There are many factors in the transparency of financial information, the most important and most effective of which are financial components. In this research, we merely consider financial insurance agents in transparency of financial information because of, insurance a More
There are many factors in the transparency of financial information, the most important and most effective of which are financial components. In this research, we merely consider financial insurance agents in transparency of financial information because of, insurance accounting specific nature.The purpose of this study was to investigate the effective relationship between financial insurance factors and financial information transparency of the insurance industry.To determine the final financial components of insurance, experts of the insurance industry were consulted and a researcher-made questionnaire was used to collect data.The research sample consisted of 151 managers and experts in the insurance industry selected by random sampling method. The realm of this research is 2017 and city of Tehran. One-sample t-test was used to analyze the data in a small phase.The results indicate that financial insurance factors have a meaningful relationship with the transparency of financial information in the insurance industry, but violations were also found in the research components.The results of the ranking showed that the disclosure of leverage ratios and deferred loss accounts has the highest degree of significance.
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The purpose of this study is to examine the impact of Earning Smoothing and Financial Information Transparency on Stock Price Crash Risk. In order to measure the financial information transparency, stock price crash risk and earning smoothing, respectively Donelson et a More
The purpose of this study is to examine the impact of Earning Smoothing and Financial Information Transparency on Stock Price Crash Risk. In order to measure the financial information transparency, stock price crash risk and earning smoothing, respectively Donelson et al. research (2010) and Len et al. (2012), Houghton et al. research (2014) and the model of Chen et al. (2012) and Tucker and Zarowin (2006) through evaluating the correlation between changes in accruals (unusual) and changes in pre-managed profits have been used. A total of 196 companies listed in the Tehran Securities Exchange have been selected during the period of six years from 2013 to 2018 according to the society's screening conditions. In addition 1176 company-year observations have been included in the statistical analyzes. The results of the research show that Earning Smoothing has a significant positive effect on the crash risk and Financial Information Transparency has a significant negative effect on the crash risk. Indeed, managers who are willing to smooth the reported earnings and create a more stable flow to support a higher level of profits, are more exposed to the stock price crash risk. Company size, financial leverage and institutional shareholders have a significant negative effect on the stock price crash risk, and the company age has a significant positive effect on the stock price crash risk. But the market value to book value ratio and Sale Standard Deviation do not have a significant effect on the stock price crash risk.
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One of the most important factors in transparency of financial information is financial components. The present research is applied in terms of its purpose and in terms of its implementation method is descriptive and aims to provide a functional model for transparency o More
One of the most important factors in transparency of financial information is financial components. The present research is applied in terms of its purpose and in terms of its implementation method is descriptive and aims to provide a functional model for transparency of financial information in the insurance industry and to describe the components and dimensions of the final model. To do this research, firstly, by reviewing the literature, preparing the matrix of components and integrating the components of the components matrix together with the selection of the components of the element, were examined and interviewed by the experts and experts of the insurance industry and university professors, the final components of determining and classifying the factors of focus Regulations 88 of the Supreme Council of Insurance in four levels were adopted. The statistical population of this study was financial experts of the insurance industry, which totally estimated 1200 people. In this research, Kolmogorov Smirnov tests were used to determine the distribution of data, BMI and Bartlett's tests for the suitability of the sample and the partial least squares method For modeling, finally, using partial least squares method and SmartPlS software, a final model of research was developed. Using the model of this research, the level of transparency of financial information of each insurance company can be measured and ranked quantitatively
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Ranking companies based on transparency of financial information can help better decision making in the stock market. In this study, by examining the financial statements of companies and measuring the transparency of financial information, their ranking is based on neu More
Ranking companies based on transparency of financial information can help better decision making in the stock market. In this study, by examining the financial statements of companies and measuring the transparency of financial information, their ranking is based on neural and fuzzy models. Another purpose of the present study is to compare neural and fuzzy models for ranking the transparency of corporate financial information.This is an applied research based on descriptive-analytical method. The statistical population includes the stock exchange companies during the years 2008-2009 and 198 companies were selected and analyzed by systematic elimination method. Company information was obtained through stock exchange software. Artificial intelligence algorithms were used for ranking and fuzzy and neural models were used.The results showed that among the fuzzy and neural models, the best method for ranking is the neural models and the results of the neural models method give the best results. Given that in fuzzy model, fuzzy method has the most errors and in some estimations it has unacceptable errors.
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