arXiv 11 Oct 2026 · Econometrics
arXiv:2610.15296 · PDF · Extracted main text
This paper examines the use of recurrent neural networks and their extensions for forecasting autoregressive causal-noncausal processes, characterized by local explosive patterns such as bubbles and spikes. We study the recurrent neural networks (RNN), long short-term memory networks (LSTM), gated recurrent unit (GRU), bidirectional LSTM, and also a simple feed-forward network (FNN) to reveal the difficulty of forecasting extreme values depending on the type of network and the length of the training set. We show that FNN outperforms other networks in predicting extreme values of a univariate noncausal time series during a bubble. We also examine the improvements of point predictions of extreme values resulting from pooling and a modified loss function.
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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 | Fries, Sébastien and Zakoian, Jean-Michel (2019) "Mixed Causal-Noncausal AR Processes And The Modelling Of Explosive Bubbles" | 0.737 | 3 | 2 | 100% |
| 2 | Chandra, Rohitash and Goyal, Shaurya and Gupta, Rishabh (2021) "Evaluation of Deep Learning Models for Multi-Step Ahead Time Series Prediction" | 0.737 | 3 | 2 | 100% |
| 3 | Gourieroux, Christian and Jasiak, Joann (2016) "Filtering, Prediction and Simulation Methods for Noncausal Processes" self | 0.644 | 2 | 2 | 100% |
| 4 | Bryan Lim and Stefan Zohren (2021) "Time-series Forecasting with Deep Learning: A Survey" | 0.511 | 2 | 1 | 100% |
| * | unmatched citation key * | 0.405 | 1 | 1 | 100% |
| 6 | Dumitrescu, Elena and Peignon, Julien and Thomas, Arthur (2026) "Tail-Aware Density Forecasting of Locally Explosive Time Series: A Neural Network Approach" | 0.405 | 1 | 1 | 100% |
| 7 | Gourieroux, Christian and Hencic, Andrew and Jasiak, Joann (2021) "Forecast Performance and Bubble Analysis in Noncausal MAR(1, 1) Processes" self | 0.405 | 1 | 1 | 100% |
| 8 | Gourieroux, Christian and Jasiak, Joann (2026) "Nonlinear Fore(Back)Casting and Innovation Filtering for Causal–Noncausal VAR Models" self | 0.405 | 1 | 1 | 100% |
| 9 | Hochreiter, Sepp and Schmidhuber, Jürgen (1997) "Long Short-Term Memory" | 0.405 | 1 | 1 | 100% |
| 10 | Lanne, Markku and Luoma, Arto and Luoto, Jani (2012) "BAYESIAN MODEL SELECTION AND FORECASTING IN NONCAUSAL AUTOREGRESSIVE MODELS" | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 13 scored citations. 1 of these could not be matched to a bibliography entry, so only the citation key is shown.