期刊名称：Discussion Paper Series / Universität Heidelberg, Department of Economics
出版年度：2016
出版社：Universität Heidelberg, Department of Economics
摘要：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 dep end on the ordering of variables in the forecasting mo del, 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 sto ck market returns and on a macroeconomic Bayesian vectorautoregressive model
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