Francesco Giancaterini, Alain Hecq, Joann Jasiak, Aryan Manafi Neyazi
arXiv 20 May 2025 · Econometrics
arXiv:2505.14911 · PDF · DOI · OpenAlex · Extracted main text
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.
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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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Gourieroux, Christian and Zakoian, Jean-Michel (2017) Local explosion modelling by non-causal process | 0.843 | 5 | 4 | 60% |
| 2 | Hecq, Alain and Voisin, Elisa (2023) Predicting crashes in oil prices during the COVID-19 pandemic with mixed causal-noncausal models self | 0.843 | 3 | 3 | 100% |
| 3 | Kulik, Rafal and Soulier, Philippe (2020) Heavy-tailed time series | 0.811 | 4 | 2 | 100% |
| 4 | Fries, Sébastien (2022) Conditional moments of noncausal alpha-stable processes and the prediction of bubble crash odds | 0.763 | 6 | 2 | 67% |
| 5 | Fries, Sebastien and Zakoian, Jean-Michel (2019) Mixed causal-noncausal ar processes and the modelling of explosive bubbles | 0.754 | 7 | 3 | 43% |
| 6 | Gourieroux, Christian and Jasiak, Joann (2023) Generalized covariance estimator self | 0.693 | 5 | 1 | 100% |
| 7 | Cavaliere, Giuseppe and Nielsen, Heino Bohn and Rahbek, Anders (2020) Bootstrapping noncausal autoregressions: with applications to explosive bubble modeling | 0.644 | 2 | 2 | 100% |
| 8 | Davis, Richard A and Drees, Holger and Segers, Johan and Warchoł, Mi… blueInference on the tail process with application to financial time series modeling | 0.644 | 2 | 2 | 100% |
| 9 | de Truchis, Gilles and Fries, Sébastien and Thomas, Arthur (2025) Forecasting Extreme Trajectories Using Seminorm Representations | 0.644 | 2 | 2 | 100% |
| 10 | Gourieroux, Christian and Jasiak, Joann (2016) Filtering, prediction and simulation methods for noncausal processes self | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 49 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | 2509.13492 | 0.405 | 1 | 1 |