Nonlinear cointegration in financial time series

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Abstract

In this paper, the concept of linear cointegration as introduced by Engle and Granger [5] is merged into the local paradigm. Adopting a local approach enables the achievement of a local error correction model characterised by dynamic parameters.Another important result obtained using the local paradigm is that the mechanism that leads the dynamic system back to a steady state is no longer a constant: it is a function not defined a priori but estimated point by point.

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Pizzi, C. (2010). Nonlinear cointegration in financial time series. In Mathematical and Statistical Methods for Actuarial Sciences and Finance (pp. 263–271). Kluwer Academic Publishers. https://doi.org/10.1007/978-88-470-1481-7_27

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