The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Stock Market Overreactions to Bad News in Good Times: A Rational Expectations Equilibrium Model
Abstract
This article presents a dynamic, rational expectations equilibrium model of asset prices where the drift of fundamentals (dividends) shifts between two unobservable states at random times. I show that in equilibrium, investors' willingness to hedge against changes in their own “uncertainty” on the true state makes stock prices overreact to bad news in good times and underreact to good news in bad times. I then show that this model is better able than conventional models with no regime shifts to explain features of stock returns, including volatility clustering, “leverage effects,” excess volatility, and time-varying expected returns.
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In the citing paper
“First, humaninvestors might only partially assimilate the textual information of good news during economic downturns. Related to this hypothesis, Veronesi (1999) illustrates how market responses to news can vary with the business cycle, notably showing an underreaction to good news in adverse economic times.”
From ChatGPT and Deepseek: Can They Predict the Stock Market and Macroeconomy? (2025) · cites this paper as Veronesi (1999)
In the citing paper
“indicating that the return predictability of 𝑁𝑅 𝐺 𝑡 is markedly more substantial during periods of economic downturns”
From ChatGPT and Deepseek: Can They Predict the Stock Market and Macroeconomy? (2025) · cites this paper as Veronesi (1999)
Citations
Cites
By Force of Habit: A Consumption‐Based Explanation of Aggregate Stock Market Behavior
Campbell, J. Y., & Cochrane, J. H. (1999) · Journal of Political Economy · doi:10.1086/250059 · Cited by 5,210
Research works printed but not linked: 24
- Birkoff G. Rota G. C. , 1989, Ordinary Differential Equations, Wiley, New York.
- 10.1111/0022-1082.00090 · DOI
- Black F. , 1976, “Studies of Stock, Price Volatility Changes,” Proceedings of the 1976 meetings of the Business and Economics Statistics Section, American Statistical Association.
- 10.1016/0304-4076(92)90064-X · DOI
- Campbell J. Y. , 1997, “Asset Prices, Consumption and the Business Cycle,” forthcoming in Taylor J. B. Woodford M. (eds.), The Handbook of Macroeconomics, North Holland, Amsterdam.
- 10.1016/0304-405X(92)90037-X · DOI
- 10.2307/2297810 · DOI
- Cox J. Ingersoll J. Ross S. , 1985, “An Intertemporal General Equilibrium Model of Asset Prices,” Econometrica, 53. · DOI
- 10.2307/2331232 · DOI
- Detemple J. B. , 1986, “Asset Pricing in a Production Economy with Incomplete Information,” Journal of Finance, 41. · DOI
- Detemple J. B. , 1991, “Further Results on Asset Pricing with Incomplete Information,” Journal of Economic Dynamics and Control, 15. · DOI
- 10.1016/0304-405X(87)90026-2 · DOI
- Gennotte G. , 1986, “Optimal Portfolio Choice Under Incomplete Information,” Journal of Finance, 41. · DOI
- Glosten, 1993, “On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks,”, Journal of Finance, 58, 1779, 10.1111/j.1540-6261.1993.tb05128.x · DOI
- 10.2307/1912559 · DOI
- Karlin S. Taylor H. M. , 1975, A First Course in Stochastic Processes, Academic Press, New York. · DOI
- Liptser R. S. Shiryayev A. N. , 1977, Statistics of Random Processes: I, II, Springer-Verlag, New York. · DOI
- 10.2307/1913811 · DOI
- Merton, 1980, “On Estimating the Expected Return on the Market: an Exploratory Investigation,”, Journal of Financial Economics, 8, 326, 10.1016/0304-405X(80)90007-0 · DOI
- 10.2307/2328636 · DOI
- Shiller, 1984, “Stock Price and Social Dynamics,”, Brookings Papers in Economic Activity, 2, 457, 10.2307/2534436 · DOI
- Veronesi P. , 1997, “Stock Market Volatility in Regime Shift Models,” PhD. dissertation, Harvard University.
- Veronesi P. , 1999, “How Does Information Quality Affect Stock Returns? Results from a Dynamic Model of Learning,” CRSP Working Paper 462, University of Chicago; forthcoming in Journal of Finance.
- 10.2307/2298057 · DOI
Cited by
Sorted by citations
ChatGPT and Deepseek: Can They Predict the Stock Market and Macroeconomy?
Chen, J., Tang, G., Zhou, G., & Zhu, W. (2025) · arXiv · doi:10.48550/arxiv.2502.10008 · Cited by 6
Metadata
- Authors
- Veronesi, P.
- Affiliations
- University of Chicago (US)
- Corresponding author
- Veronesi, Pietro
- Venue
- Review of Financial Studies
- Publisher
- Oxford University Press (OUP)
- Published
- 1999-10
- Volume
- 12
- Issue
- 5
- Pages
- 975-1007
- ISSN
- 0893-9454 (ISSN-L)
- 1465-7368
- OpenAlex
- W2098347405
- Cited by
- 998
- References
- 1
- Citations by year
- 2026: 20 · 2025: 34 · 2024: 32 · 2023: 38 · 2022: 36 · 2021: 69 · 2020: 34 · 2019: 45 · 2018: 33 · 2017: 49 · 2016: 43 · 2015: 58 · 2014: 64 · 2013: 46 · 2012: 49
- FWCI
- 24.61
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Review of Financial Studies (publishedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Markets and Investment Strategies
- Social Sciences › Economics, Econometrics and Finance › Finance › Stochastic processes and financial applications
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economic theories and models
- Keywords
- stock market overreaction, rational expectations equilibrium, tipping points, hedging, excess volatility, volatility clustering, leverage effect, time-varying expected returns, asset pricing
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