Effectively uses in-depth knowledge of economic time series analysis methods, applying the results of analyzes to formulate forecasts.
Subject contents:
1. Classical time series analysis (trend, cyclical fluctuations)
2. Exponential smoothing models
3. Holt and Winters model
4. Stochastic processes and time series
5. Characteristics of stochastic processes
6. Process spectrum autocorrelation functions
7. Study of the stationarity of the time series
8. Autoregressive (AR) processes
9. Moving average (MA) processes
10. Mixed processes (ARMA)
11. Non-stationary mixed autoregression-moving average (ARIMA) processes
12. Identification and estimation of models of stochastic processes
13. Time series testing and forecasting
- Teacher: Piotr Paradowski
