One way to help investors, companies and others are involved money market and capital, prediction models about the overall prospects of companies and so that investors can make good decisions [12]. Presented theories and models to predict abnormal returns indicate that there is no absolute consensus. One of the methods is very good at forecasting the financial variables such as stock prices, stock returns, stock market crash and the use of neural network approach. The major advantage of this method over other methods can be found in this issue that better data consistency is maintained [54]. In this research to predict abnormal returns stock of two artificial neural network and fuzzy neural network approach was used in this way accurately predict abnormal returns are examined by this tool. Input variables to predict abnormal returns include earnings forecast, the degree of financial leverage, return on investment, accounting transparency, conservative accounting, the value of the brand and management have been too confident. For this purpose were examined, 452 companies-year screening method for a period of five years (2017-2012) of the companies listed in the Tehran Stock Exchange. Findings demonstrate the power of predictive artificial neural network, fuzzy neural network to predict abnormal stock returns was more than that with the margin of error is less.

For many investors, it is important to predict the future trend of abnormal stock returns. Thus, in this research, the abnormal stock returns of the listed companies in Tehran Stock Exchange were tested since 2008-2017 using three hypotheses. The first and second hypotheses examined the non-linearity and non-randomness of the abnormal stock returns ′,trend around the release date of annual financial statements, respectively. While, the third hypothesis tested the potential of the chaos model in explaining future abnormal returns based on the past abnormal returns around the release date of the annual financial statements. For this purpose, BDS, Teraesvirta Neural Network, and White Neural Network tests were used to investigate its non-linearity. In addition, Lyapunov exponent, correlation dimension, Dickey-Fuller, and Hurst exponent tests were used for testing nonrandomness and the fitness of AR, SETAR, and LSTAR models to determine the optimal model in explaining the abnormal returns utilizing R software. Results of these tests represented a non-linear and non-random process and chaos in the abnormal stock returns, implying the predictability of abnormal stock returns. Also, among three used chaos models, the LSTAR model had lower error and more predictability than the other two models.

Fluctuations in oil prices a major factor in many of the economic crisis in the oil exporting and importing countries.Stock exchange is one of the main components of the financial markets is that economic growth and development role in the country. The aim of this research reviews the impact of oil price fluctuations on abnormal stock returns of companies accepted in tehran stock exchange is structured using vector error correction model in this study using screening techniques, during 1388-1392, 96 companies from accepted in tehran stock exchange is selected.The research of the type of applied research and is the target of the kind of descriptive research that practices solidarity. After collecting the data, the variables are calculated and then using panel data regression model and random effects model to examine relationships between variables was investigated. Hypothesis test results indicate that oil price fluctuations and abnormal stock returns of companies tehran stock exchange has a significant relationship

Objective: The purpose of this research is to investigate the relationship between Firm-Specific Discretionary Accruals and Stock Future Abnormal Returns on Tehran Stock Exchange. Methods: This study carries out according to the information available in listed Companies in the Tehran Stock Exchange (TSE), during 2011 to 2016, on a selected sample consisting of 190 companies. To test the research hypothesis, OLS regression has) been used. Results: The results show that there is a negative and significant relationship between Firm-Specific Discretionary Accruals and Stock Future Abnormal Returns. Conclusion: Investors should distinguish between the stability of profit components (cash and accrual) when valuing companies. The disregard of this difference has made investors optimistic about the future performance of companies when the Firm-Specific Discretionary Accruals is high, and pessimistic about the future of companies when Firm-Specific Discretionary Accruals is low. Therefore, if such unskilled investors were affected on stock price, we would expect high prices for companies with high Firm-Specific Discretionary Accruals and low prices for companies with low Firm-Specific Discretionary Accruals. In fact, companies are valued incorrectly and irrationally and since the stability of Firm-Specific Discretionary Accruals is low, in future periods, they will receive less than expected returns (negative abnormal returns) and companies with low Firm-Specific Discretionary Accruals will earn more than expected returns (positive abnormal returns).

Disclose of Complete, timeliness and with quality reporting, leads to increase transparency. On other side disclosure whit transparency can decrease information asymmetry. Also Disclose mid transparency financial statements decrease abnormal returns. Among of information that public by firms, earnings are material. Main of this study, explorer relation between earnings transparency and abnormal return. Therefore in the first step investigate relation between transparency and abnormal return and then add control variable. In order test of hypotheses have used Data from 92 firms that listed in Tehran stock exchange. Result show there is a significant and negative relation between earnings transparency and abnormal returns.

This study examines the relation of conditional and non-conditional persistence of earning components to abnormal returns. The conditional persistence has been calculated using the concept of investors’ over-reaction towards accruals and their under-reaction towards sales revenue. The research uses multivariate regression method and the statistical sample consists of 66 firms listed in the Tehran Stock Exchange over the period from 2003 to 2016. To test the hypotheses, the panel data method and t-student test is used. The findings show a significant relation of the “the difference of conditional and non-conditional persistence of unexpected revenues” and “unexpected revenues” to “abnormal stock returns”; however, the findings indicate no relation of “differences of conditional and non-conditional persistence of unexpected revenues” and “unexpected earnings” to “abnormal stock returns”. Also, the relation between “the difference of conditional and non-conditional persistence of accruals" and "accrual anomaly" is not confirmed.

The aim of this study was to investigate the effect of volume shock on abnormal stock returns. In terms of research method, this research is in the category of descriptive-correlational research and in terms of research purpose, it is in the category of applied research. The statistical population in this study is all companies listed on the stock exchange that 120 companies were selected as a statistical sample and the information of these companies during the years 1393 to 1399 from the database of Tehran Stock Exchange and Soft ¬New Rahvard ideas were extracted. EVIEWS software and data panel template were used to analyze the data. The results of the data panel model showed that there is a positive and significant relationship between volume shock and abnormal stock returns. Because the probability value of this variable (0.0032) is less than the standard value of 0.05. Therefore, the research hypothesis of a significant relationship between non-volume shock and abnormal stock returns is accepted. A coefficient of 0.098 indicates that with an increase of one unit in the volume shock of transactions, the amount of abnormal stock returns increases to the rate of 0.098 units. The results also showed that there is a significant negative relationship between equity returns and abnormal share returns. According to the results, there is a positive and significant relationship between financial leverage and abnormal stock returns. The results also showed that there is no significant relationship between firm size and profit margin with abnormal stock returns because the probability value of these variables is higher than the standard value of 0.05.

Earning Response Coefficient (ERC) indicates the ability of earnings to explain changes in stock returns. Stock returns synchronicity shows the extent to which market and industry returns can explain changes in stock returns. In this study, we investigated the effect of Earning Response Coefficient (ERC) on the relationship between stock returns synchronicity with the abnormal return and abnormal volume of stock trading The statistical population of this study consisted of all accepted companies in the securities exchange of Tehran and statistical sample consisted of one 118companies. The data of this study is related to a ten-years period from 1385 to 1394. The data is sorted by year and company and is estimated through using Multivariate Regression Analysis of models and hypotheses of the study were assessed. The results corroborated a negative relationship between the stock returns synchronicity and ERC with abnormal return. There was no significant relationship between stock returns synchronicity and ERC with abnormal volume of stock trading.

Every investor pays special attention to the main factor in their decisions: a return. What is essential for users of financial information is not the procedures and principles used in accounting, but the exit from the financial system, because it helps them achieve their goals. Many capital market concerns focus on accounting and auditing operations. Therefore, the auditor's independence is the basis of public trust in the audit process and the assurance of auditors` reports. For this purpose, this study investigates the effect of auditor switching on abnormal returns. Therefore, three hypotheses have been formulated, and a sample consisting of 365 companies listed on the Tehran Stock Exchange during the years 2010 to 2020 has been selected. The results indicate that auditor switching has no significant effect on abnormal returns. Also, between the CU switch and CD switch, the CD switch has a negative and significant effect on abnormal returns.