Five Facts about Beliefs and Portfolios
By Stefano Giglio, Matteo Maggiori, Johannes Stroebel, Stephen Utkus. The American Economic Review, 2019
162 citations recorded by the source corpus.
We study a newly designed survey administered to a large panel of wealthy retail investors. The survey elicits beliefs that are important for macroeconomics and finance, and matches respondents with administrative data on their portfolio composition, their trading activity, and their login behavior. We establish five facts inthese data. (i) Beliefs are reflected in portfolio allocations. The sensitivity of portfolios to beliefs is small on average, but varies significantly with investor wealth, attention, trading frequency, and confidence. (ii) Belief changes do not predict when investors trade, but conditional on trading, they affect both the direction and the magnitude of trades. (iii) Beliefs are mostly characterized by large and persistent individual heterogeneity. Demographic characteristics explain only asmall part of why some individuals are optimistic and some are pessimistic. (iv) Expected cash flow growth and expected returns are positively related, both within and across investors. (v) Expected returns and the subjective probability of rare disasters are negatively related, both within and across investors. These five facts provide useful guidance for the design of macro-finance models. (JEL D83, E23, G11, G12, G41, G51)
View Paper: https://www.semanticscholar.org/paper/26271d9ab41c02694e20b7e23dbd624844d9a9c6
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Citations in the corpus
- Designing Information Provision Experiments (2020, background): “For instance, Giglio et al. (2021) apply such an IV approach in the context of survey expectations about stock returns, using both point beliefs and subjective probability distributions.”
- Extrapolative beliefs in the cross-section: What can we learn from the crowds? (2020, unknown): “Our paper adds to a literature that uses survey data to study investor beliefs ( Piazzesi and Schneider, 2009 ; Amromin and Sharpe, 2013 ; Greenwood and Shleifer, 2014 ; Koijen et al., 2015 ; Kuchler and Zafar, 2019 ; Giglio et al., 2020 ; Liu et al., 2020 ).”