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Ambiguity, Risk, and Asset Returns in Continuous Time
Open accessAbstract
Models of utility in stochastic continuous–time settings typically assume that beliefs are represented by a probability measure, hence ruling out a priori any concern with ambiguity. This paper formulates a continuous–time intertemporal version of multiple–priors utility, where aversion to ambiguity is admissible. In a representative agent asset market setting, the model delivers restrictions on excess returns that admit interpretations reflecting a premium for risk and a separate premium for ambiguity.
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Citations
Cited by
Ambiguity, Information Quality, and Asset Pricing
EPSTEIN, L. G., & SCHNEIDER, M. (2008) · The Journal of Finance · doi:10.1111/j.1540-6261.2008.01314.x · Cited by 833
Self-citationHirshleifer, D. (2015) · Annual Review of Financial Economics · doi:10.1146/annurev-financial-092214-043752 · Cited by 497
Model Misspecification and Underdiversification
Uppal, R., & Wang, T. (2003) · The Journal of Finance · doi:10.1046/j.1540-6261.2003.00612.x · Cited by 474
Pricing Uncertainty Induced by Climate Change
Barnett, M., Brock, W., & Hansen, L. P. (2020) · The Review of Financial Studies · doi:10.1093/rfs/hhz144 · Cited by 467
Ambiguity, Learning, and Asset Returns
(2012) · Econometrica · doi:10.3982/ecta7618 · Cited by 404
Metadata
- Authors
- Chen, Z., & Epstein, L.
- Venue
- Econometrica
- Publisher
- The Econometric Society
- Published
- 2002-07
- Volume
- 70
- Issue
- 4
- Pages
- 1403-1443
- ISSN
- 0012-9682 (ISSN-L)
- 1468-0262
- OpenAlex
- W2138765659
- Cited by
- 1,072
- References
- 0
- FWCI
- 64.61
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Chen, Z., & Epstein, L. (2002). Ambiguity, Risk, and Asset Returns in Continuous Time. Econometrica. https://doi.org/10.1111/1468-0262.00337
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
