Title: Nonparametric pricing of multivariate contingent claims
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.