dc.contributor.author | Smug, D | |
dc.contributor.author | Ashwin, P | |
dc.contributor.author | Sornette, D | |
dc.date.accessioned | 2018-03-22T16:00:21Z | |
dc.date.issued | 2018-03-29 | |
dc.description.abstract | We analyse the behaviour of a non-linear model of coupled stock and bond prices exhibiting
periodically collapsing bubbles. By using the formalism of dynamical system theory, we explain what drives
the bubbles and how foreshocks or aftershocks are generated. A dynamical phase space representation of
that system coupled with standard multiplicative noise rationalises the log-periodic power law singularity
pattern documented in many historical financial bubbles. The notion of ‘ghosts of finite-time singularities’
is introduced and used to estimate the end of an evolving bubble, using finite-time singularities of an
approximate normal form near the bifurcation point. We test the forecasting skill of this method on
different stochastic price realisations and compare with Monte Carlo simulations of the full system.
Remarkably, the approximate normal form is significantly more precise and less biased. Moreover, the
method of ghosts of singularities is less sensitive to the noise realisation, thus providing more robust
forecasts. | en_GB |
dc.description.sponsorship | This project has received
funding from the European Unions Horizon 2020 research
and innovation programme under the Marie Sk lodowska-Curie
grant agreement No 643073. | en_GB |
dc.identifier.citation | Vol. 13 (3), article e0195265 | en_GB |
dc.identifier.doi | 10.1371/journal.pone.0195265 | |
dc.identifier.uri | http://hdl.handle.net/10871/32202 | |
dc.language.iso | en | en_GB |
dc.publisher | Public Library of Science | en_GB |
dc.rights | 2018 Smug et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | |
dc.subject | financial markets | en_GB |
dc.subject | state space models | en_GB |
dc.subject | price forecasting | en_GB |
dc.subject | simulation | en_GB |
dc.subject | bifurcation theory | en_GB |
dc.subject | finite-time singularity | en_GB |
dc.title | Predicting Financial Market Crashes Using Ghost Singularities | en_GB |
dc.type | Article | en_GB |
dc.description | This is the author accepted manuscript.The final version is available from Public Library of Science via the DOI in this record | en_GB |
dc.identifier.journal | PLoS ONE | en_GB |