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Information Journal Paper

Title

Investors' Sentiment of Market Return and its Effect on Herd Behavior Formation with Beta Herding Approach

Pages

  87-100

Abstract

 Objective: 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? Method: 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 β imt s and β imt. (Huang and Salmon, 2009): β imt s = β imt − hmt(β imt − 1) Which β imt is the equilibrium beta and β imt is the biased beta. The above relationship can be rewritten as follows: β imt s − β imt = 𝐶 +hmt(β imt − 1) + ϵ t+h The significance of hmt 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: rlow, t+h β β + ϵ t+h In above equation, the dependent variable is difference between low beta portfolio return (rlow, t+h β − rhigh, t+h ∗ = c0+c1Hmt ) with high beta portfolio return (rhigh, t+h β 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 c1 as the coefficient of Hmt ∗ ) and herd behavior criterion Hmt ∗ (crosssectional deviation of estimated betas (bimt s ) in above relation means that stocks with high and low Beta Coefficient react the same to market returns. Conversely, positive and significant c1 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 Hmt ∗ as a measure of monthly herd behavior is calculated by deviating from the standard bimt s according to the following equation (Huang and Salmon, 2009): 2 ∗ Hmt = 1 Nt 𝑠 Nt ∑ (𝑏 𝑖 𝑚 𝑡 − 1) i=1 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. Results: 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). Conclusion: 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.

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    APA: Copy

    Golarzi, Gholamhossein, & Badidast, Edriss. (2022). Investors' Sentiment of Market Return and its Effect on Herd Behavior Formation with Beta Herding Approach. JOURNAL OF DEVELOPMENT AND CAPITAL, 7(1 (12) ), 87-100. SID. https://sid.ir/paper/966122/en

    Vancouver: Copy

    Golarzi Gholamhossein, Badidast Edriss. Investors' Sentiment of Market Return and its Effect on Herd Behavior Formation with Beta Herding Approach. JOURNAL OF DEVELOPMENT AND CAPITAL[Internet]. 2022;7(1 (12) ):87-100. Available from: https://sid.ir/paper/966122/en

    IEEE: Copy

    Gholamhossein Golarzi, and Edriss Badidast, “Investors' Sentiment of Market Return and its Effect on Herd Behavior Formation with Beta Herding Approach,” JOURNAL OF DEVELOPMENT AND CAPITAL, vol. 7, no. 1 (12) , pp. 87–100, 2022, [Online]. Available: https://sid.ir/paper/966122/en

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