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 :
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