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Probabilistic Forecasting of Bubbles and Flash Crashes

Banerjee, A.; Chevillon, G.; Kratz, M.

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Authors

G. Chevillon

M. Kratz



Abstract

We propose a near explosive random coefficient autoregressive model (NERC) to obtain predictive probabilities of the apparition and devolution of bubbles. The distribution of the autoregressive coefficient of this model is allowed to be centred at an O(T−α) distance of unity, with α ∈ (0, 1). When the expectation of the autoregressive coefficient lies on the explosive side of unity, the NERC helps to model the temporary explosiveness of time series and obtain related predictive probabilities. We study the asymptotic properties of the NERC and provide a procedure for inference on the parameters. In empirical illustrations, we estimate predictive probabilities of bubbles or flash crashes in financial asset prices.

Citation

Banerjee, A., Chevillon, G., & Kratz, M. (2020). Probabilistic Forecasting of Bubbles and Flash Crashes. The Econometrics Journal, 23(2), 297-315. https://doi.org/10.1093/ectj/utaa004

Journal Article Type Article
Acceptance Date Oct 20, 2019
Online Publication Date Feb 14, 2020
Publication Date May 31, 2020
Deposit Date Oct 28, 2019
Publicly Available Date Mar 29, 2024
Journal Econometrics Journal
Print ISSN 1368-4221
Electronic ISSN 1368-423X
Publisher Oxford University Press
Peer Reviewed Peer Reviewed
Volume 23
Issue 2
Pages 297-315
DOI https://doi.org/10.1093/ectj/utaa004
Public URL https://durham-repository.worktribe.com/output/1286728

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Copyright Statement
This is a pre-copyedited, author-produced PDF of an article accepted for publication in The Econometrics Journal following peer review. The version of record Banerjee, A., Chevillon, G. & Kratz, M. (2020). Probabilistic Forecasting of Bubbles and Flash Crashes. The Econometrics Journal 23(2): 297-315 is available online at: https://doi.org/10.1093/ectj/utaa004





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