فصلنامه دانش مالی تحلیل اوراق بهادار
سال سیزدهم شماره 48 (زمستان 1399)

The goal of this research is to study excessive trading speed of traders on abnormal cumulative return on stocks around seasonal earnings announcements. Research sample includes 161 companies from listed companies in Tehran stock exchange that includes a time period from the beginning of 2013 to the end of 2017. Results show that excessive speed of traders around seasonal earnings announcements has meaningful relation with abnormal cumulative return on stocks, and leads to increase in abnormal cumulative return on stocks, that this increase in time limit of one month before and one month after earnings announcement related to fourth quarter of the year (fourth announcement) is weaker than first, second and third quarter. As a result, existence of high trading speed of stocks in all four time points affects abnormal cumulative return on stocks  and leads to development of the theoretical framework of information asymmetry , because quick deals around earnings announcements leads to renew the gap between information released in market  and traders information , and increases  information asymmetry in market.

The Incomplete Revelation Hypothesis argues that some companies, for some reason, disclose the information incompletely, complexly, difficultly and rigorously. One of the reasons why disclosure of information is difficult is the existence of fraudulent financial reporting. Fraud encourages the director to disclose information in a complex way so that the minds of users of financial information go beyond anything other than fraud. The purpose of the present study is to investigate the Fox Index Reaction Versus Companies With the Possibility of Fraud. Fox Index is a benchmark for identifying the complexity of financial statements. The research methodology is based on a content analysis approach based on an incomplete Revelation hypothesis. The statistical population of the study consisted of all listed companies in Tehran Stock Exchange from 2009 to 2016. The sample size is based on the systematic elimination of 112 companies. The research hypothesis was tested using multiple regression model and parent test based on Panel data. According to the incomplete Revelation hypothesis, the research evidence suggests that companies with a high probability of fraud are more complicated financial reports with less readability than companies with a low likelihood of fraud Publish. The findings of the present study, while completing the gap, have been carried out in the field of concealing the opportunistic behavior of managers about the non-disclosure of financial information, can be used to increase potential investors, stock market organizations and other stakeholders. Accounting information is useful in decision making

Mutual funds and investment companies are very important institutions for investing in capital markets. Hence, measuring their performance with the aim of identifying efficient investment firms and providing a corrective remedy for inefficient firms is essential. The purpose of the present study is to propose a new approach to assessing the performance and classification of investment firms in terms of uncertainty. Considering the two-stage structure of investment firms, in this research, the approach of network data envelopment analysis (NDEA) is used to evaluate the performance of each stage and the entire investment company. Also, in order to take into account, the uncertainty of the data, the interval network data envelopment analysis (INDEA) model for a two-stage structure is presented. Using the data of 10 active investment companies in Tehran Stock Exchange, the proposed research approach has been implemented and all companies have been evaluated and classified. The results of INDEA model based on non-cooperative approach indicating on the efficacy and effectiveness of the proposed approach of research for performance measurement of investment firms under uncertain data.

The purpose of this study was to investigate the role of psychological and performance factors on willingness to invest in the stock market with the mediating role of investor satisfaction and perceived investor risk in Iran. This research was conducted in 1977 and is methodologically developmental-exploratory. The statistical population of this research is customers of Tehran brokerage companies. The sampling method is available and since the number of community members is unlimited, the sample size should be 384 according to Morgan's table, so the distribution of the questionnaire was randomly distributed among the investors until the responses were sufficient. A total of 384 questionnaires were collected. Structural equation modeling and path analysis were used to analyze the research data. SPSS 23 and SmartPLS3 software were used for data analysis and the findings showed that perceived risk and investor satisfaction were used. They have a mediating role in the relationship between psychological and performance factors on the willingness to invest in the stock market.

One of the factors that exacerbate stock price volatility is the constraint on financing, while tax avoidance facilitates the development and expansion of profit management and maintenance activities and the dissemination of negative news over a longer period of time. This news may one day be released on the market and may increase the risk of future stock price crashes. On the basis of the present study, the data of 165 active companies in Tehran Stock Exchange were examined in order to investigate the effect of restriction of financing on the risk of falling stock market prices and the role that tax avoidance can play as an intermediary variable. The research sample was selected between 2013 and 1977 and then multivariate regression of panel data model and generalized least squares (GLS) method was used to test the research hypotheses. The findings indicate that the restriction on financing has a direct impact on the risk of falling stock prices and tax avoidance can also increase the risk of falling stock prices.

CEO as a decision-maker at the head of the company, especially firms of their nature, is based on agency theory, plays an important role in increasing the level of transparency and creating information symmetry. Persuasiveness behavior as a component of other science topics and issues developed capital market and financial management which may affect management approaches in disclosure. The purpose of this research is Presenting the CEO's model of persuasion through disclosure of financial information based on comprehensive structural-interpretative analysis (TISM). This combined research is based on qualitative and quantitative methodology. The statistical community of the quantitative section included 18 university professionals who specialize in financial and accounting management. The statistical population of the qualitative section included 30 managers of Tehran Stock Exchange companies that participated in the matrix analysis section. In this study, firstly, statements about the persuasive ways of managing the financial information disclosure began through a large study of relevant content and after categorizing 79 articles, the researchers terminated the classified articles, and in the end, 24 studies were introduced into the analysis further. After completing the process, 17 statements were identified in terms of three components that were reduced to 15 after Delphi analysis. In the Structural-Interpretative Analysis section (TISM), which is due to the mathematical and operational complexity of Structural-Interpretative Analysis (ISM), it was identified in the model presented. Stimulating the aspirations and expectations of shareholders and investors as a proposition of psychological approaches to persuasion and distortion through the massive display of regulatory and control mechanisms as the proposition of philanthropic approaches as the most influential statements by the CEO in disclosing information and reporting accompanying financial statements.

Intelligence is recognized as one of the criteria for investing in capital markets and its proper use can, while controlling risk, increase the attractiveness of the capital market for investment decisions. The purpose of this research is to analyze the schematics of equity investor investment predictions based on Q (Q). This research was conducted during the one-year period 1396-1397 with the participation of 17 stock brokers. In this research, 20 propositions related to investment intelligence were identified through content analysis in research articles related to the research topic, and then, based on the analysis of the QA statements, identified by factor analysis and the Varimax method, using software (SPSS) they got. Based on the results, 20 investment investment propositions were categorized in the form of 3 mental patterns. The results show that knowing the mental priorities of intelligence in investing can help brokers create high-yielding investments for shareholders and make them more personalized analysis than investment positions in the capital market.

This study examines the relationship between volatility and the probability of occurrence of expected extreme positive and negative returns in The thehran security market.‌‌ The purpose of this research is optimation portfolios via hold positive return and eleminate nagative return.‌‌ Two measures of volatility and the factor of expected shortfall are examined:‌‌ conditional volatility calculated using an EGARCH model and idiosyncratic volatility based on the Fama and French five-factor model and expected shortfall calculate with smi-parametric metod.‌‌ This paper is based on regresion probit‌ model and data use from 1382 to 7/1397.‌‌ A significantly positive relationship is observed between a firm’s idiosyncratic volatility and the probability of occurrence of an extreme return.‌‌ Other firm characteristics, including firm price, volume and Book-to-Market ratio, are also shown to be significantly related to firm extreme returns.‌‌ The relationship Between the age factor and exterem return is not found relation.‌‌ The effects of conditional and‌ expected shortfall are mixed.‌‌

Encountering with financial crises of supervision and predicting such these events which are necessary to decrease their negative effects on finanicial and economical markets. The current paper is aimed to review the designing the early warning system of financial crisis outbreak in Tehran stock Exchange. Due to this purpose, it’s used the weekly datas during the years from 1997 to 2019 (1121 weeks). The mean of crises in this present papper is the falling more than 15% of price index (TEPIX) toward last three months. Hence, it’s been used the dummy variable for operating the dependent variable. It’s been used the residual of auto regressive integrated moving average (ARIMA) for measuring the shocks caused by the price of stocks, exchange rate, price of oil and gold. The result is modeled by Logit & Probit model and showed that probability of the crisis outbreak is increased by decreasing the stock price in past period as well as the outbreaking of crisis in past period after reviewing and analyzing the data. While the decreasing of exchange rate, increasing of the gold price, and decreasing of oil price don’t affect on crisis outbreak in current periods as meaningfully. Based on weekly data, 44 crisis has occurred which both models have predicted 36 crisis. The power of crisis predicting is 82% and the power of predicting for total model is about 99%.

In the last three decades, the Iranian economy has faced many vicissitudes in macroeconomic areas such as the banking industry. Analysis of the dominant condition of Iran’s banking system indicates that although it has not practically resulted in an explicit crisis due to the state-owned banks and the central bank's financial support, the Iranian economy has experienced a banking crisis. The main objective of the current study is to examine the role of banking crisis in the effect of Income diversity on Profitability of banking industry using panel econometric method) EGLS .(For this purpose, 8 accepted banks in the Tehran Stock Exchange were evaluated as a research statistical population during 2005-2015. The results show that an increase in the share of Non-interest income in the time of banking crisis has a significant negative effect on return on equity. However, there is a significant positive relationship between the ratio of lending facilities to bank assets and return on equity during times of banking crisis. This means that in times of banking crisis, generating interest income is more efficient for the banks than diversifying their activities and investments. The results also suggest that variables of capital adequacy and efficiency in times of banking crisis have significant positive effect on return on equity, but on the other hand, the degree of bank concentration (Lerner) in times of banking crisis has significant negative effect on return on equity.

Since the problem of optimizing the stock portfolio in nonlinear conditions with multi-objective functions cannot be effectively solved using traditional and traditional approaches, in this research, a metaheuristic approach is proposed to optimize the stock portfolio using the particle swarm optimization technique. This method has been implemented on a variety of investment portfolios with selection constraint and unconstraint conditions for the investor. By implementing the algorithm and in order to validate it, the results were compared with the genetic optimization algorithm. The computational results indicate that particle swarm optimization algorithm has a good performance, so that the results seem very promising and satisfactory for use in real conditions.

The purpose of this study is to present a model for executing smart financial portfolios using Kalman filter model and kelly functions. For this purpose, using the monthly data of 180 companies listed in Tehran Stock Exchange during the period 2013 to 2019, using the Kalman filter model and kelly functions, the Sharp ratio is improved and the intelligent method for trading based on momentum and capital algorithms Long-term stock listing was presented and the purpose of the study was examined.The results of the algorithms implementation confirm that the proposed structure of the intelligent model of kelly functions is better in terms of average efficiency and Sharp ratio than the quantitative investment algorithms and it is possible to use the general constellation in optimal allocation of resources to achieve more desirable results. Finally, the results indicated that the performance of the smart portfolio with the kelly functions algorithm is better than the momentum model and long-term investment.

This paper studies the relationship framework between individual and group acts of stock trading activities in Tehran stock exchange which leads to the development of a cohesive relationship model for individual and group acts of stock trading behaviors. It has a quantitative–qualitative hybrid approach in which the model is designed by using Delphi technique at first stage, and it is tested and assessed by using structural equation modeling method at second stage. The model shows that areas of financial capability, financial capacity, word-of-mouth communication, mass media, financial consultation, stock trading behaviors, and personality are considered as causal conditions of relationship framework of individual and group acts which affect that process positively and meaningfully.