مطالب

The investment decisions of managers of investment funds (especially equity investment funds) have an impression on the returns of individuals who have deposited their capital in these funds. Therefore, the issue of evaluating the performance of investment funds and their managers is imperative for investors. The research aims to investigate the effect of cross-sectional alpha dispersion on investors' evaluation of the performance of investment funds. We extract data regarding 31 equity investment funds from 2012 till 2022 and calculate the interquartile ratio of Jensen's alpha called "IQR" and "Performance-Flow Sensitivity" along with control variables. Then, the hypothesis test model was fitted using the multivariate regression analysis using the Generalized Least Squares method. Empirical findings show a negative and significant connection between the alpha dispersion of investment funds and performance-flow sensitivity. Based on the results, one credit increase in the standard deviation of alpha dispersion leads to a decrease of about 0.4% in the ratio of performance-flow sensitivity. Environments with high alpha dispersion of investment funds will targeted by unskilled managers to introduce themselves as successful and skilled managers to investors and mislead them. Therefore, when the alpha of investment funds has a higher dispersion, the type I error possibility investors will face increases. Individuals may consider an inefficient manager to be competent and skilled. We will provide some suggestions in this regard.

Herd behavior, the tendency of individuals to mimic the actions of a larger group, significantly impacts capital markets by influencing stock prices, market liquidity, and overall market stability. This phenomenon has garnered significant attention in financial studies due to its implications for both institutional and individual investors, contributing to increased market volatility and potential crashes. Various methodologies have been developed to assess herd behavior, revealing its presence across diverse market conditions, including periods of high distress and volatility. This study examines macro herding in the Tehran Stock Exchange from March 2016 to February 2024, using weekly asset returns to measure herd behavior among listed companies. For the first time in Iran, we employ the TV method to calculate herding. The TV method offers two primary advantages: it is adept at identifying macro herding because it captures the collective trading direction of investors, and it operates independently of asset pricing models, minimizing biases associated with those models. Focusing on the collective trading direction, we aim to detect significant deviations in stock price movements indicative of herd behavior. Our findings indicate that herd behavior is more pronounced during extreme market conditions, both positive and negative, with a particularly notable increase during periods of negative market returns. This study provides insights into the dynamics of investor behavior in the Tehran Stock Exchange, highlighting the importance of monitoring such behavior to mitigate its potential adverse effects on market stability.