Semi-parametric estimation of American option prices

  • Patrick Gagliardini
  • , Diego Ronchetti

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)
316 Downloads (Pure)

Abstract

We introduce a novel semi-parametric estimator of American option prices in discrete time. The specification is based on a parameterized stochastic discount factor and is nonparametric w.r.t. the historical dynamics of the Markovian state variables. The historical transition density estimator minimizes a distance built on the Kullback–Leibler divergence from a kernel transition density, subject to the no-arbitrage restrictions for a non-defaultable bond, the underlying asset and some American option prices. We use dynamic programming to make explicit the nonlinear restrictions on the Euclidean and functional parameters coming from option data. We study asymptotic and finite sample properties of the estimators
Original languageEnglish
Pages (from-to)57-82
Number of pages26
JournalJournal of Econometrics
Volume173
Issue number1
DOIs
Publication statusPublished - Mar-2013
Externally publishedYes

Keywords

  • American option; Kernel estimator; Semi-parametric estimation; Dynamic programming; Fréchet derivative

Fingerprint

Dive into the research topics of 'Semi-parametric estimation of American option prices'. Together they form a unique fingerprint.

Cite this