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Testing Expected Shortfall Models for Derivative Positions
Kerkhof, F.L.J. / Melenberg, B. / Schumacher, J.M.
derivatives / hypothesis testingResource overview

Testing Expected Shortfall Models for Derivative Positions

Paper2003

by Kerkhof, F.L.J., Melenberg, B., Schumacher, J.M.

Tags
derivativeshypothesis testingrisk management

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Suggested foundations for risk measurement and stress and options and derivatives pricing. Specialist prerequisites vary by paper.

Before you read

  1. Random Variables and Distributions

    Represent losses as a distribution rather than one forecast.

  2. Expected Shortfall and Other Tail Risk Measures

    Distinguish a loss quantile from the average loss in the tail.

  3. The Binomial Model

    Build replication and risk-neutral probabilities in a tractable model.

  4. Market Model and Risk-Neutral Valuation

    Distinguish pricing probabilities from physical forecasts.

Go further

  1. VaR Estimation in Practice: Variance-Covariance, Historical Simulation, Monte Carlo

    Compare risk estimators and their assumptions.

  2. Backtesting VaR and ES: Coverage Tests and Model Validation

    Check forecasts against realised losses.

  3. The Black-Scholes PDE, Formula and Implied Volatility

    Connect the pricing equation, closed-form value and implied volatility.

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