Out-of-sample Comparison of Copula Specifications in Multivariate Density Forecasts

Arbeitspapier

We introduce a statistical test for comparing the predictive accuracy of competing copula specifications in multivariate density forecasts, based on the Kullback-Leibler Information Criterion (KLIC). The test is valid under general conditions: in particular it allows for parameter estimation uncertainty and for the copulas to be nested or non-nested. Monte Carlo simulations demonstrate that the proposed test has satisfactory size and power properties in finite samples. Applying the test to daily exchange rate returns of several major currencies against the US dollar we find that the Student's t copula is favored over Gaussian, Gumbel and Clayton copulas. This suggests that these exchange rate returns are characterized by symmetric tail dependence.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Tinbergen Institute Discussion Paper ; No. 08-105/4

Classification and Topics

• Classification: Wirtschaft ; Hypothesis Testing: General ; Semiparametric and Nonparametric Methods: General ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Model Evaluation, Validation, and Selection ; Forecasting Models; Simulation Methods
• Subject: Copula-based density forecast ; semiparametric statistics ; out-of-sample forecast evaluation ; Kullback-Leibler Information Criterion ; empirical copula ; Kopula (Mathematik) ; Prognoseverfahren ; Nichtparametrisches Verfahren ; Zeitreihenanalyse ; Modellierung ; Theorie

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Diks, Cees ; Panchenko, Valentyn ; van Dijk, Dick
• Event: Veröffentlichung
• (who): Tinbergen Institute
• (where): Amsterdam and Rotterdam
• (when): 2008

Further information

• Handle: http://hdl.handle.net/10419/86957
• Last update: 10.03.2025, 11:44 AM CET