As technology is shaping the business landscape, several top universities have pioneered training in computat ional economics and f inance at the graduate level that combines mathematical and computational rigor with deep understanding of economics and finance. The Sargent Institute of Quantitative Economics and Finance (SIQFE) has also launched the Computational Economics and Finance sequence. The sequence is open to those who hold undergraduate degrees or have mastery of undergraduate mathematics and statistics.
“A computational economist must understand a number of tools beyond those that a typical undergraduate program in economics has time to deliver,” Professor Thomas Sargent remarked, adding that understanding must include mastery of topics from many distinct disciplines including computer science, data science, mathematics, and statistics. Professor Sargent designed the sequence together with Chase Coleman and Spencer Lyon, and taught the classes starting from fall 2020. The sequence consists of four one-module long classes together with an online preparatory “bootcamp” class to be completed during the summer preceding the program sequence.
SIQFE launched the online summer preclass in July, taught by three eminent professors: Spencer Lyon, Chase Coleman and Thomas Sargent. They are all experienced python users who are patient and ebullient. For those who don’t have solid knowledge in computer science, the pre-class will prepare them to learn computer science at a level typically taught in a good undergraduate class.
“The curriculum is well-designed and interesting. It begins with definition of elements, then introduces different types of loops, ends with interaction with git,” said PHBS economics student Chen Yongqiao. Chen added, “It further deepened my understanding of Python's programming. After a detailed introduction of python basic functions, I knew some tricks on writing efficient code. More importantly, I gained a preliminary insight on how to use programming to calculate prices for financial products. These examples have broadened my horizon and enable me to study finance from a computational perspective.”
“The summer pre-class uses Python as the main programming language, which is in line with the current mainstream of macro-research in academia. Since the course is not mandatory, the biggest challenge for me was how to maintain curiosity and enthusiasm in the learning process, especially when I couldn’t communicate with the professor face to face. However, it was a good way to establish study groups and communicate with classmates,” said Zhang Xizi, a PHBS student of economics.
“ It’s a good chance for me to review and learn more about Python programming language and other tools. The courses are well designed and arranged by the teaching team. The topics are thorough and practicable, which gradually deepen from theory to practice, and Professor Sargent gave us some valuable advice,” commented SIQEF PhD student Liu Xing, who has already taken some training courses that combine economics and computer language.
Four core courses come in pairs, with two courses to be taken each semester, including “Mathematical Foundations for Computational Economics and Finance”, “Data Tools for Computational Economics and Finance”, “Dynamic Models for Computational Economics and Finance”, and “Machine Learning for Computational Economics and Finance.” With topics focusing on cutting-edge research, those courses are designed to teach students how to build state-of-the-art models, arm them with cutting-edge data manipulation and management tools, and empower them to apply a variety of classical and cutting-edge machine learning techniques to problems in the social sciences.
According to Professor Sargent, the sequence will prepare students for careers as technically knowledgeable data scientists and computational economists, as they can acquire special skills useful for universities, research institutions, business entities, and even tech companies like Alibaba and Tencent. He further pointed out, “It will a lso provide invaluable technical skills for graduates who might want to pursue a PhD program in economics, finance, or other social
sciences.”
By Annie Jin
