فهرست مطالب محسن خوش طینت

This research aims to identify the influential components on LGD by using Tobit regression on institutional customers of the bank of Industry and Mine. In order to achieve this goal, LGD can be used to calculate the probability of default on the basis of the Basel II agreement. LGD is the amount of loss a bank faces when the borrowers default on loan repayment. To accomplish this goal, 204 of institutional customers of bank for an 8 years period (2007-2014) have been chosen as a sample. The results show a significant relation between loan amount, collaterals (excepted promissory notes), industry type and LGD, and no significant relation between loan maturities and LGD.

Today, banks are looking for performance improvement methods to surpass their competitors to increase market share and profitability. Since one of the most important issues and concerns for the banks are profits and returns, they use a variety of methods to attract more customers. Base on this reason, performance evaluation of banks is very crucial and important not only for their investors and depositors, also for their managers. This study examines the factors affecting the profitability of Iranian private banks in the period of 2006 to 2014 and focuses on the financial factors to increase the efficiency by the bank managers.
The study is a correlational research and was conducted using analysis of historical data. In this study, according to 3 independent variables (size of the bank, operating efficiency, asset management), 6 hypotheses were formulated. The results show that there exists a significant relationship between the independent variables and profitability criteria (net interest income and return on assets of the banks). To test the research hypotheses, multivariate linear regression and panel data analysis were utilized.

Insolvency risk of banks accounted for a large part of the banking literature, especially after the global financial crisis and the subsequent widespread bankruptcies of the banks is of great importance. Most banks and credit institutions face with financial insolvency due to the lack of portfolio diversification of financing structure, lending large amount of loans to a particular industry or economic sector, and the lack of management and control of risks before they come into existence. Since the failure of the financial sector especially banks undermine public confidence in the financial system and as a result devastating effects is transferred on the entire economy, studying factors influencing the risk of insolvency is very important. Hence, the present study uses panel data model (unbalanced panel) and Generalized Least Squares (GLS) to test the effectiveness of the financing structure, credit risks, interest rate risk on insolvency risks of banks. Research data include financial information of 10 commercial public banks, private, and privatized banks under Article 44 during the priod of 2001 to 2012. The results show that specialization financing structure variable has a significant and direct effect on the risk of bank insolvency, while financing structure stability variable over the medium term (mid-term policy of banks lendings) has reverse and significant effect on the risk of bank insolvency. Also, the effect of interest rate risk, credit risk and liquidity risk on bank insolvency risk is significant and positive.

Many finance researchers know disability of classical models of assets pricing and efficient market hypothesis to explain predictable patterns in securities return, anomalies and mispricing in assumption of full rationality of economic agents. Based on this assumption, the probability that people will mistake is random and its effects quickly remove by other rational investors. By relaxing this assumption, some models developed based on specific trading strategies and others based on cognitive biases and psychological characteristics of investors.One of the most common cognitive biases in the field of psychology is overconfidence that has been defined as overestimation (optimistic) of precise of private information. Many researchers explain stylized facts such short-term continuation (momentum) and a long-term reversal in stock returns, high levels of trading volume, excessive volatility, and a disproportionate amount of risk borne by investors by using overconfidence bias. In this study, which tried to plan and test four hypotheses based on the data of 119 companies during the period from the beginning of the 1378 to end of 1386 (for 9 years) in regard to evidence documentation for aggregate overconfidence behavior. Results of study show that evidence for supporting aggregate overconfidence is not strong.

This paper studies the relationship between information asymmetry and accounting conservatism in financial statements. Information asymmetry between informed and uninformed equity investors creates an agency cost that increases the equilibrium return on the firm's equity. This effect gives parties to the firm an incentive to generate a mechanism that reduces information asymmetry. In the other hands Conservatism reduces the manager's incentives and ability to manipulate accounting numbers and then reduces the agency costs. Our empirical tests express that information asymmetry among equity investors is significantly positively related to conservatism. Further our tests confirm that changes in information asymmetry between equity investors lead changes in conservatism but conservatism doesnt lead to information asymmetry. This result rejects the FASB proposition that conservatism produces information asymmetry among investors.

The focus of this paper is on standard Markowitz mean–variance model and its traditional approach to solve portfolio selection problem (Quadratic Planning). For this goal we have applied a meta-heuristic method based on genetic algorithms (GA) in order to trace out the efficient frontier associated with the portfolio selection problem under cardinality and bounding constraints. These constraints ensure the investment in a given number of different assets and limit the amount of capital to be invested in each asset. We have presented some experimental results in two samples from Iranian stock market and overseas ones and compare the GA result with unconstrained quadratic results. Finally, we have found out which proposed GA can optimize portfolio selection problem under cardinality and bounded constrains