Curved Gaussian Models with Application to
Modeling Currency Exchange Rates.
Juan Lin Peter Dayan
In YS Abu-Mostafa, B LeBaron, AW Lo & AS Weigend, editors,
Computational Finance 99. Cambridge, MA: MIT Press.
Abstract
Gaussian distributions lie at the heart of popular tools for capturing
structure in high dimensional data. Standard techniques employ as
models arbitrary linear transformations of spherical
Gaussians. In this paper, we present a simple extension to a class
of non-linear, volume-preserving transformations which provides an
efficient local description of curvature. The resulting
generalized Gaussian models give a simple statistical tool for
measuring deviations from multivariate Gaussian
distributions. Remarkably, there is a computationally efficient,
analytic solution for fitting the parameters of the non-linear
models. The power of this approach is demonstrated in a curvature
analysis of the Asian foreign exchange market.
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