An application of extreme value theory in estimating liquidity risk

  1. Sonia Benito Muela 1
  2. Carmen López Martín 2
  3. Raquel Arguedas Sanz 1
  1. 1 Universidad Nacional de Educación a Distancia
    info

    Universidad Nacional de Educación a Distancia

    Madrid, España

    ROR https://ror.org/02msb5n36

  2. 2 Universidad Carlos III de Madrid
    info

    Universidad Carlos III de Madrid

    Madrid, España

    ROR https://ror.org/03ths8210

Revista:
European Research on Management and Business Economics

ISSN: 2444-8834

Año de publicación: 2017

Volumen: 23

Número: 3

Páginas: 157-164

Tipo: Artículo

DOI: 10.1016/J.IEDEEN.2017.05.001 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: European Research on Management and Business Economics

Resumen

The last global financial crisis (2007–2008) has highlighted the weaknesses of value at risk (VaR) as a measure of market risk, as this metric by itself does not take liquidity risk into account. To address this problem, the academic literature has proposed incorporating liquidity risk into estimations of market risk by adding the VaR of the spread to the risk price. The parametric model is the standard approach used to estimate liquidity risk. As this approach does not generate reliable VaR estimates, we propose estimating liquidity risk using more sophisticated models based on extreme value theory (EVT). We find that the approach based on conditional extreme value theory outperforms the standard approach in terms of accurate VaR estimates and the market risk capital requirements of the Basel Capital Accord.

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