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Non-Euclidean Conditional Expectation and Filtering

Anastasis Kratsios and Cody B. Hyndman

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Abstract: A non-Euclidean generalization of conditional expectation is introduced and characterized as the minimizer of expected intrinsic squared-distance from a manifold-valued target. The computational tractable formulation expresses the non-convex optimization problem as transformations of Euclidean conditional expectation. This gives computationally tractable filtering equations for the dynamics of the intrinsic conditional expectation of a manifold-valued signal and is used to obtain accurate numerical forecasts of efficient portfolios by incorporating their geometric structure into the estimates.

New Economics Papers: this item is included in nep-big, nep-cmp and nep-ecm
Date: 2017-10, Revised 2018-09
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