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This course provides an advanced treatment of econometric models used to forecast financial and economic data. This type of data often comes in the form of time series and thus much of the course uses methods for time series analysis. Autoregressive moving average, vector autoregression and generalized autoregressive conditional heteroscedastic models are some of the techniques that are used in the course to forecast economic growth rates, returns on financial securities and volatility of those returns.
Weekly Contact: Lecture: 3 hrs.
GPA Weight: 1.00
Course Count: 1.00
Billing Units: 1
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