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Linear goal programming as an alternative to multivariate discriminant analysis: a note

Yash P. Gupta, +2 more
- 01 Sep 1990 - 
- Vol. 17, Iss: 4, pp 593-598
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This article is published in Journal of Business Finance & Accounting.The article was published on 1990-09-01. It has received 54 citations till now. The article focuses on the topics: Multiple discriminant analysis & Optimal discriminant analysis.

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Citations
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Multicriteria classification and sorting methods: A literature review

TL;DR: The objective of this paper is to review the research conducted on the framework of the multicriteria decision aiding (MCDA).
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A survey of business failures with an emphasis on prediction methods and industrial applications

TL;DR: This paper provides a review of the literature and a framework for the presentation of prediction models, and relationships and research trends in the prediction of business failure are discussed.
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Business failure prediction using rough sets

TL;DR: The rough set approach is used to provide a set of rules able to discriminate between healthy and failing firms in order to predict business failure and the results are very encouraging, compared with those of discriminant and logit analyses.
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Multi‐criteria decision aid in financial decision making: methodologies and literature review

TL;DR: In this paper, the authors provide an in-depth presentation of the contributions of Multi-Criteria Decision Aid (MCDA) in the field of finance, focusing on the methods used and their real-world applications.
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Riskcalc tm for private companies: moody's default model

TL;DR: Moody's version of its RiskCalc TM default model for private firms as mentioned in this paper analyzes financial statement data to produce default probability predictions for corporate obligors - particularly those in the middle market.
References
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Journal ArticleDOI

Financial ratios, discriminant analysis and the prediction of corporate bankruptcy

TL;DR: In this paper, a set of financial and economic ratios are investigated in a bankruptcy prediction context wherein a multiple discriminant statistical methodology is employed, and the data used in the study are limited to manufacturing corporations, where an initial sample of sixty-six firms is utilized to establish a function which best discriminates between companies in two mutually exclusive groups: bankrupt and nonbankrupt firms.
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Pitfalls in the application of discriminant analysis in business, finance, and economics

TL;DR: The purpose of this paper is to discuss problems of application of discriminant analysis techniques and the prospects for statistical research on the application of the techniques.
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Simple but powerful goal programming models for discriminant problems

TL;DR: In this paper, the authors suggest alternative assignment procedures, utilizing a set of interrelated goal programming formulations, and demonstrate the potential of these procedures to play a significant part in addressing the discriminant problem, and indicate fundamental ideas that lay the foundation for other sophisticated approaches.
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An experimental comparison of statistical and linear programming approaches to the discriminant problem

TL;DR: In this paper, the results of an experimental comparison of three linear programming approaches and the Fisher procedure for the discriminant problem were reported, and sample-based rules were suggested for selecting an approach based on Hotelling's T2 and Box's M statistics.
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Applications and Implementation

TL;DR: This work proposes an alternative solution to the discriminant problem that requires little more than a minimum familiarity with linear programming and shows promise for eliminating the complexities of conventional statistical approaches without sacrificing the essential power of existing methods.
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