The tail of the stationary distribution of a random coefficient AR(q) model

By Claudia Klüppelberg, Serguei Pergamenchtchikov. 2004

66 citations recorded by the source corpus.

We investigate a stationary random cofficient autoregressive process. Using renewal type arguments tailor-made for such processes we show that the stationary distribution has a power-law tail. When the model is normal, we show that the model is in distribution equivalent to an autoregressive process with ARCH errors. Hence we obtain the tail behaviour of any such model of arbitrary order.

Subfields: Finance

View Paper: https://www.semanticscholar.org/paper/51c4728e2ba15774ecb1fea90a2cbe71ef041e76

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In Finance

1. Yves Guivarc'h
2. Mariusz Mirek

Citations in the corpus

• Tail-homogeneity of stationary measures for some multidimensional stochastic recursions (2009, methodology): “In general, if Mn are only in GL(V ), (1.1) not being required, the remarkable fact that the tail of � is homogeneous has been observed by Kesten ([K], see also [Gri], [Gol], [Gui2], [ KP ], [LeP]).”