DocumentCode
924219
Title
Valuation of American options via basis functions
Author
Lai, Tze Leung ; Wong, Samuel Po-Shing
Author_Institution
Dept. of Stat., Stanford Univ., CA, USA
Volume
49
Issue
3
fYear
2004
fDate
3/1/2004 12:00:00 AM
Firstpage
374
Lastpage
385
Abstract
After a brief review of recent developments in the pricing and hedging of American options, this paper modifies the basis function approach to adaptive control and neuro-dynamic programming, and applies it to develop: 1) nonparametric pricing formulas for actively traded American options and 2) simulation-based optimization strategies for complex over-the-counter options, whose optimal stopping problems are prohibitively difficult to solve numerically by standard backward induction algorithms because of the curse of dimensionality. An important issue in this approach is the choice of basis functions, for which some guidelines and their underlying theory are provided.
Keywords
adaptive control; dynamic programming; function approximation; neural nets; pricing; stock markets; American options valuation; actively traded American options; adaptive control; basis functions; complex over-the-counter options; function approximation; neurodynamic programming; nonparametric pricing formulas; optimal stopping problems; option pricing; simulation-based optimization strategies; Adaptive control; Cost accounting; Councils; Finance; Functional programming; Guidelines; Multidimensional systems; Pricing; Spline; Standards development;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/TAC.2004.824466
Filename
1273637
Link To Document