The Adaptive Mesh Model: A New Approach to Efficient Option Pricing

Stephen Figlewski and Bin Gao

New York University, Leonard N. Stern School Finance Department Working Paper Seires from New York University, Leonard N. Stern School of Business-

Abstract: Exact closed-form valuation equations for traded derivative securities are rare. Numerical approximation, most commonly with Binomial and Trinomial lattice models, gives exact valuation in the limit, but convergence is non-monotonic and often slow, due to 'distribution error' and 'truncation error.' This paper explains how truncation error arises and describes the Adaptive Mesh Model (AMM), a new approach that sharply reduces it by grafting one or more small sections of fine high-resolution lattice onto a tree with coarser time and price steps. Three different AMM structures are presented, one for pricing ordinary options, one for barrier options, and one for computing delta and gamma efficiently. The AMM approach can be adapted to a wide variety of contingent claims, yielding significant improvement in efficiency with very little increase in computational effort. For some common problems, including calculating delta, accuracy increases by several orders of magnitude relative to the standard models with no measurable increase in execution time at all.

Date: 1998-03-15
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Journal Article: The adaptive mesh model: a new approach to efficient option pricing (1999)
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:fth:nystfi:98-032

Access Statistics for this paper

More papers in New York University, Leonard N. Stern School Finance Department Working Paper Seires from New York University, Leonard N. Stern School of Business- U.S.A.; New York University, Leonard N. Stern School of Business, Department of Economics . 44 West 4th Street. New York, New York 10012-1126. Contact information at EDIRC.
Bibliographic data for series maintained by Thomas Krichel ().