Set by the PHBS Sargent Institute of Quantitative Economics and Finance (SIQEF) and designed and given by SThomas J. Sargent (winner of the 2011 Nobel Economics Prize and director of PHBS SIQEF), Chase Coleman (PhD, New York University),and Spencer Lyon (PhD, New York University), the one-year " Computational Economics and Finance" program covers basic knowledge of Python, including fundamentallearning and algorithms, dynamic models, as well as an online “training camp”. The course was completed this July, so let’s see what students gained from their class!
Cutting-edge and practical
Students describe the course as cutting-edge and practical. Zhang Yue, a management major at PHBS, was impressed by the professor’s patience and the abundance of topics in the class. “The class taught me how Python could be applied in our major,” she reflected.
Professor Sargent hopes that this course could help students in tackling problems in the social sciences with classical and advanced machine learning technology. In the class, students tried to write abstract theories in the form of codes and embodied them into curves. “Such interactions enabled students to learn by doing，” says Dr. Lyon, one of the course professors. All codes involved in the course were recorded using Jupyter Notebook, and classes can be replayed at any time to ensure that students have mastered every point.
Demystifying and empowering
Empowering students with a series of advanced tools is Professor Sargent’s education philosophy. “Learning how to use tools could facilitate students in asking great questions, and basic training built on these tools will explicate the consistency behind diversity.” The course taught students a series of core mathematical tools through continuous application of those tools. Course professors adopted the “incentive method” to eliminate students’ apprehension towards the advanced tools. Li Lei recalled an episode in Professor Sargent’s class: “Although he has made great achievements in this field, Professor Sargent often told us that doing research is not that easy, even for scientists like him. That encouraged us a lot. From his words, I now know that progress is not only built on your talent, but more so on your hard work.”
For Professor Shi Jiao, vice director of PHBS SIQEF, the program helps to demystify concepts: “Professors tried to articulate complicated AI courses through simple ways. For example, to make economic forecast through using many methods of neural network and deep learning, or to abstract useful information from sentences, articles or figures.”
The PHBS program was based on Professor Sargent ’ s decades of experience teaching economics. “Professor Sargent knows very well the difficulties of economics, the development trend of this subject in the future, and how computer science could help this process,” Professor Shi explained.
Living up to great expectations
Living up to great expectations Dr. Lyon, who for years taught computational economics and finance in New York University ’s Data Bootcamp, thinks highly of the PHBS program because it ensures enough time to “cover more themes, offer more details, and explore more cases”. Moreover, PHBS students live up to professors’ expectations. As Dr. Lyon said, they are willing to take these advanced courses and master the knowledge and skills needed in this field. In fact, among over 40 students who took this class, some are preparing to continue their research, while others view this program as a way to increase their opportunitiesto get a better job.Dr. Lyon also expressed his hope for the future: “We expect alumni to be prepared to make immediate contributions in either research or applied teams at the world's top
academic and private sector institutions.”
Estella Zhang Qiming also contributed to the editing
