Recent behavioral asset pricing models and the popular press suggest that investors may follow similar strategies resulting in crowded equity positions to push prices further away. The purpose of this research is to investigate the effect of Individual Stock Crowded Trades and Individual Stock Investor Sentiment on Excess Returns. This paper develops a new approach to measure individual stock crowded trades, and further investigates the joint effects of individual stock crowded trades and individual stock investor sentiment on excess returns. To achieve this goal, two hypotheses were developed. The population consisted of all companies listed in Tehran Stock Exchange. To test the hypotheses, using a systematic method, 186 companies were selected during the years 2013-2017. Multiple regression and panel data have been used to analyze the data. The results of the research hypotheses show that changes in Individual stock investor sentiment in Tehran Stock Exchange market are effective on Excess stock. In Individual stock crowded trades changes in the swing in the stock market lead to a change in Excess stock.

Investor sentiment about the capital market can play an important role in stock price trends, market transactions, and especially on the stock return synchronicity. The entry of many Individual investors who do not have enough information about investment, the study of this issue has made more important. To this end, in this research we investigate the relationship between investor sentiment and stock return synchronicity in Tehran Stock Exchange, by using the financial data of 167 firms listed on Tehran Stock Exchange from 15 various industries during ten years from March 2010 to March 2020. We use the Baker-Wurgler (2006) sentiment index as our primary measure of investor sentiment that Measured by principal component analysis. Also, three different methods have been used to measure the stock return synchronicity: the Mork model, the Carhart four-factor model and the Fama and French five-factor model. The results show that the Investors sentiment significantly affect on increasing stock return synchronicity. The findings also showed that the coefficients of positive and negative sentiment are not significantly different and as a result, positive and negative sentiment are symmetrically affecting the increase in stock return synchronicity.

Behavioral finance explains contradictory patterns with market efficiency hypotheses with behavioral biases. One of the most common price patterns in the stock market is the pattern of momentum, which can be driven by investors' adjustment and anchoring bias and disposition effect. In this study, the role of adjustment and anchoring bias and disposition effect on the formation of momentum returns on the Tehran Stock Exchange are examined. Using the portfolio study method and the data of the research period of 2007-2016, it was found that investors are more affected by adjustment and anchoring bias compared to disposition effect and form a pattern of momentum by reversing against the maximum price thresholds with a one-year period as the reference price. Also, among the maximum thresholds, investors are most affected by the maximum price of 26 weeks with a six-month waiting period, and further analysis and analysis using the Fama-Macbeth regression and the Fama-French three-factor model confirm these results.

The bank credit system is limited and the bond issuance process is complex. Most firms issue new shares to raise the funds they need to develop their activities and implement their plans. This article details an investigation of the impact of investor sentiment and using market timing at the time of SEO, the short and long-run stock price performance subsequent to SEOs and the cross-sectional and time-series effects of investor sentiments on both short and long-run stock price performance subsequent to SEO events. We used the Baker and Wurgler(2007) model to estimate the sentiment index in the TSE. Next We categorize all sample SEOs into high and low sentiment, according to the level of the sentiment index in the month when the SEO is conducted. we use cumulative abnormal-returns(CARs) to investigate short-run stock price performance and the buy-and-hold returns (BHAR) to examine long-run stock price performance. The data were compiled of 101 firms from different industries of TSE in the period of 1391-1398. Firms conducting SEOs during high sentiment periods experience less severe short-run price drops around the issuance and this effect are stronger for small, young, and high market-to-book ratio firms. firms conducting SEOs during high sentiment periods experience more severe post-issue long-run underperformance and this effect of investor sentiment are stronger for big, older, and low market-to-book ratio firms. By considering sentiment index level around SEOs and the firm's characteristics, investors can adopt the investment policy of selling,-buying or holding shares after the SEO.

Although a positive mean-variance relation is a cornerstone of traditional finance theory, empirical evidence supporting it is controversial and mixed. According to behavioral finance theory, the mixed risk-return tradeoffs attributes to investor sentiment in the financial market. In this paper, we investigated the effect of individual investor sentiment on the mean-variance relationship in 103 Tehran Stock Exchange firms using the BSI index. Meanwhile, we examined the relationship between small and large companies, high and low-priced firms, and growth and value stocks. The conditional volatility of stocks was calculated with GARCH models, and the research hypotheses were examined using a panel data method. The results show that the risk-return relationship in the total sample, growth stocks, and high-priced entities are less affected by sentiments, but sentiments strengthen the positive mean-variance relation in value stocks, low capitalization, and low-priced firms. However, sentiment does weaken the positive relation in high-capitalization firms. According to the research results, in constructing portfolios based on variance, investors should consider not only the sentiment of investors but also the features of the share in terms of value and growth, the market value of the company, and the stock price of the companies.

The objective of this paper is to offers a Meta-analysis of the relationship between Investor Sentiment and Stock Returns. Although it is taken for granted in the scientific research area that sentiment do influence stock returns, they have produced contradictory and inconsistent results. This paper applies meta-analysis, which is considered among quantitative statistic metods, in order to integrate the existing body of research and identify the moderators of the relationship between Investor Sentiment and Stock Return. The results of studies conducted about this relationship indicate that these studies are heterogeneous. The recorded studies consisting of Master and Ph. d. theses as well as recognized national and international papers have been selected as research populatiob. Out of these 134 research 72 cases were found qualified and suitable having the condition for studying meta-analysis. The final results showed a significant relationship between Investor Sentiment and Stock Return.

vestor sentiment index and macroeconomic indicators such as inflation, exchange rate, employment growth and real GDP of representative variables were used to market timing to predict the direction and return of the total index of Tehran Stock Exchange. In this regard, four models of logistic regression, Lasso, Ridge and Elastic Net were used using monthly data in the period 1395 to 1399. In order to develop the sentiment index, using the exploratory factor analysis model, six different emotional variables were used, and finally, three variables of stock ratio in the portfolio of investment funds, Tehran price index and top 50 index were selected. The output of the logistic regression model for forecasting based on a single index was compared with the value of forecasting based on other indicators, which showed that logistics forecasting based on all variables was superior to logistic forecasting based on a single index. Comparison of Lasso, Ridge and Elasticnet models for prediction showed that the strength and accuracy of Ridge regression model was more than the other two models, in addition, Lasso and Elasticnet models were almost equally accurate. The results of this research can be useful for investment companies and portfolio managers, analysts and investors.

Several studies in Tehran Stock Exchange have examined the effect of audit quality on investment decisions in the market, but toward most of these studies are based solely on the principle of rationality of economic agents and documentation of the relationship between audit quality and stock price and the direct reaction of the market to the audit quality criteria are indicative of the effect of audits on the investors' decisions and rarely examine the role of independent auditors on the emotional behaviors investors in the market. So, this paper the main purpose is investigating the effect of moderating audit quality on investor sentiment in stock pricing. In this study, to measure the audit quality, it has been used the observable variables such as the type of audit opinion, audit size and investor sentiment was measured by using five criteria of microeconomic and two macroeconomic criteria. For this purpose, sample of 560 years-company, during the years 2009-2016 was investigated using modified multivariate regression. The results show that the auditor's reports strengthens investor confidence to accounting information and affect the investors' sentiment in stock pricing, but the size of the auditor is not moderating and has no effect on the investors' sentiment in the capital market.

In recent researches in the field of financial markets and stock exchanges, determinig the effect of behavioral variables such as investor sentiment and trading behavior along with fundamental variables, has attracted the attention of most financial researchers, especially those of behavioral finance. In this study, in order to investigate the effect of investor sentiment and trading behavior on stock excess return, using data of 159 companies listed in Tehran Stock Exchange (TSE) during the period from 1388 to 1395, three behavioral variables including the "Investor sentiment index", "Individual investors trading behavior index " and " Institutional investors trading behavior index " were calculated and added to Fama and French 5 factor model, to achieve a new 8 factor model with a combination of fundamental and behavioral variables. Then, by analyzing multiple regression with panel data, the explanatory capability and goodnes of fit index of the new 8 factor model is compared with the FF 5 factor model and the effect of each index on stock excess return, has been investigated. The results show that, adding these three behavioral variables improves the FF 5 factor model, and the 8 factor model, fits better than FF 5 factor model in explaining the " stock excess return". Meanwhile, the effect of investor sentiment is more than the effect of investors trading behavior.