Financial Management · 1993 · 473 citations · 25 references
BusinessFinanceInsuranceForecastingMachine LearningPredictive AnalyticsFinancial DistressFinancial ForecastingFinancial RiskNeural NetworksRisk ClassificationRisk ForecastingBank Distress PredictionDistress ClassificationDistress Signal DetectionDistress SignalsFinancial Distress MonitoringNeural Network DiagnosticsNeural Network ModelingNeural Network-based Diagnosis
Neural networks are a novel mathematical approach for detecting discriminative patterns in data, and reliable early forecasts of firms’ financial health are essential for lenders, investors, analysts, portfolio managers, insurers, and other finance professionals. The study builds neural networks to estimate firms’ future financial health and to detect early warning signals of distress in currently viable firms. Neural networks are employed to identify financial data patterns that consistently differentiate healthy firms from distressed ones and to estimate their future financial health.
This study builds neural networks (NNs) which estimate the future financial health of firms. A neural network is a relatively new mathematical approach for recognizing discriminating patterns in data. We use NNs here to identify financial data patterns which consistently distinguish generally healthy firms from distressed ones. The purpose is to detect early warning signals of distressful conditions in currently viable firms. Being able to form highly reliable early forecasts of the future health of firms is critical to bank lending officers, investors, market analysts, portfolio managers, insurers, and many others in the field of finance.
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Classification and Regression Trees.
John Van Ryzin, Leo Breiman, Jerome H. Friedman et al. · Journal of the American Statistical Association · 1986 · 21K citations
An introduction to computing with neural nets
Richard P. Lippmann · IEEE ASSP Magazine · 1987 · 7.9K citations