The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
A Theory of Trading Volume
Abstract
A theory of trading volume is developed based on assumptions that market agents frequently revise their demand prices and randomly encounter potential trading partners. The model describes two distinct ways informational events affect trading volume. One is consistent with conjectures made by empirical researchers that investor disagreement leads to increased trading. But the observation of abnormal trading volume does not necessarily imply disagreement, and volume can increase even if investors interpret the information identically, if they also have had divergent prior expectations. Simulation tests support the model and are used to contrast the random‐pairing environment with costless market clearing. Volume is lower in the costly market, and volume increases caused by an informational event persist after the event period. This is consistent with existing empirical evidence and suggests that markets do not immediately clear all orders or that investors have demands to recontract.
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Cites
A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices
Clark, P. K. (1973) · Econometrica · doi:10.2307/1913889 · Cited by 2,779
The Information Content of Annual Earnings Announcements
Beaver, W. H. (1968) · Journal of Accounting Research · doi:10.2307/2490070 · Cited by 2,738
The Relation Between Price Changes and Trading Volume: A Survey
Karpoff, J. M. (1987) · The Journal of Financial and Quantitative Analysis · doi:10.2307/2330874 · Cited by 2,377
Self-citationAggregate Demand Management in Search Equilibrium
Diamond, P. A. (1982) · Journal of Political Economy · doi:10.1086/261099 · Cited by 1,932
Information Effects on the Bid‐Ask Spread
COPELAND, T. E., & GALAI, D. (1983) · The Journal of Finance · doi:10.1111/j.1540-6261.1983.tb03834.x · Cited by 1,868
Demsetz, H. (1968) · The Quarterly Journal of Economics · doi:10.2307/1882244 · Cited by 1,861
The Price Variability-Volume Relationship on Speculative Markets
Tauchen, G. E., & Pitts, M. (1983) · Econometrica · doi:10.2307/1912002 · Cited by 1,450
Information aggregation in a noisy rational expectations economy
Diamond, D. W., & Verrecchia, R. E. (1981) · Journal of Financial Economics · doi:10.1016/0304-405x(81)90026-x · Cited by 1,067
Epps, T. W., & Epps, M. L. (1976) · Econometrica · doi:10.2307/1912726 · Cited by 931
A MODEL OF ASSET TRADING UNDER THE ASSUMPTION OF SEQUENTIAL INFORMATION ARRIVAL*
Economics, T. E. C. (1976) · The Journal of Finance · doi:10.1111/j.1540-6261.1976.tb01966.x · Cited by 607
Cited by
Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards
Antweiler, W., & Frank, M. Z. (2004) · The Journal of Finance · doi:10.1111/j.1540-6261.2004.00662.x · Cited by 2,373
The Relation Between Price Changes and Trading Volume: A Survey
Karpoff, J. M. (1987) · The Journal of Financial and Quantitative Analysis · doi:10.2307/2330874 · Cited by 2,377
Self-citationTextual risk disclosures and investors’ risk perceptions
Kravet, T., & Muslu, V. (2013) · Review of Accounting Studies · doi:10.1007/s11142-013-9228-9 · Cited by 685
Determinants of the informativeness of analyst research
Frankel, R., Kothari, S. P., & Weber, J. (2006) · Journal of Accounting and Economics · doi:10.1016/j.jacceco.2005.10.004 · Cited by 631
Tweets and Trades: the Information Content of Stock Microblogs
Sprenger, T. O., Tumasjan, A., Sandner, P. G., & Welpe, I. M. (2014) · European Financial Management · doi:10.1111/j.1468-036x.2013.12007.x · Cited by 561
Metadata
- Authors
- KARPOFF, J. M.
- Venue
- The Journal of Finance
- Publisher
- Wiley
- Published
- 1986-12
- Volume
- 41
- Issue
- 5
- Pages
- 1069-1087
- ISSN
- 0022-1082 (ISSN-L)
- 1540-6261
- OpenAlex
- W2011263548
- Cited by
- 553
- References
- 20
- FWCI
- 7.75
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
