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Order Invariant Evaluation of Multivariate Density Forecasts

Dovern, Jonas ; Manner, Hans

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Abstract

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.

Item Type: Working paper
Series Name: Discussion Paper Series, University of Heidelberg, Department of Economics
Volume: 0608
Place of Publication: Heidelberg
Date Deposited: 08 Mar 2016 09:03
Date: March 2016
Number of Pages: 41
Faculties / Institutes: The Faculty of Economics and Social Studies > Alfred-Weber-Institut for Economics
Subjects: 330 Economics
Uncontrolled Keywords: density calibration, goodness-of-fit test, predictive density, Rosenblatt transformation
Schriftenreihe ID: Discussion Paper Series / University of Heidelberg, Department of Economics
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