Explosive Bubble Modelling by Noncausal Process
AbstractThe linear mixed causal and noncausal autoregressive processes provide often a better fit to economic and financial time series than the standard causal linear autoregressive processes. By considering the example of the noncausal Cauchy autoregressive process, we show that it might be explained by the special associated nonlinear causal dynamics. Indeed, this causal dynamics can include unit root, bubble phenomena, or asymmetric cycles often observed on financial markets. The noncausal Cauchy autoregressive process provides a new modelling for explosive multiple bubbles and their transmission in a multivariate dynamic framework. We also explain why standard unit root tests will fail in detecting such explosive bubbles
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Bibliographic InfoPaper provided by Centre de Recherche en Economie et Statistique in its series Working Papers with number 2013-04.
Date of creation: Feb 2013
Date of revision:
Causal Innovation; Explosive Bubble; Noncausal Process; Unit Root; Bubble Cointegration;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-06-04 (All new papers)
- NEP-CWA-2013-06-04 (Central & Western Asia)
- NEP-ECM-2013-06-04 (Econometrics)
- NEP-ETS-2013-06-04 (Econometric Time Series)
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- Gouriéroux, Christian & Zakoian, Jean-Michel, 2014. "On uniqueness of moving average representations of heavy-tailed stationary processes," MPRA Paper 54907, University Library of Munich, Germany.
- Saikkonen, Pentti & Sandberg , Rickard, 2013. "Testing for a unit root in noncausal autoregressive models," Research Discussion Papers 26/2013, Bank of Finland.
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