Author
Abstract
There is a trend in investment banking to unify pricing tools in a framework of partial differential equations. The Black-Scholes equation and its extensions are solved numerically with pde-based techniques (instead of rather heuristic techniques like Monte Carlo or Trees). The predominant numerical technique today is Finite Differences. This technique has been studied since L. Euler and is fairly easy to apply. A more modern technique, Finite Elements, can also be applied to solve the pdes. It offers some advantages: 1. The solution is a polynomial approximation to the entire domain. The method of Finite Differences supplies an approximate solution only to distinct points in the domain, so that interpolation becomes necessary. 2. There are several FE methods that supply Delta and Gamma as a by-product. The other Greeks can be computed in a slightly easier manner than with FD. 3. Irregular domains, which occur when knock-out barriers are applied to multi-asset options, can be solved easily since the elements can be adjusted to almost any domain. FD techniques, however, are designed to cover rectangular domains. 4. FD techniques for problems involving Neumann conditions are not straightforward to apply. FE methods, however, have no problems with Neumann conditions. Neumann conditions are easier to apply to financial problems since the behavior of the function at infinity has to be approximated. Approximating the function at infinity is normally harder than approximating its derivative. We will demonstrate these advantages with various exotic options (for instance, capped power calls, double barrier options on baskets, volatility models, and the like) and bond pricing models (Duffie/Kan, Sandmann/ Sondermann/ Miltersen). We also demonstrate how to use FE for nonlinear models arising through the incorporation of transactions costs and through passport options.
Suggested Citation
Juergen Topper, 1999.
"Finite Element Methods in Bond and Option Pricing,"
Computing in Economics and Finance 1999
131, Society for Computational Economics.
Handle:
RePEc:sce:scecf9:131
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sce:scecf9:131. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/sceeeea.html .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.