نشریه چشم انداز مدیریت مالی
پیاپی 42 (تابستان 1402)

Operational risk is one of the most important risks of financial institutions. After the approval of the Basel committee, it has started to be noticed all over the world. The increasing increase in operating losses in various business lines has caused the attention of financial institution managers to be directed to the area of operational risk. In this  research, a method for estimating the appropriate threshold for  operational loss data and also a method for classifying operational loss data is presented, and the capital required to cover operational risk by combining the intensity distribution function and frequency of operating loss data and Monte Carlo simulation are obtained. Also, the dependence between matrix cells of business lines and loss making events has also been investigated. For this research, operational loss data related to a banking group including several Asian, European and American banks have been used. The research results indicate that the loss distribution approach with the combination of critical value theory and machine learning algorithms (clustering), as well as the loss distribution approach with the combination of machine learning algorithms (classification), is more efficient than other methods.

The purpose of this study is a model for measuring investment efficiency in companies listed on the Tehran Stock Exchange based on the combination of artificial neural networks and the cumulative particle motion optimization algorithm. For this purpose, samples consisting of 124 companies listed on the Tehran Stock Exchange during the years 2008-2019 have been studied. In order to achieve the goals of the research, first by studying the previous researches in the field of investment efficiency, 17 variables affecting investment efficiency were selected and using the combined data method, the optimal model of investment efficiency was estimated based on the cash flow resulting from investment activities. The results of the model estimation showed that 8 variables of growth opportunity, quality of financial reporting, sales growth, rate of return on assets, financial leverage, operating cash flows, dividends, operating profit on total assets have a significant relationship with the amount of cash spent on investment activities. Finally, the results of comparing the research model based on the combination of artificial neural networks and particle cumulative motion optimization algorithm with other models showed that the development of the research model reduced the neural network training error with particle cumulative motion algorithm by 0.0560. Also, with the development of the research model, by entering accounting variables, the rock curvature level increases to 0.6164 and as a result, the accuracy of the research model increases to 63.602%.

The developmentof a new system of corporate governance after the collapse of Enron and WorldCom in the early years of the 21st century at the global level and the acceleration of the process of handing over government assets simultaneously with the development of the capital market and the strengthening of institutional investment at the country level, the issue of ownership and its impact has made the performance of companies a controversial topic in the field of financial literacy. The purpose of this research is to investigate the relationship between the ownership structure and the financial performance of companies listed in the Tehran Stock Exchange. Based on this, the research investigated the effect of the relationship between institutional and government ownership on the financial performance of 146 listed companies on the Tehran Stock Exchange from 2012 to 2021 using the dynamic panel(Panel GMM) method. The research results indicate the positive effect of institutional ownership on the performance of sample companies. Also, performance metrics based on accounting information show a significant and negative relationship between government ownership and company performance. Other findings of the research show the positive effect of financial leverage and the positive view of shareholders towards the shares of large and growing companies in evaluating the company's financial performance

Exchange Traded Funds (ETFs) have so many features like low cost, tax efficiency, liquidity and stock like attributes which make it most attractive. Because of this, ETFs are the most popular type of investment destination. Intuitively, because of their ease and low cost of trading, ETFs may be appealing to individual (unsophisticated, uninformed) investors who are more likely to chase trends, raising a concern over the impact of their introduction on the overall market efficiency. The purpose of this article is to examine the strategy of feedback trading and investors’ behavior ETF in the capital market of Iran for the first time. For this purpose, the daily data of seven ETFs 2013/10/07-2023/03/20 and Santana-Wadvani model (1992) have been used. The results showed that despite the existence of a fully overlapping market for underlying asset transactions, these ETFs are traded below their net asset value on most trading days. The results of the estimation of the feedback trading model showed that there is no evidence of the existence of feedback trading in ETFs and traders do not pay attention to their past performance. The market of these ETFs is efficient, which can be attributed to the professional management of these ETFs

The competitive environment makes it difficult for firms to achieve effective performance. To be able to prove themselves, managers try to make performance positive by earning management. Based on this, the aim of the current research is to investigate the marginal effect (which includes both simple and Interaction) of competition on performance at different levels of earning management. In this research, variables of performance (asset return rate, sales return rate and equity return rate), product market competition and profit management have been used as indicators research. A statistical sample of 94 companies listed on the Tehran Stock Exchange between 2013 and 2019 was used for this research. Regression with panel data was used to test research hypotheses. The findings of the research show that competition has a significant effect on the three performance measurement indicators and the impact varies depending on the level of earning management. In such a way that with the increase in earning management, the level of competition has an increasing effect on performance, and with its decrease, this effect decreases. The results showed that the degree of competition has a rising impact on performance as earning management increases and a decreasing impact as earning management decreases. Also, the higher the earning management of the business unit, the higher the competition, which will lead to better performance.

Increasing the debt capacity leads to improving the company's financial flexibility. Financial flexibility plays an important role in the financial empowerment of the company regarding investment in the future, which is important to maintain flexibility according to the existing risks, which is possible with risk management. The current research aims to track the effect of business risk management and life cycle on the debt capacity of the companies listed in the Tehran Stock Exchange. In this regard, a sample of 124 companies from the Tehran Stock Exchange along a period of 2012-2021 were selected as sample and the research hypotheses were tested with aide of multiple linear regressions based on pooled data. The results showed that business risk management has a positive effect on the debt capacity of companies, and this business risk management effect during the recession stages of the life cycle of companies is more dominant. As expected, in the conditions of better use of business risk management mechanisms, the debt capacity of companies has also improved significantly. With better applying of risk management mechanisms, the reliability of loans and creditors to the company is increased too and as a result, the company's debt capacity is also improved.