Buchumschlag

Order invariant evaluation of multivariate density forecasts

We derive new tests for proper calibration of multivariate density forecasts based on Rosenblatt probability integral transforms. These tests have the advantage that they i) do not depend on the ordering of variables in the forecasting model, ii) are applicable to densities of arbitrary dimensions,...

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Bibliographische Detailangaben
Hauptverfasser: Dovern, Jonas (VerfasserIn) , Manner, Hans (VerfasserIn)
Dokumenttyp: Buch/Monographie Arbeitspapier
Sprache:Englisch
Veröffentlicht: Heidelberg University of Heidelberg, Department of Economics March 4, 2016
Schriftenreihe:Discussion paper series / Universität Heidelberg, Department of Economics No. 608
In: Discussion paper series (no. 608)

DOI:10.11588/heidok.00020376
Schlagworte:
Arbeitspapier
Graue Literatur
Online-Zugang:Resolving-System, kostenfrei, Volltext: http://nbn-resolving.de/urn:nbn:de:bsz:16-heidok-203762
Resolving-System, kostenfrei, Volltext: https://doi.org/10.11588/heidok.00020376
Resolving-System, kostenfrei, Volltext: http://hdl.handle.net/10419/162951
Verlag, kostenfrei, Volltext: http://www.ub.uni-heidelberg.de/archiv/20376
Volltext
Verfasserangaben:Jonas Dovern; Hans Manner
Beschreibung
Zusammenfassung:We derive new tests for proper calibration of multivariate density forecasts based on Rosenblatt probability integral transforms. These tests have the advantage that they i) do not depend on the ordering of variables in the forecasting model, ii) are applicable to densities of arbitrary dimensions, and iii) have superior power relative to existing approaches. We furthermore develop adjusted tests that allow for estimated parameters and, consequently, can be used as in-sample specification tests. We demonstrate the problems of existing tests and how our new approaches can overcome those using Monte Carlo Simulation as well as two applications based on multivariate GARCH-based models for stock market returns and on a macroeconomic Bayesian vectorautoregressive model.
Beschreibung:Online Resource
DOI:10.11588/heidok.00020376

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