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Consistent Estimation of Pricing Kernels from Noisy Price Data

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  • Vladislav Kargin

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.

Suggested Citation

  • Vladislav Kargin, 2003. "Consistent Estimation of Pricing Kernels from Noisy Price Data," Papers math/0310223, arXiv.org.
    • Handle: RePEc:arx:papers:math/0310223
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    More about this item

    Keywords

    $epsilon$-entropy; non-parametric estimation; pricing kernel; inverse problems.;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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