Staff Reports
Nonparametric Pricing of Multivariate Contingent Claims
March 2003 Number 162
JEL classification: G13, C14

Author: Joshua V. Rosenberg

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.

Available only in PDFPDF40 pages / 1,169 kb

For a published version of this report, see Joshua V. Rosenberg, "Non-parametric Pricing of Multivariate Contingent Claims," Journal of Derivatives 10, no. 3 (spring 2003): 9-26.

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