AI赋能量化交易虚拟仿真实验教学的实践探索

Teaching Practice and Exploration of AI-Driven Virtual Simulation Experiments in Quantitative Trading

摘要: 在人工智能深度融入金融行业与高等教育的背景下，量化交易人才培养对知识整合、实训组织与评价反馈提出了更高要求，而传统课程教学仍面临知识体系碎片化、理论实践脱节与反馈机制滞后等问题。本文以期货、期权交易虚拟仿真实验教学为研究对象，在梳理人工智能赋能教学、虚拟仿真实验教学与量化交易人才培养相关研究的基础上，提出“AI赋能、虚实结合、动态迭代”的课程改革思路。课程以知识图谱重组教学内容，以虚拟仿真平台构建高仿真交易情境，并结合大语言模型与检索增强生成技术完善智能问答和实验评价机制，进而形成“智能导学–仿真实操–智能评价–迭代提升”的全流程育人闭环。实践表明，该模式有助于提升实验教学的系统性、交互性与反馈及时性，增强学生对交易规则、策略设计和风险控制的综合理解，并为金融类实验课程的智能化改革提供可复制的实践路径。

Abstract: Against the backdrop of artificial intelligence deeply integrating into both the financial industry and higher education, the cultivation of quantitative trading talents increasingly requires the integration of technology, practical training, and risk control. Traditional teaching models therefore face several challenges, including fragmented knowledge structures, a disconnect between theory and practice, and delayed instructional feedback. Focusing on futures and options virtual simulation experiment teaching, this paper reviews related studies on AI-empowered education, virtual simulation experiment teaching, and quantitative trading talent cultivation, and then proposes a reform path characterized by AI empowerment, integration of virtual and real elements, and dynamic iteration. Specifically, the course organizes scattered knowledge points through a knowledge graph, reconstructs authentic trading scenarios via a virtual simulation platform, and combines large language models with Retrieval-Augmented Generation to build intelligent question answering and experiment evaluation mechanisms. In this way, a full-process educational closed loop of intelligent guidance, simulation practice, intelligent evaluation, and iterative improvement is formed. Practice demonstrates that this model helps enhance the systematicness, interactivity, and timeliness of feedback in experimental teaching. It also strengthens students’ comprehensive understanding of trading rules, strategy design, and risk control, thereby providing a replicable practical pathway for the intelligent reform of finance-related experimental courses.