Nearest comoment estimation with unobserved factors

Kris Boudt, Dries Cornilly and Tim Verdonck

Journal of Econometrics, 2020, vol. 217, issue 2, 381-397

Abstract: We propose a minimum distance estimator for the higher-order comoments of a multivariate distribution exhibiting a lower dimensional latent factor structure. We derive the influence function of the proposed estimator and prove its consistency and asymptotic normality. The simulation study confirms the large gains in accuracy compared to the traditional sample comoments. The empirical usefulness of the novel framework is shown in applications to portfolio allocation under non-Gaussian objective functions and to the extraction of factor loadings in a dataset with mental ability scores.

Keywords: Higher-order multivariate moments; Latent factor model; Minimum distance estimation; Risk assessment; Structural equation modelling (search for similar items in EconPapers)
JEL-codes: C10 C13 C51 (search for similar items in EconPapers)
Date: 2020
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Related works:
Working Paper: NEAREST COMOMENT ESTIMATION WITH UNOBSERVED FACTORS (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:217:y:2020:i:2:p:381-397

DOI: 10.1016/j.jeconom.2019.12.009

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