LSEG交易后解决方案的量化服务团队宣布与风险管理公司 Rhisco Group 开展合作，旨在提升其量 化能力并扩展其在墨西哥及更广泛的拉丁美洲（LATAM）市场的服务覆盖水平。 两者结合了LSEG交易后解决方案的全球经验以及Rhisco在区域市场的深厚专业知识，此次合作的 目标是为拉美地区的客户量身打造创新解决方案，并开发有助于金融行业整体发展的新战略与技 术。此外，这次合作将提升 LSEG 交易后解决方案为区域与全球客户提供服务的效率。 LSEG交易后服务定量服务合伙人Xabier Anduaga表示："Rhisco与我们一样追求卓越，致力于创 新。我们携手准备迎接未来的挑战，并提供顶级的解决方案。" Rhisco 联合创始人兼首席增长官 Elizabeth Marvan 也说："我们非常高兴能与 LSEG 交易后解决方 案携手合作。该联合使我们能够为客户提供更多附加价值，并进一步巩固我们在该地区的市场地 位。" 为 Banc a Mif e l 实施 XVA 平台 此次合作的一个重要成果，是成功为 Banca Mifel 推出了一套用于计算信用估值调节（XVA）的估 值与监管报告平台。该平台结合了 L ...

Core Insights - Open-source technology is widely applied across various industries, enabling companies to access professional functionalities at minimal or no cost, particularly in the post-trade sector [1] - The latest version of the Open-source Risk Engine (ORE) has been released, featuring significant updates aimed at enhancing user experience and optimizing outcomes [1][2] User-Centric Development - Since its launch, ORE has provided a diverse range of examples that simplify project development and showcase its powerful capabilities, now categorized by themes such as market risk and product analysis for easier navigation [2] - The new ORE wrapper prototype supports Excel, Python, and Restful API, allowing users to operate in familiar environments and integrate ORE functionalities seamlessly into existing workflows [2] Functionality Enhancements and Extensions - The 13th version of ORE introduces support for mid-term coupon exercises, enhancing the accuracy of valuation and risk metrics for financial instruments [3] - The American Monte Carlo simulation framework has been expanded to include stock trading, and the stress testing module has been optimized to output cash flow data under stress scenarios, providing more detailed analysis [3] Commitment to Accessibility and Innovation - The continuous development of ORE since its inception in 2016 is driven by ongoing dialogue with users, ensuring that feedback is incorporated into software updates [4] - The goal is to make powerful, transparent pricing and risk analysis capabilities accessible to all companies, not just those with the resources to develop or purchase expensive solutions [4] Integration with QuantLib - ORE is built on the open-source quantitative finance library QuantLib, facilitating integration with applications written in Python or Java through its SWIG language binding feature [5]