The student acquires the skills of recognizing and studying relationships between economic phenomena and the skills of modeling socio-economic phenomena by collecting real statistical data, selecting suitable explanatory variables for modeling, creating a model using a suitable method, its verification, and the interpretation of obtained results. The student explores some possibilities of application econometric models for explaining and describing economic phenomena and let to know the limitation of their application.
Wymagania wstępne
Probability theory, mathematical statistics, econometrics.
Zakres tematyczny
Lecture
Stationarity and non-stationarity of the process. Autocorrelation and partial autocorrelation function. (2 hours)
Autoregressive, moving average, and mixed models: AR, MA, ARMA, ARIMA. Identification of the process. (2 hours)
Estimation of structural parameters. Unit roots. (2 hour)
Multidimensional stochastic processes. (1 hour)
Cointegration. (2 hours)
Models of GARCH type. Estimation. (1 hour)
Analysis of the distribution of prices and rates of return. (1 hour)
Modeling of a portfolio, the hypothesis of the effective market, the hypothesis of rational expectation, pricing of options. (2 hours)
Estimation and the forecast of measures of risk (Value at Risk). (1 hour)
Laboratory
Modeling of stationary and nonstationary processes. (2 hours)
Autocorrelation and partial autocorrelation function. Tests of significance of autocorrelation and partial autocorrelation function. (2 hours)
Modeling of processes AR, MA, ARMA, ARIMA. Identification of processes. (2 hours)
Estimation of parameters. Unit roots. Analysis of real data. (4 hours)
Multidimensional stochastic processes. Modeling and analysis based on real data. (4 hours)
Cointegration. Modeling and analysis based on real data. (4 hours)
Modeling of processes GARCH. Estimation. Modeling and analysis based on real data. (4 hours)
Analysis of the distribution of prices and rates of return. Modeling and analysis based on real data. (4 hours)
Modeling of a portfolio. Modeling and analysis of real data. (4 hours)
Metody kształcenia
The traditional lecture.
Laboratory – In the first part, the students are modeling the specific types of process, analyze obtaining data, draw conclusions from obtained results. Next, they repeat the analysis using real data.
Efekty uczenia się i metody weryfikacji osiągania efektów uczenia się
Opis efektu
Symbole efektów
Metody weryfikacji
Forma zajęć
Warunki zaliczenia
The student makes the project in order to verify whether the level of acquired knowledge and skills in the course is sufficient.
Writing exam from the problem of forecasting and methods of simulation.
The final mark from this course consists of the following partial marks: laboratory (60%) and exam (40%) provided that both marks are positive.
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