Troster, Victor and Wied, Dominik . A specification test for dynamic conditional distribution models with function-valued parameters. Econom. Rev.. PHILADELPHIA: TAYLOR & FRANCIS INC. ISSN 1532-4168

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Abstract

This paper proposes a practical and consistent specification test of conditional distribution models for dependent data in a general setting. Our approach covers conditional distribution models indexed by function-valued parameters, allowing for a wide range of useful models for risk management and forecasting, such as the quantile autoregressive model, the CAViaR model, and the distributional regression model. The new specification test (i) is valid for general linear and nonlinear conditional quantile models under dependent data, (ii) allows for dynamic misspecification of the past information set, (iii) is consistent against fixed alternatives, and (iv) has nontrivial power against Pitman deviations from the null hypothesis. As the test statistic is non-pivotal, we propose and theoretically justify a subsampling approach to obtain valid inference. Finally, we illustrate the applicability of our approach by analyzing models of the returns distribution and Value-at-Risk (VaR) of two major stock indexes.

Item Type: Journal Article
Creators:
CreatorsEmailORCIDORCID Put Code
Troster, VictorUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Wied, DominikUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
URN: urn:nbn:de:hbz:38-333863
DOI: 10.1080/07474938.2020.1761151
Journal or Publication Title: Econom. Rev.
Publisher: TAYLOR & FRANCIS INC
Place of Publication: PHILADELPHIA
ISSN: 1532-4168
Language: English
Faculty: Unspecified
Divisions: Unspecified
Subjects: no entry
Uncontrolled Keywords:
KeywordsLanguage
VALUE-AT-RISK; GOODNESS-OF-FIT; REGRESSION-MODELS; CONSISTENT TEST; MOMENT TESTS; BOOTSTRAP; INFERENCE; VOLATILITY; CAVIARMultiple languages
Economics; Mathematics, Interdisciplinary Applications; Social Sciences, Mathematical Methods; Statistics & ProbabilityMultiple languages
URI: http://kups.ub.uni-koeln.de/id/eprint/33386

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