Computational Algorithms for Vertical Complementarity Arising in Finance
Berç Rustem (),
Tetsuya Noguchi () and
Michael Selby ()
Additional contact information
Berç Rustem: Imperial College
Tetsuya Noguchi: Imperial College
Michael Selby: Imperial College
No 931, Computing in Economics and Finance 1999 from Society for Computational Economics
Abstract:
We consider efficient computational algorithms for vertical complementarity problems. Vertical complementarity represents the equilibrium relationship among functions such that min (F1(x),...,Fm(x))=0 . This form is more general than the ordinary complementarity relationship, min (x, F(x))=0 . We consider an application in finance in terms of an option-hedging problem under transaction costs formulated as a singular stochastic control problem. This is expressed as a quasi-variational inequality. It is fully nonlinear and non-differentiable and belongs to a class of multi-dimensional free boundary problems equivalent to a vertical complementarity problem. In order to solve the quasi-variational inequality, alternative formulations are investigated. In addition, efficient numerical schemes are considered to provide a numerical solution.
Date: 1999-03-01
New Economics Papers: this item is included in nep-fin
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.doc.ic.ac.uk/~tn4 main text (text/html)
Our link check indicates that this URL is bad, the error code is: 404 Not Found (http://www.doc.ic.ac.uk/~tn4 [302 Found]--> http://www.doc.ic.ac.uk/~tn4/)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:sce:scecf9:931
Access Statistics for this paper
More papers in Computing in Economics and Finance 1999 from Society for Computational Economics CEF99, Boston College, Department of Economics, Chestnut Hill MA 02467 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().