Stationarity and Ergodicity Regions for Score Driven Dynamic Correlation Models

Francisco Blasques (), Andre Lucas and Erkki Silde
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Erkki Silde: VU University Amsterdam, and Duisenberg school of finance

Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: We describe stationarity and ergodicity (SE) regions for a recently proposed class of score driven dynamic correlation models. These models have important applications in empirical work. The regions are derived from sufficiency conditions in Bougerol (1993) and take a non-standard form. We show that the non-standard shape of the sufficiency regions cannot be avoided by reparameterizing the model or by rescaling the score steps in the transition equation for the correlation parameter. This makes the result markedly different from the volatility case. Observationally equivalent decompositions of the stochastic recurrence equation yield regions with different sizes and shapes. We illustrate our results with an analysis of time-varying correlations between UK and Greek equity indices. We find that also in empirical applications different decompositions can give rise to different conclusions regarding the stability of the estimated model.

Keywords: dynamic copulas; generalized autoregressive score (GAS) models; stochastic recurrence equations; observation driven models; contraction properties (search for similar items in EconPapers)
JEL-codes: C22 C32 C58 (search for similar items in EconPapers)
Date: 2013-07-19
New Economics Papers: this item is included in nep-ets
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20130097

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