Introduction to Financial Analytics.

Catalog description

Semester course; 3 lecture hours (delivered face-to-face or hybrid). 3 credits. Prerequisite: FIRE 311 with a minimum grade of C. The course will provide an overview of probability and statistical concepts, hypothesis testing, covariance and correlation analysis, and simple and multiple regression methods. Students will also learn Python, the most popular data science programing language, and use it for data analysis. The skills acquired in this course will help students build basic financial models for investment decision-making. As the structure of the course generally follows the quantitative methods portion of the CFA curriculum, students will be prepared for the quantitative methods portions of the level I and II exams for the CFA charter.