Core Insights - Bloomberg has expanded its fund data solutions to include a comprehensive view of exchange-traded products (ETP) fund flows, providing nearly two decades of historical data to support backtesting and market cycle analysis [1][2] - The enhanced fund data will support portfolio management, product strategy, quantitative research, and risk and compliance monitoring, addressing the growing reliance on data-driven tools by investors [1][2] Group 1 - The global ETP fund flow data solution covers all ETP fund flows, including over 80,000 active trading codes from more than 90 exchanges, with total assets under management (AUM) exceeding $19.7 trillion by December 2025 [1][2] - Bloomberg's fund flow data tracks investor flows by monitoring changes in net asset value (NAV) and circulating shares, covering 95% of daily NAV and 90% of circulating shares [2] - Historical analysis is supported with comprehensive fund flow and revision history data available since 2007, aiding clients in adjusting analyses and optimizing investment strategies [2][3] Group 2 - The ETP fund flow data can be integrated with Bloomberg's dividend forecasting to estimate ETF dividends for income planning, risk assessment, and derivative pricing [3] - The data is accessible through Bloomberg terminals, static data set products, and enterprise-level products, with delivery options including SFTP, REST API, or designated cloud environments [3]

Core Insights - Bloomberg's Multi-Asset Class Factor Risk Model (MAC3) has been adopted by Marshall Wace, a leading global alternative asset management firm with over $70 billion in assets under management, to enhance its quantitative research and systematic investment strategies [1][3] - The MAC3 model provides advanced modeling techniques, precise risk forecasting, and robust portfolio analysis capabilities, enabling comprehensive measurement and monitoring of multi-asset portfolio risks [1] - The MAC3 model is recognized as a state-of-the-art risk factor model, utilizing over 3,000 factors for daily calculations, offering superior predictive accuracy for various investment portfolios, ranges, and styles [1][2] Group 1 - Marshall Wace's adoption of MAC3 reflects the growing demand among institutional investors for high-precision risk models that help in understanding the factors driving portfolio risks [1] - The modular design and strong factor structure of MAC3 support quantitative and systematic managers in enhancing portfolio construction and risk prediction capabilities [1] - Bloomberg's PORT Enterprise, powered by the MAC3 model, serves over 800 clients with advanced portfolio risk analysis and attribution, featuring enhanced customization and batch reporting capabilities [2] Group 2 - Established in 1997, Marshall Wace is a leading alternative investment management company specializing in long/short equity and systematic trading strategies [3] - The company operates globally with offices in major financial hubs including London, New York, Hong Kong, Singapore, Abu Dhabi, and Shanghai, employing over 750 staff [3] - Marshall Wace's commitment to innovation and technology upgrades is a key driver of its success, supported by a robust and scalable global infrastructure [3]

Core Insights - Bloomberg is the first global index provider to include Chinese bonds in mainstream global indices, offering a unique perspective on the Chinese bond market through its flagship Bloomberg China Fixed Income Index [3] - The Bloomberg China Aggregate Index experienced a slight decline of 0.02% in November, with a year-to-date return of 0.69% [5] - Shorter-term bonds outperformed longer-term bonds in November, with 10-year and above bonds returning -0.67% and 1-3 year bonds returning 0.12% respectively [5] Index Performance Summary - The China Aggregate Index (I08271CN) recorded a month-to-date return of -0.02% and a year-to-date return of 0.69%, with an index level of 244.63 [7] - The China Treasury and Policy Banks Index (I32561CN) had a return of -0.11% in November, with a year-to-date return of 0.49% [7] - The 1-3 Year maturity segment (I08279CN) achieved a month-to-date return of 0.12% and a year-to-date return of 1.13% [7] Economic Outlook - The 10-year government bond yield is expected to stabilize around 1.8% by year-end, potentially testing the 2% mark in 2026, supported by positive macroeconomic fundamentals and government policies [13] - U.S. liquidity pressures are identified as a primary cause for declines in dollar-denominated risk assets, with a widening of credit spreads in U.S. corporate bonds observed [13] - The Bloomberg Asia (ex-Japan) USD bond index is projected to experience a mild decline in 2026, as the benefits of U.S. Federal Reserve easing may be offset by widening credit spreads [13]

本文来自彭博终端，终端用户可运行NSN T6EOMEKIJH8G 阅读原文。非终端用户可点击文末 "阅读原文" 预约演示。 全球市场版图日新月异，彭博行业研究（Bloomberg Intelligence）为您的企业战略助力。在 制药与生物技术领域，无论是全球行业资讯与热点，还是制药管线里程碑及催化剂事件、财务 预测…… BI涵盖广泛且深度的关键信息，旨在为您的决策提供可靠且具有竞争力的洞见支撑。 扫描二维码 立即订阅 彭博生物制药双周报 本期主题： 诺和诺德、礼来因特朗普肥胖症协议面临20亿至30亿美元销售损失 （彭博行业研究）——根据我们的情景预测，由于与白宫达成协议，礼来、诺和诺德的GLP- 1类肥胖症药物2 0 2 6年在美国市场的合计销售额将减少2 0亿- 3 0亿美元，降至2 6 4亿美元，较 市场普遍预期低6%。该协议新增1 , 0 0 0万名符合资格的联邦医疗保险(Me d i c a r e )患者，并将 GLP- 1药物价格下调2 5%- 3 5%；若目标人群渗透率从此前的4 . 5%升至6%，销量增长将部分 抵消降价影响。 覆盖范围扩大将新增1,000万Medicare患者 美国国家健康 ...

战略部署需克服结构性挑战。 张益国 先生指出，当前新能源基地开发痛点主要集中于源 网荷储各环节在规划建设上不够匹配，以及大型基地叠加生态治理和长距离输电成本的经 济性问题。对此，他提出要推动新能源场站、调节电源和输电通道的同步规划建设，加强 新能源与有关产业集成融合发展，特别要重视提升省区间电力互济平衡能力，加强技术和 机制创新，多措并举推动新能源高质量消纳，提升发展的综合效益。 中国能源研究会常务理事李俊峰先生 指出，随着"136号文"将风光项目开发权由中央逐步 下放至地方，行业正从过去的"抢项目"转向更看重区位、消纳与经济性的"选项目"阶段。 当前装机节奏放缓属于机制切换下的正常磨合过程，短期调整趋势清晰。他判断，2025 年市场大概率呈现"前高后低、波动过渡"的波浪式走势，而随着新机制逐步消化、项目筛 选逻辑稳定，2026年有望实现较为明显的修复与反弹。 近期，彭博新能源财经BNEF上海峰会圆满闭幕。作为一年一度的能源盛会，本次BNEF上海 峰会汇聚了来自全球能源行业的顶尖嘉宾、创新先锋与行业领袖，围绕中国在"双碳"目标下 推动能源结构转型、深化电力市场改革，以及中国清洁技术企业在全球扩张中所面临的机遇 ...

Core Insights - The article emphasizes the importance of real-time data in enhancing front-office trading capabilities, highlighting how previously backend information is now crucial for driving stock market dynamics [1][4]. Group 1: Transformations in Front-Office Trading - There are three fundamental changes impacting trading desk decisions, liquidity acquisition, and risk management [4]. - Over 75% of U.S. stock trading volume is handled by "low-touch" trading engines, with over 60% of European stock orders originating from algorithms [5]. - A unified real-time data stream is essential for both algorithms and traders to maintain effective collaboration, especially during periods of market volatility [5]. Group 2: The Rise of Daily Options - Zero-day-to-expiration (0-DTE) options now account for 23% of the U.S. options market, contributing 56% of SPX options trading volume [6]. - Daily options have become the preferred tool for event-driven trading, with their associated hedging activities closely linked to rising volatility [7]. Group 3: Decentralization of Liquidity - By the end of 2024, major exchanges will handle less than half of U.S. stock trading, with trading report facilities (TRF) and regional platforms capturing 51% of the market share [8]. - The emergence of alternative trading systems (ATS) like Blue Ocean allows for trading during off-hours, increasing market fragmentation and necessitating a unified data stream to capture price movements and their driving events [8]. Group 4: Practical Implications of Real-Time Data - Bloomberg's recent launch of a "real-time event data" solution enhances its B-PIPE market data stream, allowing trading desks to respond promptly to market-moving information [10]. - Three case studies illustrate the impact of timely data on trading decisions, showing that delays in information can lead to significant financial consequences [22]. Group 5: Infrastructure for Continuous Trading - The market structure is evolving towards a 24/5 trading reality, requiring infrastructure that delivers both price and contextual information [24]. - B-PIPE provides a single API that pushes real-time quotes from all public markets and dark pools, along with machine-readable events that drive these quotes [24].

Core Viewpoint - The article emphasizes the critical role of natural gas in China's energy strategy, particularly in achieving carbon peak goals by 2030 and enhancing energy security. The expected annual growth rate of natural gas production in China from 2025 to 2035 is projected to be 5.3% [3]. Group 1: Energy Policy and Market Outlook - China's natural gas policy is set to boost industry development, with a focus on increasing domestic production and achieving a self-sufficiency rate of 71% by 2050, significantly higher than the 47% expected for the oil sector [3]. - Decision-makers are reducing pipeline transportation prices by at least 8% to stimulate natural gas usage, which could lead to a 10%-15% increase in gas transmission volumes [3]. - The demand for natural gas is expected to rise due to the shift in energy consumption structure, with natural gas's share in total energy consumption projected to increase from 8.9% in 2025 to 16% by 2035 [14]. Group 2: Performance and Valuation - As of September 30, Asian gas stocks have risen by an average of 3.6%, lagging behind the MSCI Energy Index's 7.6% increase, indicating a rebound from earlier lows [4]. - Despite the overall positive market sentiment, the price-to-book ratios of companies like Xinao Energy and China Gas remain near five-year lows, suggesting potential undervaluation [4]. - Xinao Energy's price-to-book ratio is 1.5 times, compared to a five-year average of 2.6 times, while China Gas's ratio is 0.8 times against a five-year average of 1.3 times [4]. Group 3: Supply and Demand Dynamics - The geopolitical landscape, particularly the Russia-Ukraine conflict, has heightened the focus on energy security, prompting China to prioritize domestic natural gas supply and production growth [10]. - By 2030, domestic natural gas production is expected to meet 59.8% of demand, increasing to 71.1% by 2050, as exploration and development activities ramp up [17]. - China's LNG import sources are diversifying, with Russia expected to become a major supplier, potentially surpassing Australia in the long term [19].

Core Viewpoint - Bloomberg has played a crucial role in connecting China's financial market with the global market over the past 30 years, particularly in the bond market, enhancing transparency and efficiency through data and technology [2][3]. Group 1: Milestones in Bloomberg's Development in China - The inclusion of Chinese bonds in the Bloomberg Global Aggregate Index in 2018 marked a significant milestone, increasing the weight of RMB bonds in the index from approximately 6% to about 10%, making it the third-largest after USD and EUR bonds [3]. - Bloomberg has supported various connectivity mechanisms, becoming the first overseas electronic trading platform to support both "Bond Connect" and direct investment models in 2019, facilitating investor participation in China's financial market [4]. - Continuous collaboration with Chinese financial institutions has been a focus, helping them enhance their global capabilities through data and technology, exemplified by a recent strategic partnership with Guotai Junan, China's largest securities firm [4]. Group 2: Changes and Impacts of China's Bond Market Opening - The current phase of China's bond market opening is characterized by a shift from "channel-based" to "institutional" opening, enhancing predictability, convenience, and professionalism for global investors [5]. - As of August 2025, 1,170 foreign institutions from 80 countries have entered the Chinese bond market, holding approximately 4 trillion RMB, indicating a growing interest in RMB assets despite fluctuations due to global interest rates [5][6]. - Institutional improvements are enhancing market transparency, liquidity, and predictability, making the experience for foreign investors more aligned with international practices [6]. Group 3: International Investors' Perspectives - International investors are increasingly focused on market transparency, liquidity, and expectations regarding exchange rates and policies when considering investments in Chinese bonds [7]. - Bloomberg aids investors in understanding these factors through data and analytical tools, providing insights into the Chinese bond market and macro policies [7]. Group 4: Innovations by Bloomberg - Bloomberg has leveraged technology to enhance market transparency and efficiency, utilizing AI, machine learning, and natural language processing to help clients extract key information from vast data [9]. - The BQUANT quantitative solution integrates data, computational power, and analytical models, significantly reducing the time required for strategy development and backtesting [10]. - A recent innovation includes a RMB bond repurchase trading solution that allows global investors to use bonds held through "Bond Connect" as collateral for electronic trading, improving financing and liquidity management [10]. Group 5: Future Expectations - Looking ahead, Bloomberg anticipates a clear direction for the opening of China's financial market, with further improvements in market mechanisms and the continued internationalization of the RMB [11]. - The expectation is that more Chinese financial institutions will integrate into the global market, requiring high-quality data, timely information, and reliable trading solutions, which Bloomberg aims to provide [11].

中国务实的 '人工智能+'战略极有可能推动整个经济的生产力提升。与单纯追求人工智能发展不 同，中国更注重软件优化和低成本模型，这使其在人工智能的实际应用方面具备良好优势。" 然而，彭博行业研究的自研市场预测模型显示，中国民营科技企业由于优先服务国家战略目标，而 非单纯追求利润最大化，因此在实现投资回报方面将面临挑战。 报告指出，中美在人工智能战略上的分化日益明显，全球人工智能产业正呈现 "双雄竞赛" 格局。 美国预计将继续在基础技术和先进硬件领域保持领先，而中国则优先发展软件和提升模型效率，推 动小型、高效模型的大规模部署，以实现整体经济的效率提升。 彭博行业研究高级中国科技分析师、《中国人工智能2026展望》报告主要作者Robert Lea 表示： " 彭博行业研究（BI）近日发布 《中国人工智能2026展望》报告 ，预测中国自上而下的人工智能 （AI）战略将推动其庞大经济体系的生产力提升。报告指出，在全球人工智能竞争日益激烈的背 景下，中国正专注于全国范围内快速部署AI，利用低成本、开源模型实现生产力增长。 根据彭博经济研究，中国包括人工智能在内的技术实力不断增强，预计高科技产业在GDP中的占 比将从20 ...

Core Insights - The article provides a schedule of upcoming Bloomberg seminars and workshops, focusing on various financial tools and market analysis techniques [3][4][5][6][7][12]. Group 1: Seminar and Workshop Offerings - Bloomberg offers a series of introductory courses for terminal users, including sessions on customizing personal workspaces and utilizing Bloomberg news and media tools for market insights [4][5]. - Specialized sessions are available for fixed income analysis, foreign exchange, and derivatives, aimed at enhancing users' understanding of market dynamics and product analysis [5][6][7]. - The schedule includes advanced training on Bloomberg Query Language (BQL) for equity and fixed income data retrieval, catering to users interested in quantitative analysis [12]. Group 2: Specific Dates and Topics - Key sessions include: - December 2: Fixed Income Expert Series on monitoring interest rate changes and product analysis [6]. - December 4: Terminal Introduction Series on customizing personal workspaces [4]. - December 9: Derivatives Series on stock option pricing and volatility tools [7]. - December 11: Foreign Exchange Series on analysis tools for foreign exchange and derivatives [5]. - December 16: BQL Series on equity data retrieval [12]. - December 23: BQL Series on bond rating data and fixed income [12].