- Texts (optional):
- Logistics: Compass2g
- Safety information: http://police.illinois.edu/emergency-preparedness/run-hide-fight/resources-for-instructors/
Grading policy: Final grades will be determined on the basis
- Pairs Trading
- Gaussian random variables
- Central Limit Theorem
- Returns and Log Returns
- Brownian Motion
- Brownian Quadratic Variation
- Ito Calculus
- Binomial Models
- Martingale pricing
- Interest rate models
of the total numerical score (and will be curved).
Component Weight Hourly Exam (9/16) 15% of grade Hourly Exam (10/14) 15% of grade Hourly Exam (11/11) 15% of grade Final (12/16) 20% of grade Quizzes, Projects, Homework 35% of grade
- Asynchronous notes will be made available on a module-by-module basis
- There will be a number of assignments involving data (and coding). Python (and Jupyter notebooks) will be the preferred framework for this (Python is one of the top languages for data analysis, so this is designed to be to your benefit). NB: Anaconda is one of the common distributions of Python.
- We will have synchronous Zoom meetings once a week. Details will be at Compass2g
- I will also give 5% Incentive points. These extra credit points will be given out by randomly spot-checking that students are continually engaged.
- All date-times will be in Champaign-Urbana
- All students are expected to abide by the Honor Code; you are here to learn (and my interest is in helping you do that).
- The technology of the course may evolve as the semester progresses and as I learn new tools. The content and goals will stay the same.