فصلنامه بورس اوراق بهادار
پیاپی 62 (تابستان 1402)

The present study aimed to investigate the effect of liquidity risk on the SEO timing.. This study tries to evaluate the effect of liquidity risk on the timing of the seasoned equity offering based on Tehran Stock Exchange data during the period 2012-2018 and the use of the data panel’s regression models. In order to achieve the research goals of 71 firms listed in the Tehran Stock Exchange, which had Capital increase, they were analyzed as prototype before and after season equity offering.the results of the research show that there is a negative and significant relationship between liquidity risk and the SEO timing. Also, by examining the periods before and after the seasoned equity offering, it was found that the liquidity risk index was three years ago, one year ago and in the second year of supply, there is a significant relationship with stock pricing Therefore, the hypothesis Timing is confirmed, but the liquidity risk index has not changed significantly after the seasoned equity offering.

Analyzing the behavior of investors as a new scientific field in behavioral finance is a good tool for acquiring knowledge. The purpose of this study is to investigate the effect of investors' behavioral biases in explaining the added value created based on the volume of transactions in mutual funds listed on the Tehran Stock Exchange and its time domain was from 1392 to 1396. In order to analyze the data, variance heterogeneity tests, F-Limer, Hausman and Jarkbra tests were used and then multivariate regression was used to test the research hypotheses in Ives software. The results indicate that the factors of investors' behavioral biases include optimism, pessimism and positive and negative investor tendencies; Investor transaction value; Investors 'net turnover and investors' share of the trading volume of investors influence the explanation of value added created based on the volume of transactions in mutual funds. Also, these results are consistent with financial behavioral theories in general and emotional and cognitive bias theories in particular.

The determinants of banks' profitability and performance in the literature have been investigated in this study in a large and detailed way. However, there is little study about the banking sector and in emerging markets. In this paper, an analysis was conducted to determine the internal factors affecting the performance of banks in Iran using the spatial data during 2011-2016. In this research, the relationship between bank performance and financial firmness in eleven banks accepted in Iran's stock exchange and farabourse has been investigated using panel data regression. In the case of the deferred loan ratio variable, it can be seen that this variable has a negative relationship with the rate of return of the shareholders. Also, the bank's liquidity level and interest margin to gross income also have a negative relationship. As a result, in order to increase profitability, banks must take care of the quality of the loans they grant.

The capital market is growing rapidly. This has led to higher demand for information, more effort to predict and invent new models for predicting the future of the market. Predictive models can be classified into three categories. The first group uses technical analysis, the second group uses fundamental analysis, and the third group uses data mining and machine learning. In the present study focusing on data mining method to compare the accuracy of selected machine learning models including neural network, logistic regression, k nearest neighborhod, support vector machine and cross validation to predict stock prices for 12 selected companies of Tehran Stock Exchange that They have been selected through systematic deletion method in the form of machine learning models and the results of this paper showed that among the machine learning algorithms, the support vector machine algorithm has the highest predictive power in stock prices.Keywords: stock exchange, forecast; Stock prices, algorithms, machine learningJEL Classification Code: C8, G1

The return of assets and various investment opportunities are two of the most basic principles of optimal allocation of resources in the economy. Liquidity is one of the most important factors affecting the risk and expected return of assets, and liquidity risks arise from it. The main purpose of this study is to determine the effect of different liquidity risks on the stock returns using the LCAPM model with the most optimal illiquidity measure. To test the hypotheses of research, a sample of 167 companies listed on the Tehran Stock Exchange during the years 1389 to 1398 has been selected. In order to select the optimal illiquidity measure from among six different measures, Principal Component Analysis approach is used and PSpread measure has been chosen. For estimating the model, the Generalized Method of Moments method has been used. The results of this study show that investors price liquidity risks in bearish markets in addition to the illiquidity effect, however, they do not pay much attention to these risks in the bullish markets.

abstractAccording to Merton (1987), idiosyncratic volatility pricing is mainly concerned with unknown stocks which have limited investor base. However, there is no trace of recognition effect study in experimental research of IVOL puzzle. Thus, ignoring the recognition effect could be one of the effective components in the puzzling behavior of idiosyncratic volatility. Therefore, in the present study, we try to explain the effect of recognition on idiosyncratic risk pricing. In this regard, first, the effect of recognition on the relationship between idiosyncratic risk and stock returns has been tested based on double sort portfolio study and Fama-Macbeth regression. Then, the proposed approach of Hou and Loh (2016) is applied to evaluate the amount of recognition effect on the relationship between idiosyncratic risk and stock returns in the Tehran stock exchange during (1384-1398). Results indicate a positive relationship between idiosyncratic risk and return. Moreover, show that recognition can explain up to 70% of the relationship between idiosyncratic risk and return.Keywords: unsystematic volatility, idiosyncratic risk, cognition effect, asset pricing

Liquidity is a concept that is not clearly defined and so far more than 90 different criteria have been used for liquidity around the world. The present study aims to provide a local model for daily stock liquidity based on factors affecting liquidity. The values of 7 non-systematic factors that could be evaluated daily were extracted based on the data of 151 active companies in the period of 2009 to 2021 and divided into two clusters. Using structural equations with partial least squares approach, the validity of the identified variables was evaluated by the extraction criterion and their ability to explain its changes was calculated. Evaluation of the relationship between variables in machine learning models showed that final price, daily transaction value, daily returns, variance of daily returns and firm size have the greatest impact on clustering. Finally, the best model of machine learning was selected based on training and tests. The results show that the independent variables explain more than 83 per of the liquidity changes. Also, logistic regression model has a higher predictive power compared to other machine learning models and with 99.6 per fit accuracy, it is the most appropriate liquidity prediction model.

The Purpose of this study is to explain a model for assessing the quality of audit reports providing quality ratings for issued reports and finally Conformity of the rank of trusted auditing institutions in the IACPA and the SEO with the obtained rank of the quality of the audit report. The method of the research is descriptive-survey and the implementation method is the Delphi of experts. Finally, a checklist for evaluating the quality of audit reports was prepared. The final checklist consists of thirteen sections; each section is divided into subsidiary indicators. The number of subsidiary indicators determines the quality control score of the reports which is 42 indicators. In order to explain main indicators of the checklist from auditing report standards, the auditor's position regarding compliance with the legal requirements and the tone and frankness of reporting have been used. The research was conducted throughout the year 2020 and the sample used is the audit reports of TSE and OTC Listed companies. The findings show that there is a positive and significant relationship between the quality ratings of the audit report with the ranking of the IACPA. However, there was no significant relationship between the quality rating of the audit report and the ranking of the SEO.

The negative economic consequences resulting from the uncertainty of economic policies have led to the formation of concerns between regulatory bodies, government, and companies. The purpose of this study is to investigate the relationship between economic uncertainty in Iran and the Synchronization of stock returns. To achieve the purpose of the study, the financial information of 135 companies listed on the Tehran Stock Exchange for the period 1390 to 1399 was examined and the hypotheses were tested using a multivariate regression model. in order to measure economic uncertainty (indicators of economic growth rate, exchange rate, inflation rate and interest rate) and the synchronization of stock returns, the Garch model and the market model determination coefficient have been used, respectively. The results of testing the hypotheses show that there is a negative and significant relationship between uncertainty in economic growth rate and interest rate with the Synchronization of stock returns and a positive and significant relationship between uncertainty in exchange rates and Synchronization of stock returns

Valuation of assets, including securities and real assets, is one of the pillars influencing investment decisions. Optimal and principled valuation leads to optimal allocation of capital resources, and optimal allocation of capital in the economy plays an irreplaceable role in economic growth and development. At present, the lack of a clear and concise framework that can explain the exact estimation of value has become doubly important. Therefore, it is important to provide a framework that can be used scientifically and reasonably, regardless of personal judgments and different tastes, to provide a suitable model for valuing companies.In this study, we will first select the appropriate model for stock valuation in 14 different types of companies using interviews with experts, so that first the weight of criteria is calculated using the network analysis process and based on experts' opinions, and finally a comprehensive model for valuing types. Various companies have been offered. Finally, a comprehensive pathology of the valuation environment is presented.Criteria used in this research in 4 categories of past profitability approach (including average EBIT, profit at past price), asset-based approach (including nominal value, book value, replacement value, net asset value and liquidation value), discount Cash flow approach (including fcff, fcfe, apv, eva and ddm) and based on market approach (p/s, p/nav, p/e except,ev/ebit, p/c, ev/s, p/b, p/cf and p/dps).

The study of the relationship between the development of information and communication technology(ICT), financial development and economic growth has always been the focus of researchers and policy makers and due to differences in views on the relationship between those and the diversity of modeling of studies in this field, researchs has not resulted in a single result. On the other hand, with the development of technology and the introduction of fuzzy logic, developed modeling methods and the possibility of consolidating expert opinions in an intelligent inference system based on collective wisdom to create indicators of ICT development and financial development now exists. Accordingly, in this study, after consolidating the opinions of experts in a knowledge base consisting of 414 questionnaires on the relationship between the constructive sub-indicators of financial development and ICT development, fuzzy indicators of financial development and ICT development using the Mamdani Fuzzy Inference System(MFIS) then assess the short-term and long-term causal relationships between ICT development, financial development and economic growth in the form of a panel error correction model considering the Dynamic Common Correlated Effects(DCCE) using annual provincial data during The period from 2001 to 2017 was covered. After consolidating the opinions of experts and creating fuzzy indicators, only in the short run, the positive causal relationship from ICT development to economic growth was confirmed.

Capital market violations are numerous and the models of dealing with them are different. judicial model, quasi-judicial model and administrative model are the most common models of dealing with violations. Regulation is the chosen model of this article. An agreeable model between capital market activists, they have determined the authority of the regulator to establish and apply disciplinary punishment in this area. In this model, the authority of the regulator in facing capital market violations and crimes has granted by individuals and by their will. For this reason, the capital market regulator, i.e., Securities and exchange organization, must be a non-profit and non-governmental institution in order to fulfil its goal. The legislator's clarification on the powers of securities and exchange organization in the law is also a kind of emphasis on a clear matter. Only effect of passing an act is the official recognition of such an institution. Then not mentioning the powers in the law will not harm the authority of this institution. Securities and exchange organization, as the capital market regulator, has the necessary tools to achieve the goals of its formation, which these tools include regulation, imposing and applying disciplinary punishments. Therefore, establishing and applying disciplinary punishment for the violators of this field has no conflict with the criminal principles and rules, as well as the principle of separation of powers.

Management manipulations are always one of the important areas of accounting literature. Managers have tools at their disposal, through which they can manipulate the earning and revenue of the firm under their management. One of these tools is classification shifting. The purpose of this study is to investigate the profit and loss items classification shifting in firms with initial public offerings on the Tehran Stock Exchange according to their age and size. For this purpose, a sample consisting of 70 initial public offerings during the years 2004 to 2019 was examined using multiple regression and cross-sectional model. The findings of the research show that in small firms (also young firms) there is a positive relationship between non-operating expenses and unexpected operating Earnings in the year before the launch, and there is a negative relationship with changes in it; But in big firms (also old firms), the relationship between non-operating revenue and expected operating revenue and changes in it is not significant. The findings of the research support the involvement of small firms (also young firms) classification shifting of expenses, by transfer operational expenses to non-operational expenses, in the year before the IPO; but there was no evidence indicating the involvement of big firms (also old firms) in classification shifting of revenues, by transfer non-operational revenues to operational revenues. The findings of this research can be effective in the decision making of investors, lenders, and analysts.