Financial distress can be the reflection of corporation's management condition. Consequently the distress score of corporations should be considered as a new predictor variable in predicting the financial distress.The analysis of ROC curve, among the models employed to compare the effectiveness of different statistical models, is often used in the fields of psychology and bio-physics in order to summarize the discriminatory of a diagnostic test and also to compare the performance of different models for binary outcomes. Therefore, concerning the topic of this research and the use of ROC curves in predicting the financial distress of corporations, we use logit models to study the financial distress of the manufacturing corporations in Tehran Stock Exchange. We also compare the accuracy of the prediction method with financial distress score variable to the method without this variable.Concerning the accuracy of prediction and classification, the results of this research show that the accuracy of prediction can be enhanced by using the distressed score, gained from DEA, as a new predictor variable in predicting the financial distress.
In this paper, the performance of RiskMetrics model for prediction of 1-day and 10-days value at risk were preceded in three confidence levels of 95%, 97.5% and 99%.The main data are TEDPIX Index that their fluctuations can be indicated market risk of Tehran Stock Exchange. Time series of this index has been applied from 21 March 2001 to 20 March 2010 with the total 2172 observations. As well, for validation of models, Kupiec test and Christoffersen test have been applied. The finding of this paper is that Risk Metrics model are good alternatives in modeling volatility and in estimating VaR. Also the results indicate that in Kupiec test for both periods, the accepting models number are equal, but in Christoffersen test, the results indicate that upon increasing the time period, the accepting models number are decreased.
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