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Evaluating Density Forecasts via the Copula Approach

Listed author(s):
  • Xiaohong Chen

    ()

    (Department of Economics, New York University)

  • Yanqin Fan

    ()

    (Department of Ecomomics, Vanderbilt University)

Registered author(s):

    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.

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    File URL: http://www.accessecon.com/pubs/VUECON/vu02-w25R.pdf
    File Function: Revised version, 2003
    Download Restriction: no

    Paper provided by Vanderbilt University Department of Economics in its series Vanderbilt University Department of Economics Working Papers with number 0225.

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    Date of creation: Oct 2002
    Date of revision: Sep 2003
    Handle: RePEc:van:wpaper:0225
    Contact details of provider: Web page: http://www.vanderbilt.edu/econ/wparchive/index.html

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    1. Berkowitz, Jeremy, 2001. "Testing Density Forecasts, with Applications to Risk Management," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 465-474, October.
    2. Elerain, Ola & Chib, Siddhartha & Shephard, Neil, 2001. "Likelihood Inference for Discretely Observed Nonlinear Diffusions," Econometrica, Econometric Society, vol. 69(4), pages 959-93, July.
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