Tehran Stock Exchange

The ultimate goal of investments in stock markets is to earn a satisfactory return on investment, but this is difficult to achieve without enough information to predict stock returns. Information asymmetry refers to a situation where some investors have access to private information that is not reflected in the prices and is yet to be revealed to others. Information asymmetry as a market failure can lead to adverse effects such as poor investor decisions, increased corporate investment risk, and finally reduced stock returns. The issue is important in capital market of developing countries particularly due to the incomplete voluntary disclosure of information as well as its low quality and defective regulatory system. Therefore, in this study, effect of information asymmetry on stock returns has been investigated in a select group of companies listed in Tehran Stock Exchange. The analysis of this relationship was conducted dynamically for the short-term and long-term using Westerlund and Dumitrescu-Hurlin tests and Generalized Method of Moments to achieve articulated results. Using the tests is suitable with cross-sectional dependence of variables and error terms. Also, using the method is appropriate for measuring lagged effect of dependent variable and removing the bias caused by the endogeneity of explanatory variables. The Results demonstrate a significant relationship between information asymmetry and stock return dynamically in short- and long-run. The results show that there is a negative systemic effect of information asymmetry on stock return. Also, debt to asset, profit to sales, firm size and lagged stock return effects are significant.

This study examines the relationship between stock liquidity and return predicta-bility of 116 publicly-traded firms in Tehran Stock Exchange (TSE). To this end, we constructed a dated-regular frequency of time series with total 40128 stock-firm observations. After calculating daily bid-ask spreads and stock returns, the observations were classified based on liquidity into three classes and the return predictability was investigated across different classes using a set of parametric tests. The results exhibit signs of return autocorrelation and non-independence over three liquidity groups. Our findings didn’t show a connection between stock liquidity and market efficiency. The Hurst exponent also revealed mean reversion of returns series across different liquidity classes. We conclude that stock liquidity doesn’t play a significant role in market efficiency and return predictability of stocks in TSE. In case of TSE as other emerging markets, due to the small num-ber of traders (the need for more trading activity) and low market making activi-ties, both the cost of trading increases and the reaction to stock price information is delayed, resulting in predictability of price /return.

The stock market is one of the main components of the economy, and various factors cause fluctuations in it, one of which is the effect of investors' behavior. Therefore, present study seeks to answer the question of whether the feelings and sentiments of investors might intensify the fluctuations in the Tehran Stock Exchange or not. To answer this question, at first, in order to quantify sentiments, as non-abstract variables, the Equity Market Sentiment Index (EMSI) was used that investors are classified in 5 categories of completely risk-averse, risk-averse, neutral-risk, risk-taking and completely risk-taking. Using GARCHi-in-Mean, results indicate that the sentiments of investors will result in greater fluctuations in the Tehran Stock Exchange. Hence, if fluctuation is considered an indicator of market risk, the excitement associated with an abnormal rise in volumes will increase that risk.

Objective: In today's interconnected global economy, changes in one market can have ripple effects across related markets, making it essential for economic and financial policymakers and experts to accurately predict these mutual impacts. Various methods have been developed to forecast the impact and mutual impressions of financial markets. In this study, a generic framework is proposed for forecasting economic and financial market indicators using the interrelationship of shocks among global financial markets and a system dynamic approach. Methods: To demonstrate the stages of the proposed generic framework and system dynamics modeling, as an example, the study forecasts the Iranian economic and the Tehran Stock Exchange indicators using their interactions with eleven major global financial markets, including London, Tokyo, Shanghai, Frankfurt, Paris, Milan, SIX Swiss, Istanbul, Korea, Bombay Stock Exchanges, and Dubai Financial Market. The New York Stock Exchange index return is used as a stimulant or driver for the other stock exchanges in the model.Results: The results indicate that the proposed forecasting model successfully predicted the Iranian economic and the Tehran Stock Exchange indicators. Furthermore, the study finds that while Iranian exports are sensitive to global financial markets, the sensitivity of imports and production returns to global financial markets is low. Conclusions: The proposed generic framework and system dynamics modeling can provide valuable insights for predicting different economies using their interactions with the global economy and finances.

This study aimed to investigate the performance of diverse stock market indices on the Tehran Stock Exchange during two distinct phases: a boom from September 2022 to December 2022 and a recession from December 2022 to September 2022 in the foreign exchange market. The results of this study diverged from the anticipated outcomes and show that by using dynamic conditional beta and conditional Treynor ratio during the period of exchange rate boom, export-oriented companies such as metals and chemicals in the Tehran Stock Exchange did not perform better than non-export-oriented companies such as Insurance and medicine. While it is always believed that export-oriented firms outperform the others when the Rial depreciates.

The purpose of this research is to investigate the reasons for tax evasion in companies, which uses two independent variables (financial constraints and tax planning opportunities) and tow dependent variable (firm value and tax evasion by tax difference method) in the form of 13 models. The 11 indicators have been considered for the variable of financial constraints of companies, and the model is implemented for all these indicators. The research was conducted in the 5-year period from 2015 to 2019 in the Tehran Stock Exchange, and Eviews software was used to analyse the data and fit them for 3 research hypotheses. The results of the research show that the opportunity for tax planning has a negative effect on the value of the company, and the increase in the opportunity for tax planning and subsequently tax evasion causes a decrease in the value of the company. Also, the research results showed that there is a significant relationship between tax planning opportunity and tax evasion (by tax differences method) of companies, while there is no positive relationship between financial constraints and tax evasion (by tax difference method) in companies that have tax planning opportunities.

This study explores the considerable significance of candlestick chart patterns as a foundational asset within the realm of stock market analysis and prediction. As a graphical representation of historical price movements and patterns, Candlestick charts offer a distinct and valuable perspective for understanding how the financial market operates. This perspective assists us in accurately pinpointing the most advantageous times for making decisions to buy or sell financial securities, such as stocks or bonds. These charts provide insights into market trends and potential trading opportunities. We adopt an innovative approach by harnessing image processing techniques to extract and analyze patterns from Candlestick charts systematically. Our findings underscore the pivotal role of visual data in financial analysis, particularly in times of market volatility and uncertainty. Investors often resort to technical analysis strategies when confronted with erratic market trends, often relying on insights derived from chart-based analysis to guide their decision-making processes. By meticulously extracting essential insights from candlestick charts, our study aims to provide investors with more efficient and less error-prone tools. Ultimately, this endeavor contributes to the enhancement of decision-making precision and the mitigation of risks inherent in participating in the dynamic stock market landscape.

Several studies in the field of capital markets indicate that changes in macroeconomic parameters, including crude oil price changes in many cases, have significant effects on capital market indexes. The present study seeks to investigate the effect of crude oil price changes on the indexes of Tehran Stock Exchange and Saudi Stock Exchange also known as The Tadawul Exchange using the two-factor capital asset pricing model with samples gathered from years 2016-2022 from both markets. The results of the study show that, both markets are relatively sensitive to the oil price index and despite severe economic sanctions imposed on Iran, Its capital market, having more significantly oil-related indexes, is still more oil-dependent than that of Saudi Arabia. The results also suggest the asymmetric relation with oil price movements in both countries due to their oil-exporting nature where both markets are more sensitive to negative oil price movements rather than its positive ones. Also, it is concluded that due to the diversity of industries in Tehran Stock Exchange, the economic sanctions imposed on Iran have a more directed impact on its capital market rather than affecting it through a mediator parameter such as oil price movements.

The purpose of this research is to design a profit maximization model for companies using the theory of constraints. To collect information, library and field studies were used, according to the method of data collection, documents, interviews and questionnaires were used, so the current research method is mixed (qualitative and quantitative). The statistical population of the research in the qualitative part included experts, professors and specialists in the field of management accounting, 10 of whom wereselected by snowball sampling until theoretical saturation was reached, and primary data were collected through interviews and a questionnaire was designed. A questionnaire was included in the quantitative part as well. All managers and assistants of the finance and accounting departments of manufacturing companies admitted to the Tehran Stock Exchange were an unknown number. According to Cochran's second formula, 385 people were selected by available sampling. A questionnaire with 78 questions was used tocheck the research variables. Cronbach's alpha coefficient confirmed the reliability of the questionnaires, 10 interviewees confirmed the content validity of the questionnaires, and their construct validity was confirmed by confirmatory factor analysis. Then, the data obtained from the questionnaire was analyzed in two sections: descriptive statistics and inferential statistics. In the section on inferential statistics, the Kolmogorov-Smirnov test was used to check the type of data distribution in terms ofnormality or not, and then confirmatory factor analysis by LISREL 8.80 software. In order to check the construct validity of the questionnaire and to test the structural equation model with the help of Lisrel SmartPLS.03 software, it has been used to answer the research questions. The most important findings of the research showed that the components of identifying the limits of profit maximization, exploiting the limits of profit maximization, spreading the effect of profit maximization decisions, removing system limitations, and the process of continuous improvement of profit maximization, respectively, with a path coefficient of 0.41, 39 0.0, 0.43, 0.37, 0.40 have a positive effect on the theory of limitations