Journal of Economic Modeling Research

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"Market efficiency" is the basic axiom of Financial Economics and fondamental base for ability of optimal allocation (of financial resources) in a capital market. Vast and extensive studies around Market efficiency in recent decades, has induced strong evolutions in economist’s perception from a Market efficiency, methods of assessing and their implications in real world. This essay attempts to procure a concise leterature review of these evolutions. Results show that applied methods in Iran are incomplete in regard with new addvancements in foreign studies. So, weak form efficiency of Tehran Stock Exchange is reevaluated using new method of H statistic of Hinich. Results of empirical study shows that weak form efficiency is rejected for all the sample as a whole. But, market efficiency would be in evolvotion in studied periods based on used H statistic in this article. Also, market efficiency experienced an stationary improvement  from 2005.

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This study examines the effect of Herding in different states (low, high and extreme volatility) in Tehran Stock Exchange during the years 2009-2013 using Chang et al (2000) and Balcilar et al (2013) models. In this survey herding are tested under 3 market regimes in selected industries: Cement, Chemical, Pharmaceutical and Investment.
The results don't show evidence of herding in 4 industries using static model (Chang et al, 2000). So dynamic model (Balcilar et al, 2013) was used  to analyze Herding under 3 regimes in which our results support the presence of  herding under 2 market regimes (high and extreme) . The results also demonstrate evidence of herding behavior under the high volatility regime for all of the selected industries. Herding under the extreme volatility regime is only found in investment and cement industries.

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Modeling price fluctuations in financial markets is very important. We try to model price fluctuations in Tehran stock exchange using heterogeneous agents’ model.  We used agent-based computational approach. In this model, there are two kinds of agents, some agents have extrapolating expectations (chartists) and others have stabilizing or mean-reverting expectations (fundamentalists). The dynamics of shares of these two types of agents make price fluctuations. For determining the relative effectiveness of agents expectations, Diechi and Westerhoff (2012) method, is used.  For this purpose, weekly data of Tehran Stock Exchange price index (TEPIX) from 1997 to 2014 were used. Modeling results show that the relative sensitivity of buyers with different expectations, and their relative impact to aggregate demand, have significant and important role in the price dynamics of Tehran stock market. We also show that the relative impact of chartists to price fluctuations very important and over the past two decades, the share of them from aggregate demand have been more than 80 percent.

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The main purpose of this study, is to evaluate the effect of diversion earnings forecast and earnings realized on returns stocks in Tehran Stock Exchange. In fact, this research aims to examine the diversion of earnings resulting from the diversion of corporates managers forecasts earnings, what impact these diversion of earnings have on the returns of stock price. To achieve this, 194 companies listed in the Tehran Stock Exchange selected in the period of 2005-2013.
In this study, two groups of companies experienced the highest returns and lowest returns over the period studied, have been selected. Multi-factor model of Fama and French (1993) was used as the theoretical basis. The results indicate that forecasts of companies have experienced highest returns in comparison with lowest returns are more cautious and accurate than prediction of their future earnings. Changes in earnings realized and Tehran Stock Exchange index returns have positive and considerable relationship with stock returns as well, but these relationships for companies with highest returns are stronger than companies with lowest returns.

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Noise traders make decisions based on market sentiment and buy and sell assets based on unrelated information. These traders generally have poor timing, follow trends, and overreact to good or bad news. The experience of financial markets shows that noise traders cause excess volatility and deviation of the stock value from its intrinsic value. This study seeks to evaluate the role of noise traders on the occurrence of bubbles in the Tehran Stock Exchange in the period 2011 to 2017 .Therefore, the research hypothesis is: "The effect of noise trading on the occurrence of bubbles in the Tehran Stock Exchange is positive and significant." In this study, PCA method is used to extract a composite sentiment index, The GSADF method also is employed to determine the bubble periods of the Tehran Stock Exchange price index. Finally, the logit method is applied to measure the effect of noise trading on the bubble in the stock market price index. The results show that the effect of noise trading on the occurrence of bubbles is positive and significant. Also, the estimation of the final marginal effect indicates that the increase of one unit of optimistic sentiment and optimistic sentiment with a lag in the stock market increases the probability of bubbles by 24 and 28%, respectively.

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