Nonparametric pricing of multivariate contingent claims
By: Joshua V. Rosenberg.
Contributors: Federal Reserve Bank of New York.
Series: Staff reports ;; no. 162; Staff reports (Federal Reserve Bank of New York : Online) ;; no. 162.
Publisher: Federal Reserve Bank of New York
Published: 2003
Place of publication: [New York, N.Y.]
Language: eng
Format: Electronic resource
Description: "In this paper, I derive and implement a nonparametric, arbitrage-free technique for multivariate contingent claim (MVCC) pricing.  Using results from the method of copulas, I show that the multivariate risk-neutral density can be written as a product of marginal risk-neutral densities and a risk-neutral dependence function.  I then develop a pricing technique using nonparametrically estimated marginal risk-neutral densities (based on options data) and a nonparametric dependence function (based on historical return data).  By using nonparametric estimation, I avoid the pricing biases that result from incorrect parametric assumptions such as lognormality.  I apply this technique to estimate the joint risk-neutral density of euro-dollar and yen-dollar returns.  I compare the nonparametric risk-neutral density with density based on a lognormal dependence function and nonparametric marginals.  The nonparametric euro-yen risk-neutral density has greater volatility, skewness, and kurtosis than the density based on a lognormal dependence function.  In a comparison of pricing accuracy for euro-yen futures options, I find that the nonparametric model is superior to the lognormal model"--Federal Reserve Bank of New York web site.
Notes: Also available in print.
Includes bibliographical references.
Title from PDF file as viewed on 3/3/2005.
System requirements: Adobe Acrobat Reader.
Mode of access: World Wide Web.