Probabilistic forecasting of bubbles and flash crashes
Anurag Banerjee (),
Guillaume Chevillon () and
Econometrics Journal, 2020, vol. 23, issue 2, 297-315
SummaryWe 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.
Keywords: random coefficient autoregressive model; local asymptotics; predictive density; bubbles; flash crashes (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:oup:emjrnl:v:23:y:2020:i:2:p:297-315.
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