Predicting large US commercial bank failures

Predicting Failures of Large U.S. Commercial Banks

Equilibrium Non - Panic Bank Failures ∗

We observe many episodes in which a large number of people attempt to withdraw their deposits from a bank, forcing it to suspend withdrawals or even to fail. In contrast with the view that those episodes are driven by consumers’ panic or sunspots, we propose to explain them as a consequence of the conjunction of lack of full back up of deposits by banks, and of an unexpectedly high fraction of ...

Predicting Plan Failures 33

This paper presents the PlanMine sequence mining algorithm to extract patterns of events that predict failures in databases of plan executions. New techniques were needed because previous data mining algorithms were overwhelmed by the staggering number of very frequent, but entirely unpredictive patterns that exist in the plan database. This paper combines several techniques for pruning out unp...

GenSo-EWS: a novel neural-fuzzy based early warning system for predicting bank failures

Bank failure prediction is an important issue for the regulators of the banking industries. The collapse and failure of a bank could trigger an adverse financial repercussion and generate negative impacts such as a massive bail out cost for the failing bank and loss of confidence from the investors and depositors. Very often, bank failures are due to financial distress. Hence, it is desirable t...

Systemic Funding Liquidity Risk and Bank Failures

We examine the roles of idiosyncratic and systemic funding liquidity risks in bank failures. We estimate a discrete-time hazard model of bank failure using data of U.S. commercial banks between 1985 and 2004, and examine its out-of-sample forecasting performance between 2005 and 2011. The out-of-sample performance comparison shows this model outperforms typical bank failure prediction models. W...