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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
- Statistical models for risk management
- Outline
- Definisions of returns
- Annualize multiyear returns
- Log return and multiperiod return
- Dividend paying assets
- Excess return
- Distribution of returns
- Problems (1)
- Problems (2)
- Log-normal
- Log-returns
- Final equation
- Basic definition of normal random variable
- Finding all moments
- Log-normal and historical returns
- Returns - summary of stylized facts
- Notation
- Skewness and kurtosis - definition
- Note
- Autocovariance
- Stationarity (1)
- Stationarity (2)
- Autocorrelation
- Distributional model for asset return (1)
- Distributional model for asset return (2)
- Distributional model for asset return (3)
- Models of conditional variance
- ARCH/GARCH (1)
- ARCH/GARCH - properties
- ARCH/GARCH (2)
- Stochastic volatility (SV) models (1)
- Stochastic volatility (SV) models (2)
- Distribution of returns - multivariate
- Multivariate normal distribution
- Note - multivariate normal distribution (1)
- Note - multivariate normal distribution (2)
- Mixture distributions (1)
- Mixture distributions (2)
- Mixture distributions (3)
- Multivariate GARCH processes (1)
- Multivariate GARCH processes (2)
- Non-linear dependence and copulas
- Note - non-linear dependence
- Sklar's theorem (Sklar (1959)) (1)
- Sklar's theorem (Sklar (1959)) (2)
- Rank correlation, tail dependence and copulas (1)
- Rank correlation, tail dependence and copulas (2)
- Rank correlation, tail dependence and copulas (3)
- Tail dependence
- Copulas - types
- Bivariate Gaussian copula (1)
- Bivariate Gaussian copula (2)
- t copula
- Gumbel copula
- Clayton copula
- References and further reading (1)
- References and further reading (2)
- Further reading
Topics Covered
- Definition of returns: simple returns and log returns
- Distribution of returns, univariate: normal and log-normal distribution
- Stylized facts of historical returns
- Skewness, kurtosis, autocorrelation and stationarity
- ARCH, GARCH and stochastic volatility (SV) models
- Distribution of returns, multivariate: multivariate normal distribution
- Multivariate GARCH and SV models
- Copulas and non-linear dependence
Talk Citation
Knight, J. (2007, October 1). Statistical models for risk management [Video file]. In The Business & Management Collection, Henry Stewart Talks. Retrieved January 2, 2025, from https://doi.org/10.69645/SNSS5157.Export Citation (RIS)
