A new omnibus test of fit based on a characterisation of the uniform distribution
Bruno Ebner, Shawn Liebenberg, Jaco Visagie

TL;DR
This paper introduces a new omnibus goodness-of-fit test based on characterising the uniform distribution, with strong theoretical backing, quick convergence, and competitive power in various distribution testing scenarios, including financial data.
Contribution
The paper proposes a novel goodness-of-fit test based on a uniform distribution characterisation, with detailed asymptotic theory and demonstrated effectiveness in simple and composite hypotheses.
Findings
Test converges quickly to asymptotic distribution
Test is consistent against all fixed alternatives
Competitive power in finite samples across multiple distributions
Abstract
In this paper, we revisit the classical goodness-of-fit problems for univariate distributions; we propose a new testing procedure based on a characterisation of the uniform distribution. Asymptotic theory for the simple hypothesis case is provided in a Hilbert-Space setting, including the asymptotic null distribution as well as values for the first four cumulants of this distribution, which are used to fit a Pearson system of distributions as an approximation to the limit distribution. Numerical results indicate that the null distribution of the test converges quickly to its asymptotic distribution, making the critical values obtained using the Pearson system particularly useful. Consistency of the test is shown against any fixed alternative distribution and we derive the limiting behaviour under fixed alternatives with an application to power approximation. We demonstrate the…
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Taxonomy
TopicsFinancial Risk and Volatility Modeling · Statistical Distribution Estimation and Applications · Statistical Methods and Inference
