交易后解决方案推出开源风险引擎的第13个版本，确保开源技术保持领先地位

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]