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    Rights statement: This is the author’s version of a work that was accepted for publication in Journal of Financial Stability. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Financial Stability, 24, 2016 DOI: 10.1016/j.jfs.2016.04.007

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Non-linearities in financial bubbles: theory and Bayesian evidence from S&P500

Research output: Contribution to journalJournal articlepeer-review

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<mark>Journal publication date</mark>06/2016
<mark>Journal</mark>Journal of Financial Stability
Volume24
Number of pages10
Pages (from-to)61-70
Publication StatusPublished
Early online date28/04/16
<mark>Original language</mark>English

Abstract

The modeling process of bubbles, using advanced mathematical and econometric techniques, is a young field of research. In this context, significant model misspecification could result from ignoring potential nonlinearities and, hence, it would seem wise to ensure that no terms with explanatory power are neglected. More precisely, the present paper attempts to detect and date non-linear bubble episodes. To do so, we use Neural Networks to capture the neglected non-linearities. Also, we provide a recursive dating procedure for bubble episodes. When using data on stock price-dividend ratio S&P500 (1871.1-2014.6), employing Bayesian techniques, the proposed approach identifies more episodes than other bubble tests in the literature, while the common episodes are, in general, found to have a longer duration, which is evidence of an early warning mechanism (EWM) that could have important policy implications.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Journal of Financial Stability. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Financial Stability, 24, 2016 DOI: 10.1016/j.jfs.2016.04.007