Investor Sentiments and Stock Returns: A Study on Noise Traders
Abstract
The concept of investor sentiments aims to access the interest of market players or their anticipation towards their investments. Investor sentiments hold a crucial role in trading, however, the task of measuring it is complex as it involves the quantification of emotions. Additionally, varying sentiments may exist among individual investors. Nevertheless, it is widely acknowledged that investor sentiments are integral element of stock market dynamics along with genuine explanatory power. Sentiments serve as ambiguous elements in economic activities, shaping investors' subjective outlook on future returns. Consequently, this influences their investment behavior, ultimately making a substantial impact on the market. This study aims to analyze the impact of investor sentiments on stock returns. This research is the first one to study investor sentiment proxies instead of a joint index with some novel proxies i.e. share mispricing, bond yield spread, and gold bullion in the context of Pakistan. This study uses panel data of 49 non-financial firms taken on quarterly basis from 2012-2019 covering 1467 observations of the unbalanced panel. The Generalized Least Squares model is used in the study for hypotheses testing. The results for all five hypotheses of investor sentiments’ proxies are accepted i.e. about gold bullion, survey data indicator, turnover and the two technical analysis indicators. Additionally, the findings are consistent with the literature studies conducted on the developed and developing economies. However, this study has some limitations, which can become part of future studies for having an in-depth analysis of investors’ sentiments in the Pakistan stock market. The policy implication of this study is for the policymakers to direct the policies in consideration of investors’ noise trading behavior by understanding the stock market biases.
Keywords: Investor sentiment, stock returns, noise traders, rational investors, gold, turnover, technical indicator
