Financial Time Series

Bertinoro, 8 - 13 July 2019

 

Coordinators:

Alessandra Amendola and Giuseppe Storti

Università di Salerno

Dipartimento di Scienze Economiche e Statistiche

Via Giovanni Paolo II, 132 ...

84084 Fisciano (SA)

e-mail: alamendola@unisa.it , storti@unisa.it

 

Lecturers

Alessandra Amendola, Università di Salerno

Massimiliano Caporin, Università di Padova

Walter Di Staso, Imperial College and Università di Messina

Giuseppe Storti, Università di Salerno

 

Requirements

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).

 

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.

 

Tutorials

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. Data-sets and programming files to make applied econometrics will be provided during the lectures in Bertinoro.

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

Venue and timetables

The Module 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, 15:00-17:00; tutorials and individual hands-on sessions: 17:00-19:00.

Saturday: lectures 9:00-13:00

 

 

Fees and Enrollment

  •  Students, new graduated students, PhD students and temporary university staff: 650€
  •  University staff: 800€ 
  •  Others: 2300€

Fee includes: accommodation (usually in doube room with breakfast and lunch starting from Sunday evening.

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

  •  Students, new graduated students, PhD students and temporary university staff: 550€ per Course
  •  University staff: 700€ per Course
  •  Others: 2000€ per Course

Contacts