Extra credit opportunities: if you found an error or a typo in the lecture notes below, please email me the information. You will receive 1 point of extra credit for one error you found.

Lecture Notes:

• notes1: stationarity, ACF, PACF, white noise, operators
• notes2: Box-Jenkins methodology, AR, MA
• notes3: ARMA, ARIMA
• notes4: model identification, estimation, diagnostic
• notes5: nonstationary model identification, ADF test
• notes6: forecasting
• notes7: seasonal ARIMA
• notes8: time series regression, vector autoregression (VAR)
• notes9: cointegration, vector error correction (VEC), spurious regression
• notes10: GARCH, neural network, model averaging