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Singular spectrum analysis for modelling the hard-to-model risk factors

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Abstract

The modelling of the hard-to-model risks factors is one of the topics of great interest to the financial industry. The industry is spending lots of resources on efforts to account for the hard-to-model risks in their risk management frameworks. Currently, the concept describing these risks is the Risk Not in VaR. In its turn, the newly composed Fundamental Review of the Trading Book text similarly prescribes to classify risk factors that do not have a history of continuously available real prices as non-modellable risk factors. Both entities and financial regulatory authorities have shown great concern in the search for efficient techniques and models that allow for a more accurate estimation of the risks factors linked to the derivatives. An accurate modelling of these risk factors can lead to considerable optimization in the capital charges, but any model assumption must be duly justified and supported by the entities. In this paper, the (Multichannel) Singular Spectrum Analysis for modelling these risk factors is analysed.

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Notes

  1. In general, government senior CDS do not present so many problems of scarce data. However, in CDS with other types of associated debt (e.g. subordinated) or corporate CDS, the illiquidity and therefore the lack of data is a widespread problem that needs to be solved.

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Authors and Affiliations

  1. Market Risk, CIB, Santander Bank, Ciudad Grupo Santander Edf. Marisma pl. 1, 28660, Boadilla del Monte, Madrid, Spain

    Andrés Berenguer, Luis Gandarias & Álvaro Arévalo

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  1. Andrés Berenguer
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  2. Luis Gandarias
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  3. Álvaro Arévalo
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Correspondence to Andrés Berenguer.

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Berenguer, A., Gandarias, L. & Arévalo, Á. Singular spectrum analysis for modelling the hard-to-model risk factors. Risk Manag 22, 178–191 (2020). https://doi.org/10.1057/s41283-020-00060-5

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  • DOI: https://doi.org/10.1057/s41283-020-00060-5

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