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The information in systemic risk rankings

Author

Listed:
  • Schwaab, Bernd
  • Koopman, Siem Jan
  • Lucas, André
  • Nucera, Federico

Abstract

We propose to pool alternative systemic risk rankings for financial institutions using the method of principal components. The resulting overall ranking is less affected by estimation uncertainty and model risk. We apply our methodology to disentangle the common signal and the idiosyncratic components from a selection of key systemic risk rankings that have been proposed recently. We use a sample of 113 listed financial sector firms in the European Union over the period 2002-2013. The implied ranking from the principal components is less volatile than most individual risk rankings and leads to less turnover among the top ranked institutions. We also find that price-based rankings and fundamentals-based rankings deviated substantially and for a prolonged time in the period leading up to the financial crisis. We test the adequacy of our newly pooled systemic risk ranking by relating it to credit default swap premia. JEL Classification: E

Suggested Citation

  • Schwaab, Bernd & Koopman, Siem Jan & Lucas, André & Nucera, Federico, 2016. "The information in systemic risk rankings," Working Paper Series 1875, European Central Bank.
  • Handle: RePEc:ecb:ecbwps:20161875
    Note: 955417
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    References listed on IDEAS

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    More about this item

    Keywords

    banking supervision; financial regulation; forecast combination; risk rankings; systemic risk contribution;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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