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 Factor Models & Risk Management Tools course is to provide participants with a comprehensive overview of the principal methodologies, both theoretical and applied, adopted for risk analysis and risk management. To this end, the course focuses on the implementation of both factor models and principal components analysis for the identification of specific asset, country and global risk factors and on risk management tools/measures.
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: FACTOR MODELS
Static and dynamic factors, factor estimation, determining the number of factors, nonstationary factor models;
Identifying global, asset related and country specific factors in data with a large number of assets with principal component analysis and static and dynamic factor models;
Applications of factor analysis to (bond and asset) portfolio management, stock liquidity and its determinants.
SESSION II: RISK MANAGEMENT TOOLS
Porfolio Value-at-Risk (VaR):
Approaches for estimating VaR:
Parametric VaR, Historical simulation VaR
Monte Carlo VaR
Expected Shortfall (ES) and Tail Risk (TR)
Duration based tests of independence
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 2023 training calendar. We therefore ask that you re-visit our website periodically or contact us at email@example.com should the dates for the course which you are interesting in following not yet be published. You will then be contacted via email as soon as the dates are available.
Professor Giovanni URGA, Faculty of Finance and Centre for Econometric Analysis, Bayes Business School, London (UK).
The objective of our Factor Models & Risk Management Tools course is to provide participants with a comprehensive overview of the principal methodologies, both theoretical and applied, adopted for risk analysis and risk management.
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