The course is divided into three parts:
- Classical time series modeling (50% of the course)
- Deep Learning applied to time series data (25% of the course)
- Methods based on decision trees applied to time series data (25% of the course).
- MORETTIN, P. A .; TOLOI, C.M.C. Time Series Analysis; São Paulo: Edgard Blücher, 2004.
- ENDERS, Walter. Applied Econometric Time Series, Wiley; 3rd edition, 2009.
- STOCK, James and WATSON, Mark. Introduction to Econometrics. Prentice Hall, 3rd edition, 2015
- DAVIDSON, R. and MACKINNON, J. Econometric Theory and Methods. Oxford University Press, 2004.
- GREENE, W. Econometric Analysis. Prentice Hall, 2003
- KMENTA, J. Elements of Econometrics. Atlas, 1980. DAVIDSON, R., and MACKINNON, J. Econometric Theory and Methods. Oxford University Press, 2004.
- GRANGER, C.W.J. and NEWBOLD, P., 1986, “Forecasting Economic Time Series," Academic Press 2a. Ed.
- WOOLDRIDGE, J. Introductory Econometrics: A Moderm Approach. Cengage, 6th edition, 2016