Assessment of the Measuring Stock Market Investor Sentiment

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. Surveys take into account the psychological dimension of
individuals (optimism, pessimism and neutrality) in accordance with their socioeconomic
characteristics. 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 trader’s models. Finally, we
find that our composite index has a better predictive ability than the alternative sentiment measures
largely used in the literature.