Estimating the Spectral Risk Measure with Distorted Functions over Normal and Uncertainty Market Events

Modelos como el VaR y el CVaR han demostrado no ser eficaces en predecir pérdidas en crisis, como la pandemia de covid-19. Aunque son coherentes bajo condiciones normales de mercado, no asignan peso a las pérdidas por su tamaño, especialmente en eventos extremos. Este estudio propone un enfoque robusto en la implementación de una medida espectral de riesgo basada en funciones de distorsión para mejorar la estimación de pérdidas en eventos normales y extremos de mercado, superando las limitaciones de mediciones tradicionales. Al integrar funciones de distorsión, se tiene una medida espectral que asigna peso a las pérdidas por el tamaño de esta, y se ajusta a perfiles aversos o inexpertos, así como para aquellos experimentados, midiendo el riesgo de mercado correctamente. Este enfoque optimiza la gestión de portafolios, mejora la estimación de riesgos, afina las prácticas financieras y bancarias, y robustece la medición de riesgo de mercado.

• Publication year

  2025

• Venue

  ODEON

• Publication date

  2025-11-21

• Fields of study

  Not labeled

• Identifiers
  DOI 10.18601/17941113.n28.04
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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