Year: 2019
Type: article
Abstract: The authors propose a novel approach to model investors' uncertainty using the conditional volatility of investors' sentiment. Working with weekly data on investor sentiment, 6 major U.S. stock indices, and alternative measures of uncertainty, they run various tests to validate the proposed measure. The estimates show that investors' uncertainty is greater during economic downturns, and it is linked with lower investors' sentiment. In addition, the results support the existence of a positive conditional correlation between sentiment and returns. This positive spillover between sentiment and returns is interpreted as a positive link between investors' uncertainty and market risk. The authors also find that investors’ uncertainty and market risk are strongly driven by their lagged values. The authors’ measure consistently captures periods of high uncertainty as shown by a positive and highly statistically significant correlation with other existing measures of uncertainty.
Source: Journal of Behavioral Finance
Authors: Diego Escobari, Mohammad Jafarinejad
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2805284471