一体化、端到端的新药研发服务平 ...

Group 1 - In 2025, gold is projected to reach approximately $4,300 per ounce, while silver is expected to exceed $60, doubling its value. Platinum and palladium are also anticipated to see significant price increases [2] - The surge in precious metals is driven by central bank gold purchases, geopolitical risks, expectations of Federal Reserve interest rate cuts, and demand from the new energy sector [2] - The year 2026 is expected to continue the upward trend in precious metals, with the performance of the US dollar and the global economy being critical variables [2] Group 2 - The London Stock Exchange Group (LSEG) is collaborating with Tokyo Commodity Exchange to explore the precious metals market under macroeconomic conditions, providing exclusive data on gold, silver, platinum, and palladium [2] - LSEG offers comprehensive solutions for commodity trading, including insights, data management, and seamless execution capabilities to enhance competitive advantages in the market [20][23] - The company emphasizes the importance of timely and accurate data in commodity trading, utilizing structured approaches to leverage fundamental, supply-demand, and alternative data sources [22][31]

在这个星球上，没有任何生命形式在数量和多样性上能与病毒相提并论。据估算，地球上大约存在1031 个病毒 颗粒。这是一个什么概念？如果把它们排列起来，长度甚至超过了银河系的直径。然而，面对如此庞大的数 字，人类目前所掌握的知识却显得微不足道。 即使是在基因组测序技术突飞猛进的今天，像 IMG/VR (Integrated Microbial Genome/Virus Resource) 这样最庞大 的病毒基因组数据库，也仅仅收录了约 1530万 个病毒基因组片段。这与真实世界相比，连九牛一毛都算不 上。更令人焦虑的是，即便是这"九牛一毛"中，能够被国际病毒分类委员会 (ICTV) 正式分类和命名的，还不 到 0.01%。 这是一个巨大的不对称：我们的测序能力在指数级增长，每一滴海水、每一克土壤都在告诉我们要发现成千上 万的新病毒，但我们的分类体系却像是一台老旧的打字机，试图跟上超级计算机的输出速度。传统的分类方法 依赖于专家的手工 (Manual Curation)，这种方式虽然严谨，但在宏基因组学 (Metagenomics) 的海量数据面前显 得捉襟见肘。 12月19日，《Nature Biotechnol ...

编译丨王聪 编辑丨王多鱼 排版丨水成文 基于机器学习 （ Machine Learning ） 的人工智能 （AI） 工具，彻底改变了科学家研究蛋白质结构的方式。 近日，《 自然·化学生物学 》 （Nature Chemical Biology） 期刊采访了 Cecilia Clementi （柏林自由大学） 、 Bruno Correia （洛桑联邦理工学院） 和 卢培 龙 （西湖大学） ， 探讨了开发用于预测蛋白质结构和性质的计算工具方面的进展，这些工具如何用于蛋白质设计，以及他们希望在该领域看到的发展。 问 ：用于预测蛋白质结构和特性的新计算工具已经彻底改变了化学生物学的许多领域。最近蛋白质建模方面有哪些进展让您感到兴奋？您在自己的研究中是否已 经开始使用任何新工具？ Cecilia Clementi ：我们正生活在一个非常令人兴奋的时代，机器学习正在推动不同科学领域取得重大进展。我特别兴奋的是，机器学习工具现在开始着手应对理 解大分子动态和功能的挑战，超越了单一结构的局限。在我的研究小组中，我们正在朝着这个方向努力，并且正在基于诸如 AlphaFold 和 BioEmu 这样的工具开 展工作。 Bru ...

图源ZYTLYN Technologies 瑞士信息与通信科技公司ZYTLYN Technologies（以下简称ZYTLYN）成立于2021年，公司致力于研发旅游预 测分析智能体。该智能体能够全面分析旅游行业影响因素，通过机器学习预测需求趋势，为旅游业企业提供 定价、营销等决策建议。 ZYTLYN研发了旅游预测分析智能体，该智能体依托公司专有机器学习技术，可对旅游业相关各领域数据进 行综合分析，准确反映和预测旅客的出行目的地、时间及潜在支付意愿等，为旅游业企业提供精细化、可操 作的需求模式预测，可用于定价、营收管理和销售等诸多方面。 ZYTLYN的智能体会利用机器学习技术处理和转换各类行业相关数据，从中发现最新趋势影响关联性和行为 模式并生成预测结果，为用户提供基于情境的预测建议。ZYTLYN拥有自有的全球旅行数据源，以及涵盖风 险预警、突发事件、气象条件、宏观经济指标等诸多领域的外部数据源。其智能体会从以上各种数据流中提 取数据，对数据进行清洗、规范化与聚合，并对聚合数据集进行转换，生成训练数据集。随后，智能体将进 行机器学习模型的开发和优化，包含特征工程、超参数优化等内容，并将优化后的模型交付至应用情景 ...

转自：六安新闻网 （来源：六安新闻网） 活力——通过技术创新不断优化风控模型，提升金融机构的业务拓展能力。 韧性——强化风险识别与应对能力，增强金融体系的抗风险韧性。 拓新——探索AI、大数据等新技术在风控领域的深度应用，开辟金融科技新赛道。 2025年12月12日，由华夏机构投资者年会组委会主办的第十九届华夏机构投资者年会暨华夏金融（保 险）科技论坛在北京隆重举行。本次论坛以"活力与韧性拓新与赋能"为主题，汇聚了知名学者、金融机 构领导者及行业专家，共同探讨金融科技的未来发展方向。在本次盛会上，桔子数科凭借其自主研发的 智能风控系统"桔盾"，荣获"2025年度智能风控科技创新应用典型案例"奖项，彰显了公司在金融科技领 域的创新实力与行业影响力。 科技赋能，打造金融风控新标杆 当前，全球经济环境复杂多变，金融机构在数字化转型过程中，既需要保持发展活力，又需增强风险抵 御能力。桔子数科始终坚持以技术驱动风控革新，通过人工智能、大数据、机器学习等前沿技术，构建 了覆盖全业务场景的智能风控体系，助力金融机构提升风险管理效率，优化用户体验。 此次获奖的"桔盾"智能风控系统，是桔子数科在金融科技领域的核心成果之一。该系 ...

内容概要：通信平台即服务（CPaaS）是一个基于云计算的通信平台，提供集成开发环境和应用程序编 程接口(API)，简化了向应用程序中添加通信功能的过程。该平台允许开发人员将语音、视频会议和消 息传递功能整合到他们的应用程序中，而无需构建后端基础设施。CPaaS服务主要包括、消息服务、语 音服务、移动流量服务、物联网SIM卡及数据、虚拟商品充值、RCS信息服务等。CPaaS服务市场的产 业链主要包括上游的电信运营商及云基础设施供应商、中游的CPaaS服务提供商及下游客户（包括企业 软件开发商及SaaS供应商）以及企业及公共组织。上游电信网络运营商提供电信资源及渠道，如语音、 消息、移动流量等；云基础设施供应商提供云基础设施，用以计算、储存、操作和维护等。中游CPaaS 服务提供商数量较多，竞争激烈。下游一些开发能力较强的企业和公共组织可以直接利用CPaaS服务提 供商的通信功能，并将其嵌入到自己的业务系统和应用程序中。CPaaS服务提供商高度依赖电信运营商 聚合电信资源。从2024年CPaaS服务市场成本结构来看，电信资源为其最主要的成本支出，占到总成本 的94.5%，电信网络运营商议价权较高；其次为人工成本及 ...

撰文丨王聪 编辑丨王多鱼 排版丨水成文 微生物 的生物活性对于 发酵食品 的风味、外观、质量和安全性至关重要。然而，发酵过程中酶资源的多样性和分布情况仍知之甚少。 近日，山东大学微生物技术研究院 张正 教授、 李越中 教授等在 Cell 子刊 Cell Systems 上发表了 题为： Assessment of enzyme diversity in the fermented food microbiome 的研究论文，该研究还被选为当期 封面论文 。 该研究利用人工智能 （AI） 辅助的功能注释，揭示了发酵食品微生物组中隐藏的酶多样性及分布情况， 为未来食品研究中微生物功能的探索提供了宝贵见解。 总的来说，这些研究结果强调了发酵食品环境在酶资源开发方面尚未被充分挖掘的潜力，为未来食品研究中微生物功能的探索提供了宝贵见解。 值得一提的是， Cell Systems 期刊同期发表了来自海南大学 宋凤阁 副研究员、 万逸 研究员的题为 ： Lighting up hidden microbial enzyme diversity and functional opportunities from fermen ...