EconBase
← All papers

Bubble Detection with Application to Green Bubbles: A Noncausal Approach

Francesco Giancaterini, Alain Hecq, Joann Jasiak, Aryan Manafi Neyazi

arXiv 20 May 2025 · Econometrics

arXiv:2505.14911 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper introduces a new approach to detect bubbles based on mixed causal and noncausal processes and their tail process representation during explosive episodes. Departing from traditional definitions of bubbles as nonstationary and temporarily explosive processes, we adopt a perspective in which prices are viewed as following a strictly stationary process, with the bubble considered an intrinsic component of its non-linear dynamics. We illustrate our approach on the phenomenon referred to as the "green bubble" in the field of renewable energy investment.

Citation extraction

49
references
88
in-text mentions
49
distinct cited
13
self-citations
11,892
main-text words

appendix boundary found by appendix_command · 79% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Gourieroux, Christian and Zakoian, Jean-Michel (2017) Local explosion modelling by non-causal process0.8435460%
2Hecq, Alain and Voisin, Elisa (2023) Predicting crashes in oil prices during the COVID-19 pandemic with mixed causal-noncausal models self0.84333100%
3Kulik, Rafal and Soulier, Philippe (2020) Heavy-tailed time series0.81142100%
4Fries, Sébastien (2022) Conditional moments of noncausal alpha-stable processes and the prediction of bubble crash odds0.7636267%
5Fries, Sebastien and Zakoian, Jean-Michel (2019) Mixed causal-noncausal ar processes and the modelling of explosive bubbles0.7547343%
6Gourieroux, Christian and Jasiak, Joann (2023) Generalized covariance estimator self0.69351100%
7Cavaliere, Giuseppe and Nielsen, Heino Bohn and Rahbek, Anders (2020) Bootstrapping noncausal autoregressions: with applications to explosive bubble modeling0.64422100%
8Davis, Richard A and Drees, Holger and Segers, Johan and Warchoł, Mi… blueInference on the tail process with application to financial time series modeling0.64422100%
9de Truchis, Gilles and Fries, Sébastien and Thomas, Arthur (2025) Forecasting Extreme Trajectories Using Seminorm Representations0.64422100%
10Gourieroux, Christian and Jasiak, Joann (2016) Filtering, prediction and simulation methods for noncausal processes self0.64422100%

Showing the top 10 of 49 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
12509.134920.40511