The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
A Rational Theory of Mutual Funds' Attention Allocation
Abstract
The question of whether and how mutual fund managers provide valuable services for their clients motivates one of the largest literatures in finance. One candidate explanation is that funds process information about future asset values and use that information to invest in high-valued assets. But formal theories are scarce because information choice models with many assets are difficult to solve as well as difficult to test. This paper tackles both problems by developing a new attention allocation model that uses the state of the business cycle to predict information choices, which in turn, predict observable patterns of portfolio investments and returns. The predictions about fund portfolios ’ covariance with payoff shocks, cross-fund portfolio and return dispersion, and their excess returns are all supported by the data. In turn, these findings offer new evidence that some investment managers have skill and that attention is allocated rationally.
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Cites
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Implications of rational inattention
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How Active Is Your Fund Manager? A New Measure That Predicts Performance
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Cited by
Do Investors Care about Carbon Risk?
Bolton, P., & Kacperczyk, M. (2021) · Journal of Financial Economics · doi:10.1016/j.jfineco.2021.05.008 · Cited by 3,380
Self-citationDisclosure processing costs, investors’ information choice, and equity market outcomes: A review
Blankespoor, E., deHaan, E., & Marinovic, I. (2020) · Journal of Accounting and Economics · doi:10.1016/j.jacceco.2020.101344 · Cited by 1,076
Mutual fund performance and flows during the COVID-19 crisis
Pástor, Ľ., & Vorsatz, M. B. (2020) · The Review of Asset Pricing Studies · doi:10.1093/rapstu/raaa015 · Cited by 319
Metadata
- Authors
- Kacperczyk, M., Van Nieuwerburgh, S., & Veldkamp, L.
- Venue
- Econometrica
- Publisher
- The Econometric Society
- Published
- 2016
- Volume
- 84
- Issue
- 2
- Pages
- 571-626
- ISSN
- 0012-9682 (ISSN-L)
- OpenAlex
- W2235026379
- Cited by
- 559
- References
- 31
- FWCI
- 71.58
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
