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Forecast Encompassing Tests for the Expected Shortfall

Timo Dimitriadis, Julie Schnaitmann

arXiv 13 Aug 2019 · Finance — Risk Management · publishedInternational Journal of Forecasting (2019) · 4 citations (OpenAlex)

arXiv:1908.04569 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We introduce new forecast encompassing tests for the risk measure Expected Shortfall (ES). The ES currently receives much attention through its introduction into the Basel III Accords, which stipulate its use as the primary market risk measure for the international banking regulation. We utilize joint loss functions for the pair ES and Value at Risk to set up three ES encompassing test variants. The tests are built on misspecification robust asymptotic theory and we investigate the finite sample properties of the tests in an extensive simulation study. We use the encompassing tests to illustrate the potential of forecast combination methods for different financial assets.

Citation extraction

57
references
201
in-text mentions
57
distinct cited
2
self-citations
14,006
main-text words

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Dimitriadis, T. and Bayer, S (2019) A joint quantile and expected shortfall regression framework self1.000124100%
2Bayer, S. and Dimitriadis, T (2020) Regression based expected shortfall backtesting self1.00094100%
3Fissler, T. and Ziegel, J. F (2016) Higher order elicitability and Osband's principle1.00094100%
4Basel Committee (2016) Minimum capital requirements for Market Risk1.00064100%
5Basel Committee (2017) Pillar 3 disclosure requirements – consolidated and enhanced framework1.00064100%
6Patton, A. J., Ziegel, J. F., and Chen, R (2019) Dynamic semiparametric models for expected shortfall (and value-at-risk)0.93823783%
7Giacomini, R. and Komunjer, I (2005) Evaluation and combination of conditional quantile forecasts0.90527674%
8Taylor, J. W (2019) Forecasting value at risk and expected shortfall using a semiparametric approach based on the asymmetric laplace distribution0.89911673%
9Clements, M. and Harvey, D (2009) Forecast combination and encompassing0.87462100%
10Clements, M. and Harvey, D (2010) Forecast encompassing tests and probability forecasts0.87462100%

Showing the top 10 of 57 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary0.986246
2The Efficiency Gap0.40511