Evaluating Density Forecasts via the Copula Approach
Xiaohong Chen () and
Yanqin Fan ()
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Yanqin Fan: Department of Ecomomics, Vanderbilt University
No 225, Vanderbilt University Department of Economics Working Papers from Vanderbilt University Department of Economics
In this paper, we develop a general approach for constructing simple tests for the correct density forecasts, or equivalently, for i.i.d. uniformity of appropriately transformed random variables. It is based on nesting a series of i.i.d. uniform random variables into a class of copula-based stationary Markov processes. As such, it can be used to test for i.i.d. uniformity against alternative processes that exhibit a wide variety of marginal properties and temporal dependence properties, including skewed and fat-tailed marginal distributions, asymmetric dependence, and positive tail dependence. In addition, we develop tests for the dependence structure of the forecasting model that are robust to possible misspecification of the marginal distribution.
Keywords: Density forecasts; Gaussian copula; probability integral transform; nonlinear time series (search for similar items in EconPapers)
JEL-codes: C22 C52 C53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ets
Date: 2002-10, Revised 2003-09
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http://www.accessecon.com/pubs/VUECON/vu02-w25R.pdf Revised version, 2003 (application/pdf)
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Persistent link: https://EconPapers.repec.org/RePEc:van:wpaper:0225
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