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Foundation ERM Session 4: Market Risk
This presentation is based on a part of an academic course on Enterprise Risk Management (ERM) titled ‘Market Risk’ and covers topics such as: the definition of ‘market’ risk, statistical techniques for estimating VaR (Value-at-Risk) and TE (tracking error) including parametric, non-parametric and market-implied approaches and interaction with matrix algebra including application of principal components analysis
Slides
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Session 4: Market Risk
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Session 4: Market Risk
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What is market risk?
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Typical approaches (1)
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Axioms
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Typical approaches (2)
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Session 4: Market Risk
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Statistical techniques for estimating risk measures
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Session 4: Market Risk
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Parametric Approach
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Issues
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Incomplete or out-of-date data
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Non-linear exposures
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Call option price
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Heteroscedasticity
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GARCH models
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Properties of GARCH models
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RiskMetrics approach
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RiskMetrics specification
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Session 4: Market Risk
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Non-parametric approach: order statistics
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Standard errors in non-parametric approach
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Maximum Likelihood Estimation
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Log likelihood
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Desirable properties of ML estimator
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Likelihood ratio tests
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Binomial back testing
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Introducing a restriction
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Goldman Sachs VaR model
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New directions for market risk: IRC
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New directions for market risk: Stress VaR
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Session 4: Market Risk
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Market-implied risk statistics
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Session 4: Market Risk
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Interaction with matrix algebra: principal components
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Principal components - explanation or noise?
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Smaller eigenvalues/principal components
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Important Information
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