Option pricing by mathematical programming

Sjur Flåm

No 08/07, Working Papers in Economics from University of Bergen, Department of Economics

Abstract: Financial options typically incorporate times of exercise. Alternatively, they embody set-up costs or indivisibilities. Such features lead to planning problems with integer decision variables. Provided the sample space be finite, it is shown here that integrality constraints can often be relaxed. In fact, simple mathematical programming, aimed at arbitrage or replication, may find optimal exercise, and bound or identify option prices. When the asset market is incomplete, the bounds stem from nonlinear pricing functionals.

Keywords: asset pricing; arbitrage; options; finite sample space; scenario tree; equivalent martingale measures; bid-ask intervals; incomplete market; linear programming; combinatorial optimization; totally unimodular matrices. (search for similar items in EconPapers)
JEL-codes: C61 C62 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2007-07-10
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Related works:
Working Paper: Option Pricing by Mathematical Programming (2007)
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