Volatility Spillovers and Interconnectedness in OPEC Oil Markets: A Network-Based log-ARCH Approach
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
CSTS: A Benchmark for the Discovery of Correlation Structures in Time Series Clustering
$k$-Graph: A Graph Embedding for Interpretable Time Series Clustering
Time Series Clustering with General State Space Models via Stochastic Variational Inference
Unraveling Anomalies in Time: Unsupervised Discovery and Isolation of Anomalous Behavior in Bio-regenerative Life Support System Telemetry
ShapeDBA: Generating Effective Time Series Prototypes using ShapeDTW Barycenter Averaging
PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series
토론
이 논문과 연결된 포럼 글이 아직 없습니다.