Analytics for Finance and Economics. (3-0) 3 Credit Hours

Catalog description

This course examines the analysis of financial and economic data. Students will learn advanced techniques for modeling and predicting trends, cycles, and seasonal patterns in financial markets and economic indicators. Key topics include ARIMA models, GARCH models, cointegration, vector autoregression (VAR), and machine-learning approaches to time-series forecasting. The course emphasizes practical applications, allowing students to develop predictive models and perform scenario analysis on real-world financial and economic datasets. By the end of the course, students will be equipped to make informed predictions and strategic decisions based on time-series analysis. This course has Differential Tuition.