Financial Econometrics: Risk Modeling and Forecasting
Bertinoro, 28 June - 4 July 2026
Coordinators:
Alessandra Amendola and Giuseppe Storti
University of Salerno
Department of Economics and Statistics
Via Giovanni Paolo II, 132
84084 Fisciano (SA)
e-mail: alamendola@unisa.it , storti@unisa.it
Lecturers
Alessandra Amendola, University of Salerno
Vincenzo Candila, University of Salerno
Massimiliano Caporin, University of Padua
Demetrio Lacava, Università di Messina
The maximum number of allowed participants in presence is 25.
Requirements
Intermediate knowledge of statistical inference and econometrics.
Schedule of the course:
1) Modeling financial returns using end-of-day data:
- Introduction to financial time series.
- Univariate and Multivariate GARCH models.
2) High-frequency econometrics:
- Features of intra-daily data and the estimation of realized measures and jumps.
- GARCH type models using realized information (Realized GARCH, HEAVY).
- Dynamic models for realized measures (HAR, MEM).
- Realized covariances and correlations: estimation challenges and dynamic models.
3) Portfolio analysis:
- An introduction to portfolio allocation
- Factor models: linear observable factors specification and estimation.
- Estimating risk premia in cross-section, Fama-MacBeth regressions.
4) Risk management:
- Risk measures: Value-at-Risk (VaR), Expected Shortfall (ES), and their properties; parametric, non-parametric, and semiparametric approaches to estimate VaR and ES.
- Evaluation of volatility and risk forecasts.
Reference textbooks and suggested readings:
- Aït-Sahalia Y., Jacod J. (2014) High-frequency Financial Econometrics, Princeton University Press.
- Aït-Sahalia Y., Hansen L.P. (2010) Handbook of Financial Econometrics: Tools and Techniques, North Holland.Bauwens L., Hafner C., Laurent S. (2012) Handbook of Volatility Models and Their Applications, Wiley.
- Christoffersen P. (2016) Elements of Financial Risk Management, Academic Press.
- Francq C., Zakoian J.M. (2010) GARCH Models: Structure, Statistical Inference and Financial Applications, Wiley.
- Hautsch N. (2012) Econometrics of Financial High-Frequency Data, Springer.
- Laopodis N.T. (2022) Financial Economics and Econometrics, Routledge Taylor & Francis Group.
- Linton O. (2019) Financial Econometrics: Models and Methods, Cambridge University Press.
- Turan G. Bali, Robert F. Engle, Scott Murray (2016) Empirical Asset Pricing: The Cross Section of Stock Returns, Wiley.
Handouts, further readings and material will be provided before the beginning of the course and during the lectures.
Tutorials and Software
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. Datasets and programming files to make applied econometrics will be provided during the lectures.
For the practical tutorials and applications participants will use the softwares R and Matlab, which will have to be installed on their own laptops.
Venue and timetables
Each Module requires a full-time attendance. The course will last one week and will be held in the University Residential Centre, Via Frangipane 6, 47032 Bertinoro (FC). Participants will be hosted in the Centre guest quarters, (as an exception, in case of reduced availability of rooms in the Centre, they will be accommodated in local hotels).
Lectures and tutorials will be in English, with the following schedule:
** Monday to Friday: lectures: 9.00-13.00, 15.30-17.20; tutorials: 17.40-19.30.
** Saturday: lectures: 9.00-13.00.
Contacts
- For more information: Roberta Partisani phone: +39 0543446554 ; e-mail: info@side-iea.it
- For administrative issues: Fabrizio Zanotti (admin@side-iea.it), phone:0543446561;
- For travel and accommodation: Roberta Partisani (rpartisani@ceub.it), phone: +39 0543446554
