基于MATLAB的量化高频交易算法设计与实践

Design and practice of quantitative high frequency trading algorithm based on MATLAB

随着人工智能和大数据时代的到来,越来越多的非理工科专业培养计划中引入了“MATLAB编程”课程,而以基础语法为主的传统授课内容已无法满足学生多样化的专业发展需求。在此背景下,上海交通大学学生创新中心自2021年起在原有的“MATLAB编程”课程基础上进行了改革,开设了“MATLAB基础与在科学计算中的实践”课程。该课程面向全校所有专业本科生,旨在帮助他们熟练掌握MATLAB基础语法,从而通过实践案例构建数学模型,进而解决各类专业问题。为了向金融和经管方向的学生提供贴近专业实际的教学案例,课程以2019年沪深300股指期货订单簿数据为研究对象,基于MATLAB编程使用多元线性回归方法设计了一套高频交易的预测和回测算法,以此为例,教师能够引导学生使用订单流数据对价格进行建模预测,从而培养他们分析和解决金融领域相关问题的思维方法与实践能力,使枯燥、抽象的理论教学更加贴近行业前沿。

With the advent of the era of artificial intelligence and big data,an increasing number of non science and engineering majors have introduced the“MATLAB programming”course in their training programs.However,traditional teaching content that focuses on basic grammar is no longer able to meet the diverse professional development needs of students.In this context,the Student Innovation Center of Shanghai Jiao Tong University has reformed its existing“MATLAB programming”course since 2021,offering a course on“MATLAB fundamentals and practice in scientific computing”.This course is aimed at undergraduate students from all majors in the school,aiming to help them proficiently master the basic syntax of MATLAB,and thus construct mathematical models through practical cases to solve various professional problems.In order to provide students in the fields of finance and management with teaching cases that are close to professional reality,the course takes the 2019 Shanghai and Shenzhen 300 stock index futures order book data as the research object,and designs a set of high frequency trading prediction and backtesting algorithms using multiple linear regression methods based on MATLAB programming.Taking this as an example,the teacher can guide students to use order flow data to model and predict prices,thereby cultivating their thinking methods and practical abilities to analyze and solve related problems in the financial field,making dry and abstract theoretical teaching closer to the forefront of the industry.