Predictability of corporate failure: Models for prediction of corporate failure and for evalution of debt capacity

Van Frederikslust, R.A.I. Van

ISBN 10: 1468471937 / ISBN 13: 9781468471939

Editore: Springer, 2012

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Codice articolo ABLIING23Mar2716030069503

Dati bibliografici

• Titolo: Predictability of corporate failure: Models for prediction of corporate failure and for evalution of debt capacity
• Editore: Springer
• Data di pubblicazione: 2012
• Lingua: Inglese
• ISBN 10: 1468471937
• ISBN 13: 9781468471939
• Rilegatura: Brossura
• Condizione: New

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Riassunto

1. 0 INTRODUCTION. In this chapter we define first in Section I. I the concept of failure used in this study. Thereafter, we discuss briefly the causes and possible consequ­ ences of failure. Finally, we explain in Section 1. 2 the aim of this study. 1. 1 THE CONCEPT OF FAILURE. In this monograph we investigate the predictability of corporate failure. By 'failure' we understand the inability of a firm to pay its obligations when these fall due (i. e. technical cash insolvency). (Walter 1957 and Donaldson 1962 and 1969). Failure mostly appears in a critical situation as a consequ­ ence of a sharp decline in sales. Such a decline can be caused by a recession, the loss of an important customer, shortage of a raw material, deficiencies of management, etc. The ability to predict corporate failure is important for all parties involved in the corporation, in particular for management and investors. An early warning signal of probable failure will enable them to take preventive measures: changes in operating policy or reorganization of financial structure, but also voluntary liquidation will usually shorten the period over which losses are incurred. The possibility to predict failure is important also from a social point of view, because such an event is an indication of misallocation of resources; prediction provides opportunities to take corrective measures. (See also Lev 1974, p. 134). 1. 2 AIM AND OUTLINE OF THE STUDY.

Contenuti

1. Introduction..- 1.0 Introduction.- 1.1 The Concept of Failure.- 1.2 Aim and Outline of the Study.- 2. Recent Studies..- 2.0 Introduction.- 2.1 Discriminant Analysis and the Prediction of Corporate Failure.- 2.2 Usual Foundations for the Choice of used Ratios.- 2.3 A Univariate Model.- 2.4 Multivariate Models.- 2.5 Evaluation.- 3. A Failure Prediction Model With Financial Ratios as Prediction Variables..- 3.0 Introduction..- 3.1 Donaldson’s Approach.- 3.2 A Definition of Failure in Terms of Cash Flow Concepts.- 3.3 Choice of a Failure Prediction Model...- 3.4 Identification of Prediction Variables of the Failure Prediction Model..- 4. The Failure Prediction Model With The Levels of Ratios as Prediction Variables..- 4.0 Introduction.- 4.1 Sample Design and Data.- 4.1.1 On the Sample Design.- 4.1.2 Sample Data.- 4.2 The Prediction Equations.- 4.2.0 Introduction.- 4.2.1 The Prediction Equation for the latest Year before Failure.- 4.2.2 The Prediction Equations for earlier Years before Failure.- 5. A Failure Prediction Model With The Developments of Ratios over Time as Prediction Variables..- 5.0 Introduction.- 5.1 The Variables of the Model.- 6. The Fitted Failure Prediction Model With The Developments of Ratios over Time as Prediction Variables..- 6.0 Introduction.- 6.1 Sample Data.- 6.2 The Prediction Equations.- 6.2.0 Introduction.- 6.2.1 The Prediction Equation for the latest Year before Failure.- 6.2.2 The Prediction Equations for earlier Years before Failure.- 6.3 Comparison of the Prediction Quality of the Level-variables Model with the Level-and Trend-variables Model.- 7. Practical use of Failure Prediction Models in Lending Decisions..- 7.0 Introduction.- 7.1 Subjective Expectations.- 7.2 Bayes’Theorem.- 7.3 Lending Decisions.- 8. Value of Information From a Failure Prediction Model..- 8.0 Introduction.- 8.1 Value of Information.- 8.2 The Relationship between the expected Loss of Three Lending Decision Models.- 8.3 Application of Two Discriminant Models in Lending Decisions.- 9. Summary and Conclusions.- APPENDIX 1: Sample Listing.- APPENDIX 2: Prediction Performance of the Model in later Years. ..- APPENDIX 3: Secondary Sample Listing.- REFERENCES.