Volume 15, Issue 3 (11-2018)                   jor 2018, 15(3): 67-85 | Back to browse issues page

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Ramazaniyan M, Yakideh K, Safdari Sorkhzoo Z. Providing Tobin’s q Discriminant Function using DEA-DA and Logistic Regression . jor. 2018; 15 (3) :67-85
URL: http://jamlu.liau.ac.ir/article-1-1245-en.html
University of Guilan, Department of Management, Rasht, Iran
Abstract:   (2027 Views)
The discriminant analysis tries to find an equation based on a current order in the data that can be commented about the membership of a unit in one of the two or more groups according to the number of the independent variables. DEA-DA and logistic regression are among the discriminant analysis techniques which have no complex statistical assumptions and are applicable in many studies. On the other hand, Tobin's q index is one of the widely used financial indicators used as a benchmark to evaluate performance. But also there are some ambiguities in the accuracy of the calculation of this index that many researchers have tried to resolve the ambiguity of the index and improve performance. The current research has also sought to provide appropriate discriminant function of Tobin index for the accepted   companies by Tehran Stock Exchange based on associated financial ratios widely used by such an index. Therefore, after finding indices related to Tobin's q, the data of 181 companies listed in Tehran Stock Exchange  in the financial year leading to 29 of Esfand in 1393, DEA-DA and logistic regression were run in parallel and compared  with obtained results  and a number of indices were removed which in both methods from the mathematical and statistical point of view had instable conditions, once again two methods were implemented with 5 independent variables that better and more stable outputs were observed in both of the methods. The results have been reported and analyzed.
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Type of Study: Research | Subject: Special
Received: 2016/10/3 | Accepted: 2017/06/10 | Published: 2018/11/15

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