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Does Basel II Pillar 3 Risk Exposure Data help to Identify Risky Banks?

  • Ralf Sabiwalsky
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    Basel II Pillar 3 reports provide information about banks' exposure towards a number of risk factors, such as corporate credit risk and interest rate risk. Previous studies nd that the quality of such information is likely to be weak. We analyze the marginal contribution of pillar 3 exposure data to the quality of equity volatility forecasts for individual banks. Our method uses (local in time) measures of risk factor risk using a multivariate stochastic volatility model for ve risk factors, and uses measures of bank sensitivity with respect to these risk factors. We use two sets of sensitivity measures. One takes into account pillar 3 information, and the other one does not. Generally, we generate volatility forecasts as if no market prices of equity were available for the bank the forecast is made for. We do this for banks for which such data is, in fact, available so that we can conduct ex post - tests of the quality of volatility forecasts. We nd that (1) pillar 3 information allows for a better-than-random ranking of banks according to their risk, but (2) pillar 3 exposure data does not help reduce volatility forecast error magnitude.

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    Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2012-008.

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    Length: 32 pages
    Date of creation: Feb 2012
    Date of revision:
    Handle: RePEc:hum:wpaper:sfb649dp2012-008
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