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We show that name-induced stereotypes affect the investment choices of U.S. mutual fund investors. Managers with foreign-sounding names have about 10% lower annual fund flows and this effect is stronger among funds with investor clienteles more likely to be suspicious of foreigners. Foreign-name...
Persistent link: https://www.econbiz.de/10013037533
Using firm-level ESG news indices, we examine whether active mutual fund managers skillfully integrate material ESG information into their portfolio decisions. We find firm-level ESG news affects mutual fund holdings. Fund managers incorporate material ESG news to cater to investor demand and...
Persistent link: https://www.econbiz.de/10013235253
Using data from a new field experiment in South Korea, we study how information from virtual communities such as stock message boards influences investors' trading decisions and investment performance. Motivated by recent studies in psychology, we conjecture that investors would use message...
Persistent link: https://www.econbiz.de/10013141138
This study investigates whether retail and institutional investors concentrate their trading among certain stock categories (i.e., habitats) and whether their trading activities generate return comovements among stocks within those habitats. Our results indicate that both retail and...
Persistent link: https://www.econbiz.de/10013151103
This paper examines whether sell-side equity analysts use labor market information, as reflected in job postings and corporate layoffs, to improve the quality of their earnings forecasts. We posit that labor market activities contain useful incremental information about the related firm and the...
Persistent link: https://www.econbiz.de/10014362411
This paper examines the relation between equity portfolio diversification choices of individual investors and stock returns. Using a six-year panel (1991-96) of individual investors, I find that stocks with less diversified individual investor clientele earn higher returns. A zero cost portfolio...
Persistent link: https://www.econbiz.de/10014236135
Using machine learning methods, we develop a new measure of aggregate analyst sentiment. We first train analyst-specific neural network (NN) models that capture each analyst's common biases across firms. Using NN model outputs, we decompose the forecast errors of individual analysts into...
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