Valuing American options using fast recursive projections
Antonio Cosma (),
Stefano Galluccio and
Olivier Scaillet
No unige:41856, Working Papers from University of Geneva, Geneva School of Economics and Management
Abstract:
This paper introduces a new numerical option pricing method by fast recursive projections. The projection step consists in representing the payoff and the state price density with a fast discrete transform based on a simple grid sampling. The recursive step consists in transmitting coefficients of the representation from one date to the previous one by an explicit recursion formula. We characterize the convergence rate of the computed option price. Numerical illustrations with different American and Bermudan payoffs with discrete dividend paying stocks in the Black-Scholes and Heston models show that the method is fast, accurate, and general.
Keywords: Option pricing; American option; Bermudan option; Discrete transform; Discrete dividend paying stock; Numerical techniques (search for similar items in EconPapers)
JEL-codes: C63 G13 (search for similar items in EconPapers)
Pages: 46 p.
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://luniarchidoc5.unige.ch/archive-ouverte/arc ... e:41856/ATTACHMENT01
Our link check indicates that this URL is bad, the error code is: 404 Not Found
Related works:
Working Paper: Valuing American options using fast recursive projections (2016) 
Working Paper: Valuing American options using fast recursive projections (2015) 
Working Paper: Valuing American Options Using Fast Recursive Projections (2012) 
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:gnv:wpgsem:unige:41856
Access Statistics for this paper
More papers in Working Papers from University of Geneva, Geneva School of Economics and Management Contact information at EDIRC.
Bibliographic data for series maintained by Jean-Blaise Claivaz ().