Forecasting bank failures: Timeliness versus number of failures
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Li, Guo
Sanning, Lee W
Shaffer, Sherrill
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Routledge, Taylor & Francis Group
Abstract
Motivated by the observation that very few banks fail in normal years, we explore the impact of that pattern on the precision of a standard statistical failure model and discuss implications for regulation and risk management. Out-of-sample forecasting is found to be worse for a model fitted to recent data with few failures than for a model fitted to much older data with more failures.
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Applied Economics Letters
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2037-12-31
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