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Indices of quadratic programs over reproducing kernel Hilbert spaces for fun and profit

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arxiv 2412.18201 v1 pith:Y2SV7YK6 submitted 2024-12-24 math.OC math.CVmath.FAq-fin.PMq-fin.PR

classification math.OCmath.CVmath.FAq-fin.PMq-fin.PR
keywords optimalquadraticsometowardabstractallocatedallocationasset
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We give an abstract perspective on quadratic programming with an eye toward long portfolio theory geared toward explaining sparsity via maximum principles. Specifically, in optimal allocation problems, we see that support of an optimal distribution lies in a variety intersect a kind of distinguished boundary of a compact subspace to be allocated over. We demonstrate some of its intelligence by using it to solve mazes and interpret such behavior as the underlying space trying to understand some hypothetical platonic index for which the capital asset pricing model holds.

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  1. Positive-Allocation Companion Predictors for Nonlinear Dynamics and Their Finite-Difference Diagnostics

    math.DS 2026-07 conditional novelty 5.0 of 10

    A nonnegative, sum-to-one weighted average of past snapshots defines a companion predictor whose spectrum lies in the unit disk and includes 1 as an eigenvalue.

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