QF112: Statistics Quantitative Finance
Course Catalog Description
Introduction
This course provides QF students with an introduction to (1) statistical estimation and inference and (2) the R statistical programming system. Although QF112does not expect that students have completed any formal statistical coursework in high school, including AP Statistics, the course is pitched at a level that assumes a basic acquaintance with some of the elements of calculus and probability.
Campus | Fall | Spring | Summer |
---|---|---|---|
On Campus | X | ||
Web Campus |
Instructors
Professor | Office | |
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Thomas Lonon
|
Tlonon@stevens.edu | Altorfer 303 |
More Information
Course Outcomes
In general, upon completion of the course, students will be able to use statistical methods to describe and analyze marketplace phenomena and develop solutions to commonly encountered business problems. In particular, students will be able to
- Think logically and analytically about quantitatively-based problems in a variety of functional areas such as quantitative finance and economic forecasting.
- Appreciate both the strengths and limitations of many commonly-used statistical methodologies, parametric as well as nonparametric.
- Reason programmatically in the context of the R statistical programming language including simulation as well as computation.
- Employ with confidence and skill a number of powerful, widely-used, and generally-applicable statistical methodologies.
- Think critically and skeptically about statistical findings often encountered not only in the workplace but also in the media; that is, to understand how people lie with statistics.
Course Resources
Textbook
Textbook(s): Title: Statistics with R: A Beginner’s Guide, 2018 Author: Stinerock Publisher: Sage ISBN: 978-1473-924-901 Readings: Chapters 1-13
Grading
Grading Policies
- Attendance/Participation - 5%
- Homework - 30%
- Exams - 35%
- Final Exam- 30% TOTAL - 100%
Lecture Outline
Topic | Reading | |
---|---|---|
Week 1 | Syllabus and Overview | |
Week 2 | Data | |
Week 3 | Sample Statistics | |
Week 4 | Parameter Estimation | |
Week 5 | Confidence Intervals | |
Week 6 | Hypothesis Tests | |
Week 7 | Hypothesis Tests (cont.) | |
Week 8 | Linear Regression | |
Week 9 | Exam | |
Week 10 | ANOVA | |
Week 11 | Linear Regression (cont.) | |
Week 12 | Polynomial Regression and Multivariable | |
Week 13 | Bootstrapping and Monte Carlo | |
Week 14 | Review & Catch-up |