Alessandra Amendola and Giuseppe Storti
Università di Salerno
Dipartimento di Scienze Economiche e Statistiche
Via Giovanni Paolo II, 132
84084 Fisciano (SA)
e-mail: ,


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 (asymmetric GARCH, component models)
Ex-post estimation of volatility (including realized measures based on intra-daily information and their properties)
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) \>\>\>\>\>

Reference textbooks and suggested readings:

  • Bauwens L., Hafner C., Laurent S. Eds (2012) Handbook of Volatility Models and Their Applications, Wiley, NY.Christoffersen P. (2016) Elements of Financial Risk Management, 2nd Edition. Academic Press
  • Francq C., Zakoian J-M. (2010) GARCH Models: Structure, Statistical Inference and Financial Applications, Wiley, NY.
  • Tsay, R. (2005) Analysis of Financial Time Series (2nd Edition), Wiley Series in Probability and Statistics.

Handouts, further readings and material will be provided before the beginning of the course and during the lectures.



Theoretical lectures are associated with working sessions; during them you will receive the suggestions needed to use an econometric software and to run your own empirical analysis.

For the practical tutorials and applications participants will use the  software R and Matlab, which will have to be installed on their own laptops.


Program is conditional to the recruitment of a minimum of 15 participants


Venue and timetables

Venue: The Module will be held in the Bank of Italy's Scuola di Automazione per Dirigenti Bancari (SADiBa), via San Marco n.54, Perugia. Participants will be accommodated at SADiBa.

Lectures and tutorials will be in English, with the following schedule (provisional):

Tuesday to Friday: lectures: 9.00-13.00, 15.00-17.00; tutorials: 17.15-19.00

Saturday: lectures: 9.00-13.00.


Fees and Enrollment

  •  Students, PhD students and temporary university staff: 650€
  •  University staff: 800€ 
  •  Others: 2000€

Fee includes: Full board accommodation (usually in double room) starting from Monday.

Partecipants who wish to attend two or three Courses, are allowed the following reduced fees per Course

  •  Students, PhD students and temporary university staff: 550€ per Course
  •  University staff: 700€ per Course
  •  Others: 1600€ per Course