Type of Credit: Elective
Credit(s)
Number of Students
This course provides graduate students opportunities to do research and write relevant papers. The topics include various financial economics and the recent developed techniques in artificial intelligence. Specifically, the aim of this course is to apply AI technique to quantify the model of portfolio management 、security trading and design、derivative products trading and risk management. At the end of the semester the students are required to complete a publishable paper.
能力項目說明
The goal of the course is to train the students to do research and write a completed paper.
| 教學週次Course Week | 彈性補充教學週次Flexible Supplemental Instruction Week | 彈性補充教學類別Flexible Supplemental Instruction Type |
|---|---|---|
No. Date Subjects
01 09/15 Introduction
02 09/22 Portfolio management I
03 09/29 Portfolio management II
04 10/06 Portfolio management III
05 10/13 Deep learning and active portfolio management I
06 10/20 Deep learning and active portfolio management II
07 10/27 Deep learning and active portfolio management III
08 11/03 Deep learning and active portfolio management IV
09 11/10 Midterm Presentation
10 11/17 Deep Learning and trading I
11 11/24 Deep Learning and trading II
12 12/01 Deep Learning and trading III
13 12/08 Deep Learning and risk management I
14 12/15 Deep Learning and risk management II
15 12/22 Blockchain and digital currency I
16 12/29 Final Presentation
17 01/05 General discussion
作業與出席 30%
報告 70%