(in Polish) Financial econometrics 1155-12-F21-0-FinEc

Univariate time series models
1.1. Stochastic processes and time series - introduction
1.2. Stationary time series models: AR(p), MA(q), ARMA(p,q) – identification, estimation, and forecasting
1.3 Examples of models for returns, currency exchange rates; changes, models of the returns distribution
Non-stationary time series models
2.1. Unit root tests
2.2 ARIMA (p,d,q) model and random walk
2.3. Cointegration and error correction model
2.4. Examples of applications of non-stationary time series models in finance
Financial time series characteristics
3.1 Basic definitions
3.2 Returns distributions and their consequences
3.3 Efficient market hypothesis
3.4 Verification of weak, semi-strong, and strong market efficiency
Univariate volatility models
4.1 Volatility definition
4.2 Basic and generalized ARCH models, testing for ARCH
4.3 GARCH in mean
4.4 Estimation of GARCH models parameters and their evaluation 4.5. Forecasting using GARCH model
4.6 Stochastic volatility model (SV)
4.7 Applications of volatility models (VaR, ES)