Prof. Luke Stein
This course schedule will change during the semester. Ad hoc topic changes (unannounced) may be based on current events or class pace and interest. Announcement of any meeting changes will be distributed via Discord; please ensure that you are monitoring the #announcements
channel there.
We will also have several combined meetings where multiple sections will meet simultaneously (typically to accommodate a guest). These will of course be announced in advance, but please aim to be available during all course section times (8:15am–2:30pm). Currently announced combined meetings are:
Meeting | Date | Topics/Modules | Deliverable |
---|---|---|---|
9/5 | No class (Labor Day) | ||
1 | 9/7 | Course introduction | |
2 | 9/12 | S1 | HW1 |
3 | 9/14 | P1 | Peer review |
4 | 9/19 | cont. | HW2 |
5 | 9/21 | cont. | Peer review |
6 | 9/26 | A1 | HW3 |
7 | 9/28 | P2 | Peer review |
8 | 10/3 | A2 | HW4 |
9 | 10/5 | P3, D1 | Peer review |
10/6 | Excel CC 0 | ||
10/10 | No class (Indigenous Peoples’ Day) | Excel CC 1 | |
10 | 10/11 | Tuesday class S2, P4 |
|
11 | 10/12 | A3, D2, S3 | |
10/15 | Excel CC 2 (opt.) | ||
12 | 10/17 | P5 | HW5 |
13 | 10/19 | S4, D3 | Peer review |
14 | 10/24 | Meeting 8:15–10:00am or 12:45–2:30pm A4 |
Midterm project |
15 | 10/26 | S5 | |
16 | 10/31 | S6, A5 | HW6 |
17 | 11/2 | A6 | Peer review |
18 | 11/7 | Meeting 8:15–10:00am or 12:45–2:30pm A4 |
Ethics report |
19 | 11/9 | P6 | |
20 | 11/14 | A7 | HW7 |
21 | 11/16 | cont. | Peer review |
22 | 11/21 | D4 | |
11/23 | No class (Thanksgiving break) | ||
23 | 11/28 | A8 | HW8 |
24 | 11/30 | A9 | |
25 | 12/5 | Group presentations | Final project |
26 | 12/7 | Group presentations (Final exam distributed) |
Market report |
12/12 | No class (Final exam due) | Final exam |
Module | Topic | Resources |
---|---|---|
P1 | Introduction to Python | TP 1–3, 8, 10–12 WTP 1–7 CfE Getting Started 1, Coding 3, Getting Started 2.1–2.8 PESDA 2, 4, 10 PDA 2.3, 3.1 |
P2 | Control flow and data structures | TP 5–7 WTP 8–14 CfE Getting Started 2.9–2.16 PESDA 12 PDA 3.2 |
P3 | Data manipulation | PDSH 3 PESDA 8–9, 16 CfE Data 1, Data 2 PDA 5, 7–8, 10-12 |
P4 | Visualization | PDSH 4.14 Seaborn Tutorial API overview and Plotting functions |
P5 | Regression and statistics | PESDA 21 |
P6 | Numerical Python | PDSH 2 PDA 4 PESDA 3, 11, 19 |
Module | Topic | Resources |
---|---|---|
S1 | Introduction to data | IMS 1–3 |
S2 | Exploratory data analysis (EDA) | IMS 4–6 |
S3 | Regression modeling | IMS 7–10 |
S4 | Foundations of inference | IMS 11–15 |
S5 | Statistical inference | IMS 16–23 |
S6 | Inferential modeling | IMS 24–27 |
Module | Topic | Resources |
---|---|---|
D1 | pandas-datareader | datareader documentation |
D2 | Bloomberg | TBA |
D3 | WRDS | WRDS Data documentation, Classroom, Research WRDS Python Data Access Library |
D4 | Alternative data | TBA |
Excel will be used throughout the course, with coverage not divided into explicit modules.
Module | Topic | Resources |
---|---|---|
A1 | Monte Carlo simulation | TBA |
A2 | Fixed income | TBA |
A3 | Equity returns | TBA |
A4 | Professional ethics | TBA |
A5 | Foreign exchange | TBA |
A6 | Factor models | TBA |
A7 | Capital budgeting | TBA |
A8 | Derivatives | TBA |
A9 | Equity portfolios | TBA |