Fayçal Djebari, Kahina Mehidi, Khelifa Mazouz, Philipp Otto
arXiv 20 Jul 2025 · Econometrics
arXiv:2507.15046 · PDF · DOI · OpenAlex · Extracted main text
This paper examines several network-based volatility models for oil prices, capturing spillovers among OPEC oil-exporting countries by embedding novel network structures into ARCH-type models. We apply a network-based log-ARCH framework that incorporates weight matrices derived from time-series clustering and model-implied distances into the conditional variance equation. These weight matrices are constructed from return data and standard multivariate GARCH model outputs (CCC, DCC, and GO-GARCH), enabling a comparative analysis of volatility transmission across specifications. Through a rolling-window forecast evaluation, the network-based models demonstrate competitive forecasting performance relative to traditional specifications and uncover intricate spillover effects. These results provide a deeper understanding of the interconnectedness within the OPEC network, with important implications for financial risk assessment, market integration, and coordinated policy among oil-producing economies.
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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 | Mattera, Raffaele and Otto, Philipp (2024) Network Log-ARCH Models for Forecasting Stock Market Volatility self | 1.000 | 9 | 4 | 100% |
| 2 | Otto, Philipp and Do gan, Osman and Ta spinar, Süleyman (2024) Dynamic Spatiotemporal ARCH Models self | 1.000 | 8 | 4 | 100% |
| 3 | Bollerslev, Tim (1990) Modelling the Coherence in Short-Run Nominal Exchange Rates: A Multivariate Generalized ARCH Model | 0.928 | 4 | 4 | 100% |
| 4 | Engle, Robert (2002) Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models | 0.928 | 4 | 4 | 100% |
| 5 | Harvey, David I. and Leybourne, Stephen J. and Zu, Yang (2024) Tests for equal forecast accuracy under heteroskedasticity | 0.874 | 5 | 2 | 100% |
| 6 | Van der Weide, Roy (2002) GO‐GARCH: a multivariate generalized orthogonal GARCH model | 0.843 | 3 | 3 | 100% |
| 7 | Diebold, Francis X and Mariano, Robert S (2002) Comparing Predictive Accuracy | 0.811 | 4 | 2 | 100% |
| 8 | Piccolo, Domenico (1990) A DISTANCE MEASURE FOR CLASSIFYING ARIMA MODELS | 0.811 | 4 | 2 | 100% |
| 9 | Al Rousan, Sahel and Sbia, Rashid and Tas, Bedri Kamil Onur (2018) A dynamic network analysis of the world oil market: Analysis of OPEC and non-OPEC members | 0.737 | 3 | 2 | 100% |
| 10 | Kilian, Lutz (2008) The Economic Effects of Energy Price Shocks | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 88 scored citations.