نشریه چشم انداز مدیریت مالی
پیاپی 21 (بهار 1397)

The first public stock released by a company is defined as initial public offering. In recent years, there have been many research on IPO short-term performance. The present research aims to test different classification models to find model having great efficiency in Prediction of initial public offering short-term performance. The study included 60 IPO in Tehran Stock Exchange during the period 2005-2015. In the proposed framework, average surplus return for first three days of IPO has a positive value and equals to 1.3% although this value is not high same as developed markets. 10-fold cross-validation method was used for evaluating and monitoring nearest neighbor, support vector machines, decision trees and naive-Bayes and results showed that among monitoring nearest neighbor and support vector machines models has high accuracy in predicting IPO short-term performance.

Financial flexibility is one of the key factors in making decisions about the Company's financial policeis. In this paper, proposed a novel approach to measure the value a firm's shareholders attribute to its financial flexibility. And examined the relationship between financial flexibility and financial policies, including dividends, capital structure and cash holdings as well as the cost of equity capital. The sample of this study consists of 84 companies listed in Tehran Stock Exchange for the period 2007 to 2014 (1386 to 1393 Iranian calendar). In this study, the model developed by Gamba and Triantis ]12[ has been used as financial flexibility criteria. Financial flexibility is calculated using four factors: Growth opportunities, profitability, cost of external financing and Reversibility of capital. To test the hypothesizes, multivariable regression model to panel data and logit model was used. The result of this study shows, there is negative and meaningful relationship Between financial flexibility and Debt leverage and cost of equity capital, In addition to cash holdings is a significant and positive impact. It also has no significant impact between financial flexibility and decisions of division.

Myopia is a form of bias or tendency that creates a serious and important limitation for considering options and recommendations on the selection and decision-making. Myopia, in fact, means the overestimation of short-term benefits and underestimation of long-term benefits by active investors in the market. In markets free from the efficiency features, investors and decision makers determine the value of firms according to what occurred in the past and might happen in near future and do not consider the potential abilities of the firm in a more distant future. Considering the importance of myopia, this article aimed to study the effect of managerial myopia on future stock returns of companies listed on TSE. In this article, companies with managerial myopia were selected where marketing and R&D expenses declined by the positive financial performance and ROA increase. In general, using a sample which consisted of companies listed on TSE from 2006 to 2014 we observed decreasing future annual returns of stocks. In other words, it had no effect on the relationship between the abnormal returns and managerial myopia. In case of managerial myopia, the result was not statistically significant, however.

The main purpose of this research is to study the impact of corporate diversification on firm’s excess value by including opportunities among firms listed in Tehran Stock Exchange. Excess value as an independend variable was measured by the natural logaritm of firm’s actual value (sum of market stock value and debt book value) to its imputed value. Diversified firms imputed value was calculate the imputed value of each segment by multiplying the median ratio, for single-segment firms in the same industry, of total capital to sales by the segment’s level of the accounting item. To measure independent variable (diversification), We use three indexes including Entropy, Herfindal and number of sections. Growth opportunities was measured by Q Tobin’s ratio. The initial sample of this research includes 191 firms listed by Tehran Stock Exchange (55 diversified firms and 136 single-business firms) for the period of 2013 to 2017. Regression results showed that diversification has a significant impact on excess value. All three diversification indexes including Entropy, Herfindal and number sections have positive impact on excess value. Also, the research results indicate the moderating role of growth opportunities variable on the relationship between diversification and excess value.

In the same way that healthy and efficient banks can be effective in economic growth, their unhealthy and poor performance can also lead to financial and economic crises. The WFTC has been reviewing and proposing capital requirements since 1988 and, most importantly, observing the minimum capital adequacy of banks. Calculation of capital adequacy requires consideration of capital and risk weighted assets. Due to the significant difference between the methods of financing and the use of funds and the type of contracts and payloads in the Islamic bank with the conventional bank, it is necessary to calculate and determine the minimum capital adequacy for an Islamic bank after identifying and classifying various types of assets, liabilities and capital And the amount of risk associated with each of them, taking into account its specific financial features. Therefore, this research intends to assess the suitability of a set of the most important indicators of banking healthy indicators, namely, capital ratios. To this end, the ratio of capital ratios (tire1똪) to risk weighted assets with technical efficiency of Islamic banks of Iran is reviewed. After calculating the technical efficiency index of banks by CCR and BCC, eight panel data regression models for the period 2003-2015 were estimated for 21 banks and more than 190 statistical samples. The results show that all four capital indicators have a positive and significant effect on the technical efficiency of the banks. However, tire1 capital to total assets ratio is the best explanatory variable among capital ratios for banking performance.

The most important activity of banks throughout the world is the attraction of deposits and credit. The topic of bank credit in Iran, whose banking system is based on its own, is very important. In the present study, we seek to explain the effective factor affecting Iranian bank credit. The research methodology used in this study includes reviewing systematic literature to identify the factors affecting bank accreditation as well as classical and Delphi fuzzy qualitative methods for localizing factors and then finalizing the model of bank credit model. Also, the statistical society used in this research is academic and executive experts in the field of banking credits in Iran. The results of this study show that factors related to macroeconomic conditions as well as factors related to political and social conditions have the most impact on banking credits in Iran. The factors related to laws and regulations in Iran have the least effect on credit system.

Predicting stock return rate is always one of important issues of financial markets and also major factor in investment. Predicting excess stock return based on debt-based data, other economic variables and capital market in Iran is the main purpose of this research. The proposed model emphasizes on nonlinear relationship between a set of quantitative variables and its structure basis is parametric and nonparametric models by using local kernel smoothing. First of all effective variables of debt return rate was investigated and identified. After identifying effective variables in first stage, prediction model for debt security return rate has been structured. This prediction is designed and presented by two methods of parametric and nonparametric prediction for debt security. In the following in order to determining effective factors of excess stock return rate prediction model structuring is investigated in the form of linear parametric and nonlinear nonparametric, by using results of first stage in three different steps and by observing R_v^2 criteria. The result of model implementation in all three examined steps and based on R_v^2 criteria show that results of various models of nonparametric approaches work much better than parametric approaches.