Core Insights - The article discusses the significant uncertainty and volatility in the commodity market for 2025, driven by global economic slowdown and geopolitical tensions, leading to a complex situation of "declining prices and increasing volatility" [2] - The market dynamics for energy, metals, and agricultural products are diverging, challenging traditional supply-demand logic and requiring companies to redefine resilience and competitiveness [2] - The upcoming launch of platinum and palladium futures is highlighted as a potential game-changer for the industry and global markets [2] Event Details - The London Stock Exchange Group (LSEG) is hosting a commodity seminar in Hangzhou, Zhejiang, on December 4, 2025, focusing on the impact of the "14th Five-Year Plan" on the copper market and exclusive data releases related to gold, silver, platinum, and palladium [3][4] - The agenda includes presentations from various experts, including Kian Pang Tan on palm oil market outlook and Fu Xiaoyan on opportunities in the copper market [3][4] Expert Profiles - Kian Pang Tan, with over ten years of experience in agricultural research, specializes in palm oil and sugar market analysis, utilizing weather and satellite data for yield predictions [6] - Fu Xiaoyan, a senior director at Nanhua Futures Research Institute, has extensive experience in the futures industry and focuses on copper market research [7][8] - Chen Xiaoyan, the agricultural research director at Dadi Futures, has a background in information consulting and commodity trading [9] LSEG's Commodity Trading Solutions - LSEG offers comprehensive data and analytical solutions for energy, metals, and agricultural trading, enhancing decision-making processes for clients [14][16][19] - The company emphasizes the importance of structured data utilization, combining fundamental, supply-demand, and alternative data sources to provide competitive advantages in trading [13][22] - LSEG's platforms, such as Eikon and RDMS, allow clients to access leading trading insights across various commodity markets [17][18]

Core Insights - The wealth management industry is undergoing unprecedented transformation due to the rapid development of artificial intelligence (AI) and digital technologies, reshaping the competitive landscape through smart advisory, big data analytics, customer service, and risk management [1] Event Details - The London Stock Exchange Group (LSEG) will host a closed-door exchange meeting titled "Reconstructing the Value Chain: The Future of AI, Data Tools, and Wealth Management" on December 5 in Beijing, aimed at industry elites to discuss trends and opportunities in wealth management [1] - The event will feature key speakers including Chen Fang, Managing Director of LSEG North Asia and President of LSEG China, and Bai Lu, Professor at Beijing Normal University, among others [3][4] Agenda Highlights - The agenda includes a welcome speech, keynote presentations on the role of AI in financial digital transformation, and discussions on LSEG's wealth data solutions [3][4] - A panel discussion will feature industry leaders such as Wang Xiaocen from Tiger Brokers and Li Zhuo from Shaanxi International Trust, focusing on insights and experiences in wealth management [3][4] Speaker Profiles - Chen Fang has nearly 20 years of experience in the data and analytics industry, focusing on capital markets, data analysis, and digital transformation [7][8] - Bai Lu is a recognized expert in AI and has contributed to significant advancements in the field, with applications in major Chinese enterprises [9] - Jack Wong serves as a senior financial digital solutions consultant at LSEG, bringing extensive experience in financial technology [10] Wealth Management Solutions - LSEG offers innovative wealth management solutions that provide data, digital tools, and actionable insights to empower wealth advisors and investors [13][20] - The solutions include wealth management workflow tools and flexible data solutions that enhance the client experience and operational efficiency [15][16]

Core Viewpoint - London Stock Exchange Group (LSEG) is a leading global financial market infrastructure and data provider, committed to driving financial stability and empowering economies for sustainable growth [2][11]. Group 1: Company Overview - LSEG operates in over 65 countries with more than 26,000 employees, emphasizing values of integrity, collaboration, excellence, and transformation [4][11]. - The company provides a wide range of services across the financial market value chain, including data, indices, analytics, capital formation, trading execution, clearing, and risk management [11][12]. Group 2: Business Segments - **Data and Analytics**: LSEG is one of the world's leading financial information providers, delivering over 200 billion data updates daily through various products and services, supporting clients in making informed decisions [13]. - **FTSE Russell**: A global leader in benchmark and index provision, offering solutions for measuring investment performance and aiding in asset allocation and risk management [14]. - **Risk Intelligence**: Provides comprehensive risk solutions to help organizations manage risks effectively, including due diligence and identity verification services [15]. - **Capital Markets**: Facilitates capital raising and transfer across multiple asset classes and regions, featuring electronic trading platforms for various financial products [16]. - **Post-Trade Services**: Offers services that exceed expectations, assisting clients in managing financial resources, reducing risks, and ensuring regulatory compliance throughout the trading lifecycle [17][18].

Core Insights - The true value of AI in the financial sector fundamentally depends on the data utilized [1] - The course aims to optimize various financial datasets for AI applications, including macroeconomic indicators, pricing and reference data, company data, risk intelligence, and unstructured text [1][2] Course Content - Participants will learn how to extract maximum value from financial data, empowering their AI strategies whether building predictive models, trading algorithms, or risk analysis applications [2] - The course will cover common data pitfalls, best practices in feature engineering, and the technical and data requirements necessary for scalable AI systems [4] Event Details - The event is scheduled for November 28, 2025, from 15:30 to 16:30 [3] Overview of Financial Data and AI Applications - The course will provide a comprehensive overview of financial AI, the realities behind the hype, practical optimization of financial data for AI, and detailed requirements for AI data and technology [5]

Core Insights - The article emphasizes the increasing importance of international trade compliance as a core capability for enterprises in response to evolving global trade dynamics and regulatory pressures [1][4]. Event Background - The event organized by LSEG and partners aims to address the challenges and opportunities in shipping trade and cross-border compliance, highlighting the need for transparency and compliance capabilities in the trade chain [1]. - The event invites professionals from various sectors, including maritime, shipping, trade, logistics, multinational corporations, and banking risk and compliance departments [1]. Event Agenda - The agenda includes a keynote speech on insights and best practices in shipping trade compliance, focusing on risk identification trends, the role of shipping and logistics data in financial compliance, and the latest developments in U.S. sanctions and export control systems [2][4]. - A roundtable discussion will cover the application of shipping logistics and sanctions compliance data in financial risk control, including the latest developments in U.S. sanctions and export control [5][8]. Key Topics - Best practices for verifying trade authenticity and enhancing supply chain transparency will be discussed [4]. - The use of shipping data in cross-border transaction compliance will be explored [4]. - Practical operations for identifying, avoiding, and monitoring sanction risks will be shared, along with collaborative mechanisms among banks, shipping companies, and technology providers [8]. Compliance Framework - The event will address the evolution of export control policies and their impact on enterprises, as well as strategies for navigating complex regulatory environments [8].

Core Insights - The wealth management industry is undergoing unprecedented transformation due to the rapid development of artificial intelligence (AI) and digital technologies, reshaping the competitive landscape through smart advisory, big data analytics, customer service, and risk management [1] Event Details - The London Stock Exchange Group (LSEG) will host a closed-door exchange meeting titled "Reconstructing the Value Chain: The Future of AI, Data Tools, and Wealth Management" on December 5 in Beijing, aimed at industry elites to discuss trends and opportunities in wealth management [1] - The event will feature key speakers including Chen Fang, Managing Director of LSEG North Asia and President of LSEG China, and Bai Lu, Professor at Beijing Normal University [3][4] Agenda Highlights - The agenda includes a welcome speech, keynote presentations on the role of AI in financial digital transformation, and discussions on LSEG's wealth data solutions [3][4] - A panel discussion will feature industry leaders such as Wang Xiaocen from Tiger Brokers and Li Zhuo from Shaanxi International Trust [3][4] Speaker Profiles - Chen Fang has nearly 20 years of experience in the data and analytics industry, focusing on capital markets, data analysis, and digital transformation [7][8] - Bai Lu is a professor with significant contributions to AI applications in education and has received multiple awards for her research [9] - Jack Wong is a senior financial digital solutions consultant at LSEG, with expertise in digital transformation [10] - Wang Xiaocen has over ten years of experience in fintech and focuses on AI-driven data product innovation [10] - Li Zhuo has a strong background in asset management and emphasizes technology empowerment in investment strategies [11] Wealth Management Solutions - LSEG offers innovative wealth management solutions that provide data, digital tools, and actionable insights to enhance decision-making for wealth advisors and investors [13][20] - The solutions include wealth management workflow tools and flexible data solutions that prioritize customer experience [15][16]

Core Insights - The true value of AI in the financial sector fundamentally depends on the data utilized [1] - The course aims to optimize various financial datasets for AI applications, including macroeconomic indicators, pricing and reference data, company data, risk intelligence, and unstructured text [1][2] Course Content - Participants will learn how to extract maximum value from financial data, empowering their AI strategies whether building predictive models, trading algorithms, or risk analysis applications [2] - The course will cover common data pitfalls, best practices in feature engineering, and the technical and data requirements necessary for scalable AI systems [4] Event Details - The event is scheduled for November 28, 2025, from 15:30 to 16:30 [3] Financial Data Overview - The course will provide a comprehensive overview of financial data and AI applications, addressing the realities behind the hype of financial AI, practical optimization of financial data for AI, and detailed requirements for AI data and technology [5]

Core Insights - The true value of AI in the financial sector fundamentally depends on the data utilized [1] - The course aims to optimize various financial datasets for AI applications, including macroeconomic indicators, pricing and reference data, company data, risk intelligence, and unstructured text [1][2] Course Content - Participants will learn how to extract maximum value from financial data, empowering their AI strategies whether building predictive models, trading algorithms, or risk analysis applications [2] - The course will cover common data pitfalls, best practices in feature engineering, and the technical and data requirements necessary for scalable AI systems [4] Event Details - The event is scheduled for November 28, 2025, from 15:30 to 16:30 [3] Financial Data Overview - The course will provide a comprehensive overview of financial data and AI applications, addressing the realities behind the hype of financial AI, practical optimization of financial data for AI, and detailed requirements for AI data and technology [5]

Core Insights - The article discusses the impact of the U.S. government shutdown on the CFTC's futures market data, particularly regarding gold and other precious metals, and the market's expectations for interest rate changes in December and January [2][26] - It highlights the significant price movements in gold, silver, and other assets, emphasizing the normalcy of price corrections after substantial gains [27][28] - The article also touches on the broader economic implications of potential interest rate cuts and their effects on asset valuations, particularly in the context of fund managers locking in profits [26][30] Group 1: Market Sentiment and Data Analysis - The CFTC data reflects a shift in market sentiment, with the probability of a rate cut in January rising from 17.4% to 25.2% over two weeks [2][26] - Managed positions in gold futures have seen a net long position decrease of 10.3% as of October 7, while silver and platinum also experienced declines in net long positions [4][8][9] - The article notes that gold prices have risen significantly from approximately $2,300 to around $4,000, indicating a potential for normal price corrections [27][28] Group 2: Investment Strategies and Asset Performance - The performance of gold compared to other assets shows that it has outperformed Nasdaq and Bitcoin year-to-date, despite recent declines [28] - The author references the investment strategies of notable figures, suggesting that holding physical gold and silver is a prudent approach amid market volatility [3][29] - The article warns against the mindset of expecting quick profits from high positions, likening it to gambling rather than investing [28] Group 3: Economic Outlook and Future Projections - The article posits that the U.S. is likely to continue lowering interest rates, which could support further increases in gold prices [30][29] - It discusses the potential for ongoing economic challenges, including stagflation, which may drive demand for physical assets like gold [32][33] - The future of gold prices is tied to the actions of the Federal Reserve and geopolitical dynamics, particularly U.S.-China relations [31][32]

Core Insights - Open-source technology is reshaping the financial landscape, providing companies with low-cost or free access to advanced analytical and simulation tools, particularly in the post-trade environment [1] - The release of version 14 of the Open Risk Engine (ORE) enhances analytical precision and expands tool coverage, addressing the growing demand for flexible, transparent, and high-performance risk tools [1][2] Group 1: Version Enhancements - The core of version 14 is an upgrade to QuantLib v1.40, which improves performance and consistency, ensuring ORE meets the evolving needs of global financial institutions [2] - Over 100 issues have been resolved since the last release, enhancing platform stability and accuracy across all use cases [2] Group 2: Expanded Modeling Capabilities - Version 14 extends ORE's analytical capabilities to new product classes and market areas, including support for American options on commodity futures and modeling for callable bonds and their derivatives [3] - Enhancements for bond futures include the introduction of the "Cheapest-to-Deliver" feature and total return swaps for bond futures, ensuring alignment with market practices [3] Group 3: Calibration and Analysis Improvements - New features in version 14 optimize calibration and enhance modeling consistency, including a global yield curve bootstrapping function that improves the accuracy of complex yield curve construction [4] - Additional enhancements include Delta-Gamma adjustment calibration for swaptions and improved regression techniques for modeling OIS AMC risk exposure [4] Group 4: Correlation Analysis Framework - The correlation analysis framework now allows users to generate correlations based on historical scenarios, which can be integrated into XVA analysis for a more dynamic and data-driven approach to risk exposure and valuation adjustments [5] - Improved error reporting features simplify debugging processes by automatically attributing missing fixing ID errors to transaction IDs, enhancing transparency [5] Group 5: Community-Driven Development - Since its inception in 2016, ORE has evolved through continuous feedback from a global user community, reflecting direct collaboration with practitioners, academia, and developers [6] - The updates in version 14 not only bring technical improvements but also enhance the usability of risk and pricing modeling, ensuring high-quality risk analysis is accessible to all institutions [6][7]