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Program

EN IT

Updated A.Y. 2020-2021

  1. Introduction
    Asset returns. Stylized facts: asymmetry, kurtosis and volatility clustering. Stochastic processes: stationarity, purely random processes (white noise). Random walks, with and without drifts.
  2. Review of prediction theory: forecasting schemes, forecast evaluation, forecast with nonstationary models: exponential smoothing.
  3. Volatility measurement and analysis
    Autoregressive Conditional Heteroscedasticity (ARCH) models: specification, properties, maximum likelihood estimation, prediction. Extensions: ARCH in mean.
    Generalized ARCH models and extensions: Integrated GARCH, Exponential GARCH models, GJR GARCH. Stochastic Volatility models
  4. Multivariate GARCH models. VECH, diagonal VECH and BEKK. 
  5. Switching and state space models
  6. Risk measurement: Value at Risk and expected shortfall.