Latent Affective Decision Drivers and Observable Investor Sentiment Price Outcomes
Year: 2012
Type: book
Abstract: There are two common methods to study investor sentiment. First, the top-down method, which measures investor sentiment outcomes using indirect exchange-level data and takes the origin of sentiment to be exogenous to the price formation process. Second, the bottomup approach, which directly measures sentiment at the investor level. While existing bottom-up approaches may be helpful in understanding investor decision making and market behavior, they do not measure specific investor decision drivers, and are thus not useful to develop precise theoretical conclusions about the nature of investor sentiment. Using the bottom-up approach, this paper identifies three latent investor decision drivers (Stock Market Attitude, Risk Attitude, and Risk Perception), and corroborates their role as key determinants of sentimental price processes. We extend recent work on the Affect hypothesis (Statman, Fisher, & Anginer, 2008), where the Affective content of stocks impacts their pricing. Using unique data from retail investors measuring both their Affective drivers and their risk behavior, we validate our latent decision drivers with top-down results using a conditional characteristics model. Our research implies that conceptual differences among existing investor sentiment measures help to explain the synchronization problem, where arbitrageurs have trouble coordinating their efforts to correct large stock price bubbles (Abreu & Brunnermeier, 2003). Policy implications support the use of a standardized reporting of latent Affective decision drivers of investor sentiment to synchronize arbitrageurs.
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2587311419