Year: 2012
Type: article
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.
Authors: Francisca Beer, Mohamed Zouaoui
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W2177130429