Nearest Comoment Estimation With Unobserved Factors

Kris Boudt, Dries Cornilly, Tim Verdonck

Onderzoeksoutput: Article

4 Citaten (Scopus)


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 in uence 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.
Originele taal-2English
Pagina's (van-tot)381-397
Aantal pagina's17
TijdschriftJournal of Econometrics
Nummer van het tijdschrift2
StatusPublished - aug 2020


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