Measuring Stock Market Investor Sentiment

Abstract

Recently, investor sentiment measures have become one of the more widely examined areas in behavioral finance. A number of measures have been developed in the literature without having been fully validated, and therefore leaving in question which measure should be used for empirical exploration. The purpose of this study is to examine the relative performance of a number of popular measures in predicting stock returns and to test the relative efficacy of a hybrid approach. Using a panel of investor sentiment measures, we develop a new measure of sentiment which combines direct and indirect sentiment measures. Our results show that our composite sentiment index affects the returns of stocks hard to value and difficult to arbitrage consistent with the predictions of noise traders models. Finally, we find that our composite index has a better predictive ability than the alternative sentiment measures largely used in the literature.

Measurement of Investor Sentiment and Its Bi-Directional Contemporaneous and Lead–Lag Relationship with Returns: Evidence from Pakistan

“…The indicators of the indirect method have the advantage that these rely on financial theories and are generated by using financial data, which are mostly measured with reliability and are available in higher frequencies of time as well. However, financial data may capture expectations of the investor about price changes only and no other elements of attitudes of the investor [78]. Compared to survey-based direct measures and indirect measures, the measure derived from financial and economic attitudes based on daily internet search volume has various advantages.…”

COVID-19 pandemic and capital markets: the role of government responses

“…The literature on behavioral finance has extensively explored whether investor sentiment affects trading decisions, leads to irrational trading behavior, and affects stock prices (e.g., Baker and Wurgler 2006 ; Beer and Zouaoui 2012 ; Chau et al 2016 ; Cormier et al 2010 ; Fang and Peress 2009 ; He et al 2020 ; Hong and Stein 2007 , 1999 ; Kaniel et al 2008 ; Long et al 1990 ; Palomino 1996 ; Shleifer and Vishny 1997 ). Bollen et al ( 2011 ) find that investors’ trading behavior is directly shaped by their perceptions about future market development.…”

Volatility Forecasting of China Silver Futures: the Contributions of Chinese Investor Sentiment and CBOE Gold and Silver ETF Volatility Indices

“…Based on the paper written by [15], several indicators are used to construct CnSENT as they can better capture the investors' emotions. These indicators are stock high opening rate, stock growth rate, stock effective growth rate, stock limit up rate, stock limit up closing rate, quantity relative ratio, and stock turnover rate.…”