A Meta-Distribution for Non-Stationary Samples

Dominique Guégan ()
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Dominique Guégan: PSE, Centre d’Economie de la Sorbonne, University Paris1 Panthéon-Sorbonne, Postal: PSE, Centre d’Economie de la Sorbonne, University Paris1 Panthéon-Sorbonne, MSE, 106 bd de l’Hôpital, 75013 Paris, France

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: In this paper, we focus on the building of an invariant distribution function associated to a non-stationary sample. After discussing some specific problems encountered by non-stationarity inside samples like the "spurious" long memory effect, we build a sequence of stationary processes permitting to define the concept of meta-distribution for a given non-stationary sample. We use this new approach to discuss some interesting econometric issues in a non-stationary setting, namely forecasting and risk management strategy.

Keywords: Non-Stationarity; Copula; Long-memory; Switching; Cumulants; Estimation theory (search for similar items in EconPapers)
JEL-codes: C32 C51 G12 (search for similar items in EconPapers)
Pages: 23
Date: 2009-06-01
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-rmg
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Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2009-24

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