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.