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Cited by 373

The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.

Corporate Investment and Asset Price Dynamics: Implications for SEO Event Studies and Long‐Run Performance

Open access
CARLSON, MURRAY, FISHER, ADLAI, GIAMMARINO, RON·2006·The Journal of Finance

Abstract

We present a rational theory of SEOs that explains a pre‐issuance price run‐up, a negative announcement effect, and long‐run post‐issuance underperformance. When SEOs finance investment in a real options framework, expected returns decrease endogenously because growth options are converted into assets in place. Regardless of their risk, the new assets are less risky than the options they replace. Although both size and book‐to‐market effects are present, standard matching procedures fail to fully capture the dynamics of risk and expected return. We calibrate the model and show that it closely matches the primary features of SEO return dynamics.

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Crossref · 10.1111/j.1540-6261.2006.00865.x

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Metadata

Authors
CARLSON, M., FISHER, A., & GIAMMARINO, R.
Venue
The Journal of Finance
Publisher
Wiley
Published
2006-05-16
Volume
61
Issue
3
Pages
1009-1034
ISSN
  • 0022-1082 (ISSN-L)
  • 1540-6261
OpenAlex
W3121717661
Cited by
373
References
51
FWCI
34.63
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Corporate Investment and Asset Price Dynamics: Implications for SEO Event Studies and Long‐Run Performance. https://app.cochat.ai/papers/10.1111/j.1540-6261.2006.00865.x
The paper
CARLSON, M., FISHER, A., & GIAMMARINO, R. (2006). Corporate Investment and Asset Price Dynamics: Implications for SEO Event Studies and Long‐Run Performance. The Journal of Finance. https://doi.org/10.1111/j.1540-6261.2006.00865.x

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.