New sources of finance
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33 min
1. Risk management: some lessons from the credit crisis- Mr. Edward Fishwick
- Archived Lectures *These may not cover the latest advances in the field
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22 min
2. The need for a new paradigm- Mr. Alan Brown
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41 min
3. Leading bank credit portfolio strategies- Mr. Brian Dvorak
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26 min
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18 min
5. Quantmare, August 2007- Mr. Eoin Murray
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36 min
6. Risk decomposition (and risk budgeting)- Mr. Jason MacQueen
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43 min
7. Structural and reduced form models- Dr. Theo Darsinos
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43 min
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40 min
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52 min
10. Estimating risk models- Prof. Kevin Dowd
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24 min
11. Hedge fund risk assessment- Mr. David Martin
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45 min
12. Modeling business dependencies for credit portfolios- Dr. Markus A. Leippold
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26 min
13. VaR when volatility is changing- Dr. Elizabeth Sheedy
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30 min
14. Conditional Value at Risk (CoVAR)- Mr. KiHoon Jimmy Hong
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40 min
15. Dependence modeling with copulas- Prof. Paul Embrechts
- Dr. Johanna Neslehova
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41 min
16. Extreme value theory and copulas- Prof. Paul Embrechts
- Dr. Johanna Neslehova
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42 min
17. Measures of financial risk- Prof. Kevin Dowd
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37 min
18. Modelling UK Mortgage Default in Light of the Financial Crisis- Mr. Warapong Wongwachara
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23 min
19. Statistical models for risk management- Prof. John Knight
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34 min
20. The structure of equity risk models- Mr. Jason MacQueen
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42 min
21. Utility theory and mean variance- Dr. Norvald Instefjord
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40 min
22. Definitions of risk- Dr. Norvald Instefjord
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29 min
23. Practical use of portfolio risk management today- Mr. Daryl Roxburgh
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44 min
24. Volatility- Dr. George A. Christodoulakis
Printable Handouts
Navigable Slide Index
- Introduction
- Definition of volatility
- Risk
- Risk measures
- Risk measures - example 1
- Risk measures - example 2
- Risk measures - summary
- Empirical characteristics of S and P 500
- Empirical characteristics of S and P 500 returns
- Correlogram of SP500
- S and P 500 squared returns
- S and P 500 absolute returns
- Empirical characteristics of high-frequency returns
- Rolling window volatility
- Volatility modelling (1)
- Volatility modelling (2)
- The ARCH family of models (1)
- The ARCH family of models - a long lag structure
- The ARCH family of models (2)
- GARCH (1,1) news-impact curve (1)
- GARCH (1,1) news-impact curve (2)
- Asymmetric GARCH processes
- EGARCH
- EGARCH (1,1) news-impact
- Estimation
- Maximum likelihood
- Empirical example - ARCH(p)
- Empirical example - GARCH(1,1), EGARCH(1,1)
- Model assessment
- Robust standard errors
- Model selection
- Likelihood ratio test
- Bayesian criteria: Akaike, Schwarz
- Stochastic volatility
- Risk-metrics
- Forecasting
- Forecasting asset returns under ARCH errors
- Confidence intervals for S and P 500 returns
- Forecasting volatility with ARCH (1)
- Forecasting volatility with GARCH (1,1)
- Forecasting with stochastic volatility
- Forecast error statistics
- Pathology of error statistics
- Volatility forecast evaluation
- Volatility forecast evaluation - different approches
- Implied volatility - exchange-traded options
- Implied volatility (1)
- Implied volatility (2)
- Black-scholes implied volatility (1)
- Black-scholes implied volatility (2)
- Implied volatility surface
- References
Topics Covered
- Volatility is the most heavily used measure of risk in financial decision making
- Discussion of validity of various measures of risk
- Statement of conditions under which volatility is a good measure
- Explanation of the empirical properties of data and their dynamics
- Why models need to capture these characteristics
- Analysis of various approaches of volatility estimation with particular emphasis on dynamic models in both univariate and multivariate contexts
- Techniques for volatility model validation
- Explanation of possible pitfalls
- Out-of-sample volatility forecasting using dynamic models and various methods for volatility forecast evaluation
Talk Citation
Christodoulakis, G.A. (2007, October 1). Volatility [Video file]. In The Business & Management Collection, Henry Stewart Talks. Retrieved November 4, 2025, from https://doi.org/10.69645/SSYD9337.Export Citation (RIS)
