درخت حوزه‌های تخصصی

Given the rapid development of the banking sector, it is reasonable to expect that the performance of banks has become the centre of attention among bank managers, stakeholders, policy makers, and regulators. In order to maximizing the share-holders’ satisfactory level, two bank efficiency measurement approaches, i.e. the production approach and the user cost approach, which are financial evaluations, are employed. The evaluations are done by means of data envelopment analysis method. The proposed methodology is run on the 15 privet bank branches in Markazi province. By using this approach, four regions that show the various performances are obtained. In addition the status of returns to scale for each bank branch is calculated.

Stock price crash risk is a phenomenon in which stock prices are subject to severe negative and sudden adjustments. So far, different approaches have been proposed to model and predict  the  stock price crash risk, which in most cases have been the main emphasis on the factors affecting it, and often traditional methods have been used for prediction. On the other hand, using  Meta Heuristic Algorithms, has led to a lot of research in the field of finance and accounting. Accordingly, the purpose of this research is to model the Stock price crash risk of listed companies in Tehran Stock Exchange using firefly algorithm and compare the results with multivariate regression as a traditional method. Of the companies listed on the stock exchange, 101 companies have been selected as samples. Initially, 19 independent variables were introduced into the model as input property of the particle accumulation algorithm, which was considered as a feature selection method. Finally, in each of the different criteria for calculating the risk Stock price crash risk, some optimal variables were selected, then using firefly algorithm and multivariate regression, the stock price crash risk was  predicted  and results were compared. To quantify the Stock price crash risk, three criteria for negative skewness, high fluctuations and maximum sigma have been used. Two methods of MSE and MAE have been used to compare the methods. The results show that the ability of meta-meta-heuristic methods to predict the risk Stock price crash risk is not  generally higher than the traditional method of multivariate regression, And the research hypothesis was not approved.