2003
DOI: 10.1002/fut.10061
|View full text |Cite
|
Sign up to set email alerts
|

On the optimal mix of corporate hedging instruments: Linear versus nonlinear derivatives

Abstract: We examine how corporations should choose their optimal mix of linear and nonlinear derivatives. We present a model in which a firm facing both quantity (output) and price (market) risk maximizes its expected profits when subjected to financial distress costs. The optimal hedging position generally is comprised of linear contracts, but as the levels of quantity and price-risk increase, the use of linear contracts will decline due to the risks associated with overhedging. At the same time, a substitution effect… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

3
15
0

Year Published

2010
2010
2020
2020

Publication Types

Select...
4
1

Relationship

0
5

Authors

Journals

citations
Cited by 25 publications
(18 citation statements)
references
References 23 publications
3
15
0
Order By: Relevance
“…This theorem supports results obtained in Brown and Toft (2002) and Gay et al (2003). These authors considered long commodity case and assumed that µ = 0.…”
Section: Risk Minimizationsupporting
confidence: 89%
See 4 more Smart Citations
“…This theorem supports results obtained in Brown and Toft (2002) and Gay et al (2003). These authors considered long commodity case and assumed that µ = 0.…”
Section: Risk Minimizationsupporting
confidence: 89%
“…It is important to note that although the distributions and objective functions in Brown and Toft (2002), Gay et al (2003) and this paper are different the conclusions are strikingly similar. This reassures that the results depend on the general features of distribution (randomness of price and quantity and their correlation) and objective function (penalization only of lower tail of cash-flow distribution) and do not depend on specifics of the problem.…”
Section: Risk Minimizationsupporting
confidence: 53%
See 3 more Smart Citations