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SAFE: An early warning system for systemic banking risk

Author

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  • Timothy Bianco
  • Ryan Eiben
  • Dieter Gramlich
  • Mikhail V. Oet
  • Stephen J. Ong
  • Jing Wang

Abstract

This paper builds on existing microprudential and macroprudential early warning systems (EWSs) to develop a new, hybrid class of models for systemic risk, incorporating the structural characteristics of the fi nancial system and a feedback amplification mechanism. The models explain fi nancial stress using both public and proprietary supervisory data from systemically important institutions, regressing institutional imbalances using an optimal lag method. The Systemic Assessment of Financial Environment (SAFE) EWS monitors microprudential information from the largest bank holding companies to anticipate the buildup of macroeconomic stresses in the financial markets. To mitigate inherent uncertainty, SAFE develops a set of medium-term forecasting specifi cations that gives policymakers enough time to take ex-ante policy action and a set of short-term forecasting specifications for verification and adjustment of supervisory actions. This paper highlights the application of these models to stress testing, scenario analysis, and policy.

Suggested Citation

  • Timothy Bianco & Ryan Eiben & Dieter Gramlich & Mikhail V. Oet & Stephen J. Ong & Jing Wang, 2011. "SAFE: An early warning system for systemic banking risk," Working Papers (Old Series) 1129, Federal Reserve Bank of Cleveland.
    • Handle: RePEc:fip:fedcwp:1129
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    More about this item

    Keywords

    Systemic risk; Liquidity (Economics);

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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