جستجوی مقالات مرتبط با کلیدواژه « Herding Behavior » در نشریات گروه « اقتصاد »

The purpose of this paper is to analyze the effect of the heterogeneous behavior of investors in the housing sector on housing prices and subsequently on Iran's economic growth during the period 2001:3 to 2020:3. For this purpose, first, the effect of herding behavior and overconfidence of investors on housing prices and then the effect of housing prices on economic growth was estimated by smooth transition regression (STR) method. Then, by calculating the Sobel statistic, the mediating role of the housing price in the transmission of the behavior of investors in the housing sector on economic growth was tested. The results showed that the housing price and economic growth functions have a threshold and two regimes. The imitative behavior of a previous period is the transition variable of the housing price function with a threshold equal to 0.0051 percent. The housing price is also a variable of economic growth function transfer with a threshold equal to 0.0266 percent The estimated coefficients of the first and second regimes indicate the asymmetric behavior of investors on housing prices. The estimation of the economic growth function showed that housing prices had a negative effect on economic growth in the first and second regimes, but this effect was strengthened in the second regime. The calculation of Sobel's statistic also showed that the housing price had a mediating role in transferring the effect of herding behavior on economic growth, but it did not act as a mediator in transferring the effect of overconfidence on economic growth.

The existence of uncertain conditions affects the confidence level of investors, which leads to a change in approach from rational to behavioral, judgments based on subjective perceptions, non-scientific information,  rumors, and prevailing market conditions, and it causes blindly following by some market activists, which is called herd behavior.  In the present study, the presence or absence of herding behavior of investors of industrial companies in the Tehran Stock Exchange is investigated. This research based on the data of the Tehran Stock Exchange from July 2018 to July 2021 and by considering various factors such as institutional investment, fundamental factors, and factors with lag as past trends through a regression equation, the presence or absence of herding behavior of investors evaluates. The results showed that there was herding behavior during the study period. However, by adding a) fundamental factors of variables such as P/E ratio, share turnover, capital of market, and market liquidity b) calculation of external factors such as political instability, global financial crisis, and oil price fluctuations, and c) Lagged effects, the intensity of herding behavior with a low change is observed. However, the key and final finding indicates the existence of herding behavior from July 2018 to July 2021, which is exactly consistent with what was formed in the Tehran stock market during this period.  In other words, investors blindly follow the actions of a group of people in the market irrationally and without paying attention to personal information or following scientific principles about a specific investment or decision. The feelings transmitted among people due to emotional behavior of entering the stock market affect their decision or it can be deliberative, conscious, and controlled in which social norms affect their decisions.

For the first time, this research investigat the relationship between speculative sector on herding behavior in the Tehran Stock Exchange market by using the (TVP-FAVAR) model and seasonal data from the years (1388- 1) to (1400-4). The results confirm the existence of herding behavior in the in the stock market and it shows the negative effects of the speculative sector impulse responses on the beta-herding behavior. n addition, the effects of impulse responses of other main variables of the model on the behavior of investors were as follows: the effect of beta herding behavior on itself was almost zero that means this variable was not affected by itself, the effects of GDP in the first three periods were neutral and Then in the year 1400, it became slightly positive, the inflation variable with a two-season delay had insignificant positive effects, and then in the following seasons, mainly in the seventh seasonhas been strongly negative, the total stock return variable was almost positive, and finally, the stock liquidity variable had negative effects on the beta herding behavior variable.

The experience of the world economy over the last few decades shows that herd behavior is one of the main factors in the formation of financial crises. In identifying the causes of such behavior, economists have pointed the finger of accusation at various factors, and it can be said that monetary policy is at the top of this list. Because of the harmful effects of herd behavior on stock market, identifying the factors influencing this type of behaviour can be of great importance. As a result, the main objective of this study is to investigate the effect of monetary policy on the formation of herd behavior in Tehran Stock Exchange. In this regard, using the monthly data from April 2009 to March 2021 and using the non-linear STR-GARCH model, the effect of monetary policy on the formation of herd behavior in the Iranian stock market was investigated. This method allows the researcher to model the non-linear pattern in herd behavior. In the estimated model, Chang et al.’s index (2000) was used to measure the dispersion of stock returns around the market return, also, the monetary policy variable (growth of liquidity) was used as threshold variable. By choosing this variable as a threshold variable, we can check whether changes in this variable can lead to a transition from a rational regime to a herd regime or not. The results of the study indicate that herd behavior in Tehran Stock Exchange has a variable behavior over time and the linear model is not suitable for investigating such behavior. Also, the results of the research show that based on different values of liquidity growth variable, the behavior of investors changes, so that for monthly liquidity growth values smaller than 2.3%, rational behavior is observed in investment decisions, but with an increase in the growth rate of liquidity and crossing this threshold, over time, herd behavior becomes the dominant behavior in the stock market.

The purpose of this article is to analyze the effect of the heterogeneous behavior of investors in the housing sector on housing prices and inflation in Iran during the period 2001:3 - 2020:3. The threshold effects of behavioral variables on housing prices and the effect of housing prices on inflation using smooth transition regression method (STR) is estimated. Then, using Sobel's statistic. The results of the estimation of house prices show that Herding behavior has a positive effect on housing prices in the first regime and the second regime. Overconfidence in the first regime was ineffective on housing prices, but in the second regime, it had a positive and significant effect. The results of estimating the inflation model also indicated that there are two limit regimes for the inflation function. Housing prices had a positive effect on the inflation rate in the first and second regimes. The calculation of the Sobel statistic also indicates the confirmation of the transmission of the effect of herding behavior on inflation from the housing price channel, while the Sobel test did not confirm the transmission of the effect of overconfidence from the housing price channel on inflation

In recent research, the need for regulators and policymakers to evaluate the effects of government policies on markets can be felt according to the behavior of market participants and their deviation. Herding behavior is an important behavioral element and refers to a process in which market participants imitate one another's actions and adjust their financial decisions based on other people's actions. Based on the estimations of the herding model, investors put aside their opinions about the equilibrium point of the market, and the beta-herding of individuals leans towards the beta-herding of the market. According to this method, investors consider the general trend of market return and introduce the amount of cross-sectional dispersion as a herding pattern. In this article, the relationship between the monetary policies of the central bank and herding behavior in Tehran stock market is investigated for the first time. Central banks have serious motivations to pay attention to the possible herding behavior caused by their actions for two reasons. First, the herding behavior may neutralize the intended outcome of a monetary policy. Secondly, the monetary policy has the ability to eliminate price bubbles in the financial markets by itself. In this study, a wide range of data related to Iran's economy is experimentally examined by using the (TVP-FAVAR) model to see if the central bank's monetary policies have an effect on the beta behavior of investors. If so, is it possible to say in which years these effects were greater, which monetary policy tools were more effective, and how fast this policy impacted the beta-herding behavior?

In this research the herding behavior is measured based on the beta-herding behavior model of Huang and Salmon (2009) in which addresses the change of the cross-sectional level of systematic risks. In this model, the dynamic characteristics of herding behavior are referred to and the herding of investors are considered as a variable in time. Huang and Salmon argue that behavioral biases may affect investors' understanding of the asset price equilibrium; as a result, the estimated beta deviates from the traditional risk-return relationship that can serve as the beta deviation from beta equilibrium to measure the herding. Besides, the main channel of transmitting these effects is through expectations in that the central bank can have significant effects on the stock prices of this market by shaping the expectations of investors in the stock market. Therefore, first by calculating the beta-herding coefficient in Tehran Stock Exchange market and then by estimating the variable of beta-herding behavior, the (TVP-FAVAR) model (designed by Koop and Korobilis, 2013) was regressed by the MATLAB-207 software to investigate the hidden variable effects of monetary policies on the beta-herding behavior of investors in Tehran Stock Exchange market from the quarterly data of 30 main variables in the Iranian economy from Jan, 2019 to Jan. 2021.

In the calculations for the beta-herding behavior, the existence of this behavior has been confirmed in the whole period of 2009-2021. According to the results, the peak of this behavior occurred from 2020 to the end of 2021 and, at a lower level, from 2015 until the end of 2016. The output of the TVP-FAVAR model regression shows that the impulse response of the hidden variable of the expansionary monetary policies up to the first four seasons has a high impact on the beta-herding behavior. This means that the changes in the monetary policy can have important effects on the beta-herding behavior in initial seasons. According to it, the peak of these reactions happened in the years 2013-2019. The impulse response of the variable GDP growth rate had insignificant positive effects after three seasons, and the inflation rate variable after two seasons had no effect but became positive in the third and fourth seasons. After that, these effects became negative. Although the variable of the total return of the stock market had little effects, it continued for four seasons positively and suddenly turned negative in the fifth season. Finally, the liquidity of the stocks was of small effects but positive in the first two seasons. From the third season onwards, these effects became negative. One of the strong points of this research is extracting the probability of influence of each of the monetary policy instruments on the numerical value of the hidden variable of monetary policy, according to which the rate of change in the volume of money and visual deposits has the greatest influence, and the rate of change in the volume of pseudo money has the least influence on it. In addition, during 2013-2019, economic decision makers used most of the monetary policy tools to implement these policies.

Conclusion and Policy Implications:

 In summary, Iran's economy is a developing economy and has its own limitations, and the plans and actions of economic decision makers affect people's behavior in the capital market. The results of the research show that the government can make effective changes in the stock market with monetary policies and guide investors’ behavior. Therefore, the government and economic decision-makers can influence the behavior of investors at times when this market has a price bubble or the market goes out of its way. It is to be mentioned that the government should not lose its information credibility in this market, because behavioral discussions pay attention to the behavior of ordinary human rather than economic human. This can even get an opposite response from investors. From another point of view, it can be claimed that, if the government decides to exert less influence on this market, it can implement its monetary policies by diversifying monetary policy tools and make its effects on the stock market unpredictable. Otherwise, the alternative proposal for the implementation of policies will be monetary disciplines that can reduce these effects. Another suggestion of attraction for the future research to delineate the direction of government policies is the investigation of the influence of monetary policies on each of the industries or each corporation on the stock market.

Today, export-oriented companies are very important. These companies need a lot of investment to expand their activities, which is one of the best ways to finance the stock market and since market return is one of the factors influencing people's decisions to direct their capital to this market return. Therefore, the analysis of factors affecting this market return is importants and hence the main purpose of this article is to analyze some fundamental, political and behavioral on the market return of export-oriented companies of Tehran stock exchange. The sample includes 41 export-oriented companies of the Tehran stock exchange selected by classification method. The data during 2011-2018  has been collected from the rahavard365.com website and codal.ir website. Empirical results based estimate by Semi-parametric and parametric (GLS) method applying for the stata (16) software. Empirical results shows US unilateral withdraw from JCPOA and herding behavior have a significant positive effect on the market return of export-oriented companies of Tehran stock exchange. Noise trading, size of company, financial leverage and Market-to-Book equity ratio have not significant effect on the market return of export-oriented companies of Tehran stock exchange.

One of the main issues discussed in the behavioral financial paradigm is the herd behavior of investors. Herd behavior indicates a situation in which investors, regardless of personal information and analysis, follow other investors. This study investigate the effect of investor sentiment on herd behavior formation with beta herding approach in Tehran Stock Exchange. In other worlds, the purpose of this article is to examine whether investors decision making in Tehran Stock Exchange based on fundamental variables or market performance. Although this phenomenon may be considered logical from an individual point of view, but from a macro perspective, it can have destructive effects such as bubbles, price crashes, sharp price fluctuations, and as a result, distorted equilibrium relations and market inefficiencies. Huang and Salmon (2001) scientifically studied this phenomenon by presenting a model called beta herding. They believe that the simultaneous attention of investors to market returns causes the return of individual stocks to biased towards market returns, and as a result, the stock beta coefficient is close to the market beta coefficient. This study uses a beta herding method to investigate the effect of market sentiment on the probability of herd behavior in the Tehran Stock Exchange. In other words, this study examines whether investors in the Tehran Stock Exchange make decisions based on fundamental variables, or trade by ignoring these variables and being affected by market performance. This study also examines whether the stock beta coefficient affects the impact of market performance on investor decisions?

The theoretical basis of this article is the information cascades theory. According to this theory, when investors observe a flow of information, review information and personal analysis according to the existing flow of information. Since paying attention to market returns instead of fundamental variables disturbs the equilibrium relations in the market, so applying a CAPM-based approach can be used to identify and analyze herd behavior. This approach that founded by Huang and Salmon (2009) herding behavior is analyzed by basing the CAPM equilibrium relationship and examining market influence on this relationship. Based on the herd beta approach, the cross-sectional variance of betas can be considered as a measure of the impact of market returns on investors' decisions. This means that the more investors pay attention to the market factor in their decisions, the smaller the cross-sectional deviation of betas will be. Therefore, the smaller cross-sectional deviation of betas can indicate the presence of herd behavior of investors. Since the herd behavior of investors in following the market returns, causes the stock beta to be biased, so the following relationship can be established between  and . (Huang and Salmon, 2009):Which  is the equilibrium beta and   is the biased beta. The above relationship can be rewritten as follows:The significance of   statistic as the slope of the line in the above relationship indicates the effect of market returns on investors' decisions and the formation of herd behavior. In order to investigate the effect of beta coefficient on the severity of the effect of stock returns from market returns, the following equation has been used:In above equation, the dependent variable is difference between low beta portfolio return (  with high beta portfolio return (  and herd behavior criterion  is the independent variable. Also h is used as a lag, which in this study is assumed to be equal to 1. Negative and significant  as the coefficient of  (cross-sectional deviation of estimated betas ( ) in above relation means that stocks with high and low beta coefficient react the same to market returns. Conversely, positive and significant  means that stocks with high and low beta coefficients do not show the same reaction to market returns, or in other words, stocks with low beta coefficients are more affected by market returns than stocks with high beta coefficients. Also  as a measure of monthly herd behavior is calculated by deviating from the standard  according to the following equation (Huang and Salmon, 2009):This research has been done for a period of 120 months, (from March 1, 2009 to the end of March 2018). The statistical population of this research consists of all companies listed on the Tehran Stock Exchange, which are filtered according to the following conditions:The first transaction on their stocks has been done since the beginning of 2009 or before- Have not been removed from the list of listed companies during the research period--There is no long-term suspension (more than six months) in trading on their stocks.Applying the above conditions, 112 companies remained to be surveyed, which were surveyed without sampling.

By conducting this research, we found that investors' sense of market return has a significant effect on the occurrence of herding behavior by them in the Tehran stock exchange. This means that in a boom market, investor demand for all stocks (even the stocks of weak and loss-making companies) has increased, which in turn raises prices and, consequently, returns all stocks. Conversely, in a recession condition, investor demand for all stocks (even of profitable stocks and strong companies) decreases, which reduces the price of these stocks and thus their returns. This finding is consistent with the findings of Huang and Salmon (2009) and (2013). In addition, we found in this study that the impact of stocks with large and small beta coefficients on market returns is not the same. This means that as investors become more affected by market returns, the gap between stock returns with high beta and stocks with low beta increases. In other words, stocks with lower beta coefficients are more affected by market returns than stocks with high beta coefficients. This finding is also consistent with the results of Huang and Salmon (2009) and (2013).

In this study, the effect of investors' perception of the market on the price of individual securities in the Tehran Stock Exchange was examined. We found that investors' sense of the market influences their investment decisions. Being influenced by market performance means that investors in their investment decisions ignore the impact of fundamental variables on the price of securities and pay more attention to the overall performance of the market. Considering the general market trend and ignoring the main variables affecting the company's profitability leads to the formation of the phenomenon of herd behavior. This phenomenon is more visible in the case of small beta stocks. It is obvious that ignoring the fundamental variables can lead to unequilibrium in market and ultimately market inefficiency. Encouraging to indirect investment, such as mutual funds, can greatly prevent such undesirable phenomenon. Introducing with financial analysis in trading can also prevent such phenomena in the market.

The purpose of this research is to investigate the relationship between the interest rate, exchange rate and herding behavior in Tehran Stock Exchange. This research is applied to the target and its statistical society includes all companies accepted in Tehran Stock Exchange. The studied period is 2012 to 2016 and the sample is 2055 daily views. To test the hypothesis of the research, regression method of least squares was used. The findings showed that there is a positive and significant relationship between exchange rate and interest rate with herding behavior in all cases of daily and weekly and all levels of 1%, 5%, and 10%. Also, the effect of interest rates and exchange rates on herding behavior is higher in the more limited periods (daily or weekly) and at the lower levels (1%, 5%, and 10%), and with increasing time intervals and disclosure, this herding is reduced.

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 dont 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.

In this paper following Lakonishok (1992) and Sias (2004), we examine the presence of herding behavior among active institutional investors, test the presence of momentum strategy (as a determiner of herding behavior) and the correlation between herding behavior and weekly, monthly and quarterly stock return, using time series data (2006 – 2008) in the Tehran Stock Exchange. Our findings confirm the presence of herding behavior among the institutional investors and show that its intensity is higher than the developed countries, but they reject the presence of momentum strategy and its role as a determiner of herding behavior. Furthermore, the results show that the herding behavior of institutional investors does not affect the market return and has no correlation with the past and future returns.