Probabilistic forecasting of bubbles and flash crashes

B-Tier
Journal: The Econometrics Journal
Year: 2020
Volume: 23
Issue: 2
Pages: 297-315

Authors (3)

Anurag Banerjee (Durham University) Guillaume Chevillon (not in RePEc) Marie Kratz (not in RePEc)

Score contribution per author:

0.670 = (α=2.01 / 3 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

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.

Technical Details

RePEc Handle
repec:oup:emjrnl:v:23:y:2020:i:2:p:297-315.
Journal Field
Econometrics
Author Count
3
Added to Database
2026-01-24