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Financial Industry Ontologies for Risk and Regulation Data (FIORD) – A Position Paper
Adamantios Koumpis / Allan D. Grody / Cal Muckley / Donald Lawrence / Fokion Zervoudakis / Jeroen Van Grondelle / Justin Mccarthy / Kiran Fernandes / Kyriakos Chourdakis / Laurentiu Vasiliu / Panos Xidonas / Said Tabet / Thanassis Bouras / Theodoros Krintas
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Financial Industry Ontologies for Risk and Regulation Data (FIORD) – A Position Paper

Paper2013

by Adamantios Koumpis, Allan D. Grody, Cal Muckley, Donald Lawrence, Fokion Zervoudakis, Jeroen Van Grondelle, Justin Mccarthy, Kiran Fernandes, Kyriakos Chourdakis, Laurentiu Vasiliu, Panos Xidonas, Said Tabet, Thanassis Bouras, Theodoros Krintas

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

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  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.

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  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.

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