COURSE LEADERS: GIOVANNI URGA
COURSE ID: D-EF37-OL
LANGUAGE:
The growth in financial instruments during the last decade has resulted in a significant development of econometric methods (financial econometrics) applied to financial data. The objective of our Modelling Volatility and Contagion in Finance course is to provide participants with a comprehensive overview of the principal methodologies, both theoretical and applied, adopted for the analysis of risk in financial markets. To this end, the course focuses on the modelling and forecasting of financial time series of asset returns; the modelling of cross market correlations, volatility spillovers and contagion in financial asset markets. During the course, a number of alternative GARCH models and models of conditional correlations will be reviewed.
In common with TStat’s training philosophy, throughout the course the theoretical sessions are reinforced by case study examples, in which the course tutor discusses current research issues, highlighting potential pitfalls and the advantages of individual techniques. The intuition behind the choice and implementation of a specific technique is of the utmost importance. In this manner, course leaders are able to bridge the “often difficult” gap between abstract theoretical methodologies, and the practical issues one encounters when dealing with real data. At the end of the course, participants are expected to be able to autonomously implement the theories and methodologies discussed in the course.
The course is of particular interest to: i) Master and Ph.D. Students and Researchers in public and private research centres, and ii) professionals employed in risk management in the following sectors: asset management, exchange rate and market risk analysis, front office and research in investment banking and insurance, needing to acquire the necessary econometric/statistical toolset to independently conduct an empirical analysis of financial risk.
Participants should have a knowledge of the inferential statistics and introductory econometric methods illustrated in Brooks (2019).
SESSION I: VOLATILITY MODELS – GARCH
Analysis of financial time series features:
Stationarity
Autocorrelation
Conditional heteroscedasticity
Fat tails
Modelling and forecasting asset returns volatility with univariate ARCH and GARCH models:
SAARCH
EGARCH
GJR
TGARCH
APARCH
News Impact Curve
SESSION II: MULTIVARIATE VOLATILITY (MGARCH) MODELS AND CONTAGION
Multivariate GARCH models:
Diagonal VECH (DVECH)
Constant Conditional Correlation (CCC)
Dynamic Conditional Correlation (DCC) models
Assessing contagion in financial markets:
Measuring cross-market correlation coefficients
Higher moments contagion
Estimating Markov switching regressions
Empirical applications:
Forecasting volatility and correlations in financial markets
Contagion between markets
SUGGESTED READING (PRE – AND POST- COURSE)
Introductory Econometrics for Finance. Brooks, C., (2019). Cambridge University Press, 4th edition.
Financial Econometrics Using Stata. Boffelli, S., and G. Urga (2016). Stata Press Publication.
We are currently putting the finishing touches to our 2024 training calendar. We therefore ask that you re-visit our website periodically or contact us at training@tstat.it should the dates for the course which you are interested in following not yet be published. You will then be contacted via email as soon as the dates are available.
Professor Giovanni URGA, Faculty and Centre for Econometric Analysis, Bayes Business School, London (UK).
ONLINE FORMAT
The objective of our Modelling Volatility and Contagion in Finance course is to provide participants with a comprehensive overview of the principal methodologies, both theoretical and applied, adopted for the analysis of risk in financial markets.