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Economics

Multivariate Garch (Volatility) Models For Risk Management

When:

26 January - 03 February 2023

School:

TStat Training

Institution:

TStat Training

City:

Sulmona

Country:

Italy

Language:

English

Credits:

0 EC

Fee:

710 EUR

Interested?
Please note: this course has already ended
Multivariate Garch (Volatility) Models For Risk Management
Online

About

The growth in financial instruments during the last decadeĀ has resulted in a significant development of econometricĀ methods (financial econometrics) applied to financialĀ data. The objective of our Multivariate Garch Models forĀ Risk Management course is to provide participants with aĀ comprehensive overview of the principal methodologies,Ā both theoretical and applied, adopted for the analysis ofĀ risk in financial markets. To this end, the course focuses onĀ the modelling and forecasting of financial time series and inĀ particular modelling returns and volatility in asset returns;Ā the modelling of cross market correlations, volatility spilloversĀ and contagion in financial asset markets; andĀ the implementation of both factor models and principalĀ components analysis for the identification of specific asset,Ā country and global factors. The course concludes with anĀ analysis of the available risk management tools/measuresĀ widely adopted in academia and the financial sector. During theĀ course, a number of alternative GARCHĀ models, models of conditional correlations, and Value at RiskĀ models will be reviewed.

In common with TStat’s training philosophy, throughoutĀ the course the theoretical sessions are reinforced by caseĀ study examples, in which the course tutor discusses currentĀ research issues, highlighting potential pitfalls and theĀ advantages of individual techniques. The intuition behindĀ the choice and implementation of a specific technique isĀ of the utmost importance. In this manner, course leadersĀ are able to bridge the ā€œoften difficultā€ gap betweenĀ abstract theoretical methodologies, and the practicalĀ issues one encounters when dealing with real data. At theĀ end of the course, participants are expected to be able toĀ autonomously implement the theories and methodologiesĀ discussed in the course.

Target group

The course is of particular interest to: i) Master and Ph.D.Ā Students and researchers in public and private researchĀ centres, and ii) professionals employed in risk management inĀ the following sectors: asset management, exchange rate andĀ market risk analysis, front office and research in investmentĀ banking and insurance, needing to acquire the necessaryĀ econometric/statistical toolset to independently conduct anĀ empirical analysis of financial risk.

Course aim

The growth in financial instruments during the last decadeĀ has resulted in a significant development of econometricĀ methods (financial econometrics) applied to financialĀ data. The objective of our Multivariate Garch Models forĀ Risk Management course is to provide participants with aĀ comprehensive overview of the principal methodologies,Ā both theoretical and applied, adopted for the analysis ofĀ risk in financial markets. To this end, the course focuses onĀ the modelling and forecasting of financial time series and inĀ particular modelling returns and volatility in asset returns;Ā the modelling of cross market correlations, volatility spilloversĀ and contagion in financial asset markets; andĀ the implementation of both factor models and principalĀ components analysis for the identification of specific asset,Ā country and global factors. The course concludes with anĀ analysis of the available risk management tools/measuresĀ widely adopted in academia and the financial sector. During theĀ course, a number of alternative GARCHĀ models, models of conditional correlations, and Value at RiskĀ models will be reviewed.

Fee info

Fee

710 EUR, Full-time Students*: € 710.00Ph.D. Students: € 910.00Academic: € 1010.00Commercial: € 1350.00*To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year. Our standard policy is to provide all full-time students, be they Undergraduates or Masters students, access to student participation rates. Part-time master and doctoral students who are also currently employed will however, be allocated academic status.

Interested?

When:

26 January - 03 February 2023

School:

TStat Training

Institution:

TStat Training

Language:

English

Credits:

0 EC

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