Prediction models and recovery strategies for the savings and loan industry : an evaluation of the endogenous and exogenous elements
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Date
1992
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Abstract
It is the purpose of this study to determine the turnaround strategies used by recovered savings institutions and use them to predict which thrifts might regain their solvency given sufficient time. The study focused upon the 2,502 thrifts which existed throughout fourteen semi-annual periods of the time series, 1982 through 1988. Of significance, the findings in this study indicate the nonparametric analysis achieved predictive results as accurately as the "best" logistic regression in the parametric analysis, but with substantially fewer variables. The results of the two analyses have shown that it is possible to utilize the available information from thrift financial reports in such a way as to predict with overall accuracy of better than 85% up to two years in advance of the likelihood of thrift recovery. Subjective decision-making may be substantially reduced when facing the question of whether or not to close a thrift with potential, yet heavily laden with losses such that its capital position has virtually been whittled beyond repair. The contribution of this study is that the results relate to both the thrift regulator who has access to publicly available information regarding thrift financial condition and also to individual thrift managers who have access only to their own thrifts' financial condition. In this study the probability of recovery is found to be a function of capital adequacy, asset quality, expense control, profitability, interest rate and credit risk and organizational form as a stock institution. Most of the variables that were found to be significant in the analyses conducted upon the earlier segment of the time series. 1982 to 1986, continued to be significant in the latter segment of the time series, 1987 to 1988, providing little support to the notion that thrift risks have changed over time from greater exposure to interest rate risk to increased credit risk.
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Vita.
Keywords
Major finance, Bank failures, Forecasting, Banks and banking