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The ten commandments for optimizing value-at-risk and daily capital charges
McAleer, M.J.
market risk / risk managementResource overview

The ten commandments for optimizing value-at-risk and daily capital charges

Paper2008

by McAleer, M.J.

Tags
market riskrisk managementvolatility forecasting

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Understand this paper

Suggested foundations for risk measurement and stress and volatility models and surfaces. 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. Stochastic Processes, Brownian Motion and Itô's Lemma

    Follow diffusion-based models and their assumptions.

  4. ARCH and GARCH

    Separate conditional volatility from observed returns.

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. Stochastic Volatility and the Heston Model

    Study a correlated stochastic-variance model.

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