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Efficiently Weighted Estimation of Tail and Interquantile Expectations

Sander Barendse

Journal of Financial Econometrics2026https://doi.org/10.1093/jjfinec/nbag003article
AJG 3ABDC A*
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0.50

Abstract

Tail expectations have recently attracted much attention in economics for their ability to capture risk. We develop a semiparametric estimator for the joint estimation of (nonlinear) models of tail expectations with some tail quantile as the left or right threshold, and interquantile expectations, partial expectations between two thresholding quantiles. The joint estimator of these quantities can be used to test for heterogeneity in the conditional distribution, with special attention to distinct tail behavior. We derive efficient weights and asymptotic properties of the estimator for time-series data. The estimator does not require the specification of the conditional distribution, and its computation relies on standard techniques. In an empirical application in finance, we test for a disproportionate contribution of tail events to the average abnormal return of portfolio strategies.

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https://doi.org/https://doi.org/10.1093/jjfinec/nbag003

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@article{sander2026,
  title        = {{Efficiently Weighted Estimation of Tail and Interquantile Expectations}},
  author       = {Sander Barendse},
  journal      = {Journal of Financial Econometrics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1093/jjfinec/nbag003},
}

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Efficiently Weighted Estimation of Tail and Interquantile Expectations

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0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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