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Cited by 660

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

A Unified Theory of Tobin's q, Corporate Investment, Financing, and Risk Management

Open access
BOLTON, PATRICK, CHEN, HUI, WANG, NENG·2011·The Journal of Finance
DOI 10.1111/j.1540-6261.2011.01681.x
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Abstract

We propose a model of dynamic investment, financing, and risk management for financially constrained firms. The model highlights the central importance of the endogenous marginal value of liquidity (cash and credit line) for corporate decisions. Our three main results are: (1) investment depends on the ratio of marginal q to the marginal value of liquidity, and the relation between investment and marginal q changes with the marginal source of funding; (2) optimal external financing and payout are characterized by an endogenous double‐barrier policy for the firm's cash‐capital ratio; and (3) liquidity management and derivatives hedging are complementary risk management tools.

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Crossref · 10.1111/j.1540-6261.2011.01681.x

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Metadata

Authors
BOLTON, P., CHEN, H., & WANG, N.
Venue
The Journal of Finance
Publisher
Wiley
Published
2011-09-21
Volume
66
Issue
5
Pages
1545-1578
ISSN
  • 0022-1082 (ISSN-L)
  • 1540-6261
DOI
10.1111/j.1540-6261.2011.01681.x
OpenAlex
W3021945653
Cited by
660
References
4
FWCI
120.13
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: A Unified Theory of Tobin's q, Corporate Investment, Financing, and Risk Management. https://app.cochat.ai/papers/10.1111/j.1540-6261.2011.01681.x
The paper
BOLTON, P., CHEN, H., & WANG, N. (2011). A Unified Theory of Tobin's q, Corporate Investment, Financing, and Risk Management. The Journal of Finance. https://doi.org/10.1111/j.1540-6261.2011.01681.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.