Probabilistic Forecasting of Bubbles and Flash Crashes

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

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: Feb 14, 2022
• 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