Family enterprises have been a major part of capital markets. By possessing most of their stock or being a member of the board, family members are considered the main decision makers in family businesses. Earnings on the other hand have always been a performance indicator which is under management control, most often managed or manipulated.This research seeks to identify and compare earnings management between family and non-family structured firms. After definingcriteria regarding family and non-family firms, 31 samples were selected as family based and they were grouped in relevant industries according to Tehran Stock Exchange categorization. Afterwards we randomly selected non-family firms from those industries with the same proportion. To test the research hypothesis, Jones adjusted model (Dechow et al, 1995) and multivariable regression model were used. The results indicate a meaningful relation between earnings management and ownership structure of firms where in average, non-family firms engagein earnings management more often than family ones.

Valuing intangible assets is a critical issue in modern economics; one of the most important ones is trademarks. In a competitive business environment trademarks can protect and create an advantage for firms. In today's complex and ever faster growing market, a suitable trademark affects firm performance and it is considered as a fundamental economic asset for organizations. Valuing intangible assets and determining its relation with performance indicators has two main benefits, first it can be useful for various stakeholders such as stockholders, creditors and employees in assessing firm performance and secondly it can draw standard setter's attention to importance of recognizing and measuring trademarks and other intangible assets in financial statements. The first step in conducting such research is to identify developed and acquired trademarks of listed companies in Tehran Stock Exchange and computing their related value by financial oriented models, then the relationship between trademarks value and accounting performance indicators including net profit (earnings), Return on assets (ROA), Return on Equity (ROE) and Return on sales (ROS) is examined. The results extracted from 2001 to 2011 indicate a significant and direct relationship between mentioned performance indicators and trademarks value.

Development of financial markets and consequences of economic crises at international level caused effects on job environment and the companies' future financial situation is a vital factor for different beneficiary groups, bankruptcy prediction can be used a mean to help them. Prediction methods are constantly evolving, and artificial neural networks have nowadays found a special position among these methods. Since learning constitutes a significant part of neural network models, learning methods of training these models are of particular importance. Therefore, finding a proper training method to reach the desired goals is necessary. Thus, this study seeks to find a better method of building and training artificial neural networks which leads to more accurate predictions of bankruptcy. Meanwhile, three neural networks of radial basis function type were built and trained separately by Altman model (1983( ), Zmijewski model (1984 and combinatory models' variables. After evaluating the ability of these three models of bankruptcy prediction, their accuracy has been compared. Time span of 2004 to 2012 (eight years) has been used to select samples from the listed companies in Tehran Stock Exchange. Results show that all three models have the ability of predicting bankruptcy and the model trained with Altman Model's variables is more accurate than the other two models in this regard.