Accounting report
ehsan mohebi; jafar babajani; Mohammad Javad Salimi; mohammad taghi taghavi fard
Abstract
Regional Electric companies are organizations that pursue both social and financial goals in order to fulfill the assigned missions, so fulfilling the accountability due to their dual goals is of fundamental importance. In this research, by examining the information needs of the users of the financial ...
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Regional Electric companies are organizations that pursue both social and financial goals in order to fulfill the assigned missions, so fulfilling the accountability due to their dual goals is of fundamental importance. In this research, by examining the information needs of the users of the financial reports, the effective factors in the financial reporting of the sector have been studied. The aim of this research is to present a model for the environmental conditions and characteristics of regional electric companies in Iran. For this purpose, the required data after library study and exploratory search in the theoretical foundations and financial and accounting rules and regulations governing the relations of these persons and using a questionnaire, collected and analyzed using the fuzzy Delphi research method and appropriate statistical tests. The evidence from the analysis of the views of the respondents shows that the influencing factors are in four dimensions, including the compatibility of the model in providing the achievement of the organization's goals, the needs of information users, compatibility with financial and accounting laws and regulations, and finally, budget control and credit status reporting. Experts also agree on the factors proposed by this research to design and explain the financial reporting model of regional power companies in Iran
Ali Saghafi; Roohollah Farhadi; Mohammad Taghi Taghavi Fard
Volume 12, Issue 45 , April 2015, , Pages 9-38
Abstract
According to Prospect Theory, Investors have different behaviors in theprofit and loss situations and indeed their trading behavior is different in bulland bear markets. This study uses quantile regression model (in differentquartiles) and OLS model to estimate beta of 180 firms. Results showed thatfirst, ...
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According to Prospect Theory, Investors have different behaviors in theprofit and loss situations and indeed their trading behavior is different in bulland bear markets. This study uses quantile regression model (in differentquartiles) and OLS model to estimate beta of 180 firms. Results showed thatfirst, equity total risk (standard deviation) increase in Upper quartile andsecond, stocks beta changes in different quartiles and by moving fromquartile 0.25 to quartile 0.75, systematic risk (beta) increases significantly.Linear regression model and Quantile regression model show also thatunexpected variance can explain excess return at least similar to expectedvariance. The results can also be interpreted with both Insight of standardfinance and insight of behavioral finance. In standard finance area, riskreturnpositive relation that exists in upper quintiles is consistent with longrun growth of economy. Moreover, negative relation between return and riskin lower quintiles imply more uncertainty and as a result causing stockreturns to fall. In behavioral finance area, regime-dependent behavior ofslope coefficients is consistent with prediction of Prospect theory ofinvestor’s behaviors around the reference point.
roohollah farhadi
Abstract
According to Prospect Theory, Investors have different behaviors in the profit and loss situations and indeed their trading behavior is different in bull and bear markets. This study uses quantile regression model (in different quartiles) and OLS model to estimate beta of 180 firms. Results showed that ...
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According to Prospect Theory, Investors have different behaviors in the profit and loss situations and indeed their trading behavior is different in bull and bear markets. This study uses quantile regression model (in different quartiles) and OLS model to estimate beta of 180 firms. Results showed that first, equity total risk (standard deviation) increase in Upper quartile and second, stocks beta changes in different quartiles and by moving from quartile 0.25 to quartile0.75, systematic risk (beta) increases significantly. Linear regression model and Quantile regression model show also that unexpected variance can explain excess return at least similar to expected variance. The results can also be interpreted with both Insight of standard finance and insight of behavioral finance. In standard finance area, risk-return positive relation that exists in upper quintiles is consistent with long run growth of economy. Moreover, negative relation between return and risk in lower quintiles imply more uncertainty and as a result causing stock returns to fall. In behavioral finance area, regime-dependent behavior of slope coefficients is consistent with prediction of Prospect theory of investor’s behaviors around the reference point.
Farokh Barzideh; Mohamad taghi Taghvifard; Fatemeh Zamanian
Volume 10, Issue 39 , October 2013, , Pages 105-124
Abstract
This article is seeking to provide a proper model for selecting portfolio. To do that, first we should studied literature to discover suitable criteria. Then we have used a questionnaire for determining criteria's relationships to rank them. Managers of mutual fund asked to answer this questionnaire. ...
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This article is seeking to provide a proper model for selecting portfolio. To do that, first we should studied literature to discover suitable criteria. Then we have used a questionnaire for determining criteria's relationships to rank them. Managers of mutual fund asked to answer this questionnaire. To determine these relationships, we used DEMATEL technique. After that, these criteria were ranked by using Analytic Network Process. Thus, 50 companies with more cash in market between1385-1389 were chosen to assess these criteria. These companies were ranked by TOPSIS and a portfolio selected with the top 30. Return of portfolio consist of 30 companies had compared with the average return of portfolio consist of 50 stock and was shown by Sharp Index that the proposed model can be useful for managers in their portfolio selection.
