— Economic & Financial Forecasting
This version has ended; see updated course, below. Course Description: Introduction to economics and financial forecasting tools. Econometrics modeling methods and real-world data applications using the computing language R. Time-series techniques including auto-regression, random walk, and volatility forecasting. Financial econometrics topics including yield curve modeling and asset pricing.
Prerequisites & course information
This version has ended; see updated course, below. Course Description: Introduction to economics and financial forecasting tools. Econometrics modeling methods and real-world data applications using the computing language R. Time-series techniques including auto-regression, random walk, and volatility forecasting. Financial econometrics topics including yield curve modeling and asset pricing. Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Enrollment Restriction(s): Pass One open to Economics majors only. Grade Mode: Letter. ECN 141 — Economic & Financial Forecasting (4 units) Course Description: Introduction to economics and financial forecasting tools. Econometrics modeling methods and real-world data applications using the programming language Python. Time-series techniques including auto-regression, random walk, and volatility forecasting. Financial econometrics topics including yield curve modeling and asset pricing. Prerequisite(s): (ECN 100 or ECN 100A or ECN 100AV ); ECN 101 ; ( ECN 102 or STA 108 ); or consent of instructor. Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Enrollment Restriction(s): Pass One open to Economics majors only. Grade Mode: Letter. This course version is effective from, and including: Winter Quarter 2027. Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Enrollment Restriction(s): Pass One open to Economics majors only. Grade Mode: Letter. ECN 141 — Economic & Financial Forecasting (4 units) Course Description: Introduction to economics and financial forecasting tools. Econometrics modeling methods and real-world data applications using the programming language Python. Time-series techniques including auto-regression, random walk, and volatility forecasting. Financial econometrics topics including yield curve modeling and asset pricing. Prerequisite(s): (ECN 100 or ECN 100A or ECN 100AV ); ECN 101 ; ( ECN 102 or STA 108 ); or consent of instructor. Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Enrollment Restriction(s): Pass One open to Economics majors only. Grade Mode: Letter. This course version is effective from, and including: Winter Quarter 2027.
Sources
- Course catalogue ↗2026-2027