Nearest comoment estimation with unobserved factors

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.

• Publication year

  2020

• Venue

  Journal of Econometrics

• Publication date

  2020-01-07

• Fields of study

  Mathematics, Economics, Political Science

• Identifiers
  DOI 10.1016/J.JECONOM.2019.12.009
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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