Probabilistic forecasting of bubbles and flash crashes
By: Banerjee, A., Chevillon, G. and Kratz, M
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Material type: 
BookPublisher: The Econometrics Journal Description: 23(2), May, 2020: p.297-315.Subject(s): Random coefficient overaggressive model, Local asymptotic, Predictive dentistry, Bubbles, Flash crashes
In:
The Econometrics JournalSummary: 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. – Reproduced
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Articles
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Indian Institute of Public Administration | 23(2), May, 2020: p.297-315 | Available | AR125408 |
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. – Reproduced
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