Revista de la Academia de Estudios de Marketing

1528-2678

Abstracto

Psychology of Investment-Sentimental based Literature Review

Kanwal Nayan Kapil

Considering the market-based approach, the purpose of this paper is to do sentimental based literature review. gauged sentiment components have been studied to study the influence of sentiments on the Stock Market variables. Researchers have checked the significance of sentiment components in forecasting the the index return. In Indian context the index is CNX Nifty Index & Nifty returns. Researchers have tried to gauge the investor sentiments after separating the fundamental component from the proxies. There are several defined number of proxies used in previous literature. Out of which three proxies are quite popular. Firstly, OLS regression along with newey-west method has been used to capture the impact of sentiments present in proxies on the dependent variables . Researchers have studied how Sentiment Index is constructed with same three proxies, using Principal-Component Analysis, in order to remove idiosyncratic components, present in the proxies & to capture the common sentiment component present in proxies. In several studies newey-west method and Granger Causality test are conducted to check the influence of sentiment index on dependent variables and to study the nature of causality among them, respectively.Studies have found that constructing the sentiment index is a better way of gauging the common sentiments prevailing in the market as it doesn’t account for the idiosyncratic/proxy-specific components present in the proxy variables. And Granger Causality results depict the bi-directional causality among the dependent variables and sentiment index. Therefore, the sentiment index thus formed is capable of forecasting the dependent variables. Overall the researchers have utilized that sentiment component with two different approaches to study the impact of sentiments on stock market variables and deciding which of the two approaches, can serve the purpose more accurately.