Abstract
Data Envelopment Analysis (DEA) is employed as a tool to evaluate the efficiency score of Tehran Stock Exchange. For predicting financial distress, it is designed and tested a model base on efficiency score. Its accuracy was verified by employing another model designed by financial ratios and variables based on Multivariate Discriminant Analysis (MDA). Ultimately, to investigate the effectiveness of firm's efficiency score on financial distress prediction, its score combined with financial ratios is entered in an MDA model. The results show that all the three proposed models, in this paper, have better ability of predicting financial distress in Tehran Stock Exchange for two years prior to its occurrence. It implies that, DEA efficiency score is an effective predictor variable.
Highlights
Due to the effect of corporation’s financial distress as well as bankruptcy on different interested groups, the present index of financial distress and bankruptcy warning has been one of the most attractive subjects in different countries
Until now researchers have been using financial ratios in different models based on Multivariate discriminant analysis (MDA) (Altman, 1968; Deakin, 1977; Springate, 1978, Zmijewski, 1984; Altman, 1993; Rujoub et al, 1995; Shirata, 1998; Grice & Ingram 2001), Logistic and Probit analysis (Ohlson, 1980; Rose & Giroux, 1984; Zavgren, 1985; Lau, 1987; Aziz et al, 1988; Gilbert et al, 1990; Platt & Platt, 1990; 1991, Lennox, 1999), Recursive Partitioning Algorithm (RPA) (Frydman et al, 1985; Sung et al, 1999; Mckee & Greenstein, 2000; Beynon & Peel, 2001)
Because of specialties of this method and suitable for test of statistic hypothesis that is related with classification, till MDA has been interested by researchers for prediction of financial distress and bankruptcy (Christopoulos et al, 2008; Alexakis, 2008), Miller (2009)
Summary
Due to the effect of corporation’s financial distress as well as bankruptcy on different interested groups, the present index of financial distress and bankruptcy warning has been one of the most attractive subjects in different countries. Until now researchers have been using financial ratios in different models based on Multivariate discriminant analysis (MDA) (Altman, 1968; Deakin, 1977; Springate, 1978, Zmijewski, 1984; Altman, 1993; Rujoub et al, 1995; Shirata, 1998; Grice & Ingram 2001), Logistic and Probit analysis (Ohlson, 1980; Rose & Giroux, 1984; Zavgren, 1985; Lau, 1987; Aziz et al, 1988; Gilbert et al, 1990; Platt & Platt, 1990; 1991, Lennox, 1999), Recursive Partitioning Algorithm (RPA) (Frydman et al, 1985; Sung et al, 1999; Mckee & Greenstein, 2000; Beynon & Peel, 2001) Of these methods, MDA is the oldest and the most popular in design of bankruptcy models that at the first is employed by Altman (1968). The result of this glance is presented of prediction models base on Rough Sets, Fuzzy logic, Artificial Neural Networks and DEA
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