|
Introduction to Matlab or Octave programming. Descriptive statistics of financial variables on empirical examples.
Linear models of financial variables. Estimation, verification and interpretation of ARMA models. Estimation and verification of the dynamic, linear models of financial variables in Matlab, Octave or Gretl on empirical examples.
Discussion on market volatility measures and their estimation methods. Statistical verification of volatility clustering. Empirical verification of the volatility clustering effect in Matlab, Octave or Gretl.
ARCH/GARCH models: theoretical construction, properties, goodness-of-fit assessment. Estimation and verification of ARCH and GARCH models on empirical data in Gretl, Octave or Matlab.
Extensions of GARCH models with respect to the conditional variance and the distributions of the error term. CAViaR models. Empirical examples of GARCH model extensions in Gretl, Octave or Matlab.
Econometric forecasting of market volatility. Assessment of market risk with the Value at Risk (VaR) and the Expected Shortfall (ES). Backtesting methods. Empirical examples of VaR/ES estimation and backtesting in Gretl, Octave or Matlab.
Alternative measures of volatility. Value at risk for the portfolio of assets.
Introduction to the high-frequency finance. Market microstructure effects. Empirical examples of market microstructure analyses.
Econometric methods for event studies. Examples of the event study analysis in Excel, Octave or Matlab.
Discussion on the concept of efficient markets. Statistical methods for verification of market efficiency. Statistical tests of market efficiency in Gretl, Octave or Matlab.
Application of cross-section regression models for the analysis of financial markets. The Capital Asset Pricing Model (CAPM). Estimating and testing CAPM.
Arbitrage pricing model (APT): assumptions, properties, empirical analysis. APT model estimation/verification.
Survey of major models for credit risk assesment. Credit scoring and estimation of transition matrices. Logit and probit models in credit risk evaluation.
Estimation of PD and LGD in Matlab. Introduction into survival models of credit risk. Stress-testing credit risk. Validating scoring systems and credit risk moels. Examples in Excel and in Matlab.
|
