Consistent Estimation of Pricing Kernels from Noisy Price Data

arXivmath/0310223MaRDI QIDQ6473245

Vladislav Kargin

Publication date: 15 October 2003

Abstract: If pricing kernels are assumed non-negative then the inverse problem of finding the pricing kernel is well-posed. The constrained least squares method provides a consistent estimate of the pricing kernel. When the data are limited, a new method is suggested: relaxed maximization of the relative entropy. This estimator is also consistent. Keywords: $epsilon$-entropy, non-parametric estimation, pricing kernel, inverse problems.

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Inverse problems for integral equations (45Q05) Numerical solution to inverse problems in abstract spaces (65J22)

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