Alessandra Amendola and Giuseppe Storti, Università di Salerno


Alessandra Amendola, Università di Salerno

Massimiliano Caporin, Università di Padova

Walter Di Staso, Imperial College and Università di Messina

Giuseppe Storti, Università di Salerno


Intermediate knowledge of statistical inference and econometrics.

Course outline:

Basics: a one lecture crash-course on stochastic processes and their properties.

Models for daily returns (based on EOD information):

– Models for the conditional mean of returns (level): ARMA and ARIMA models,

– Models for the conditional variance of returns (volatility): GARCH models and their variants.

Ex-post estimation of volatility (including realized measures based on intra-daily information).

Incorporating realized information in volatility prediction:

– GARCH type models using realized information (Realized GARCH, HEAVY);

– Dynamic models for realized measures (HAR,MEM).

Multivariate Volatility models:

– Multivariate GARCH models (MGARCH);

– Dynamic models for realized covariance matrices (short introduction).

Risk management:

– Risk measures: VaR, Expected Shortfall;

— Parametric GARCH based estimation (univariate vs multivariate approach);

— Semi-parametric approaches (CaViaR and CARE models);

– Backtesting (evaluation of volatility forecasts, backtesting VaR and ES).


For more information: Antonella Mallus e-mail:

For administrative issues: Alessandra Picariello phone: +39 0512092637; e-mail: