Regime changes and extreme risk spillovers of INE crude oil futures DOI

Min Liu,

Xu Yang,

Chien‐Chiang Lee

и другие.

Applied Economics, Год журнала: 2024, Номер unknown, С. 1 - 14

Опубликована: Июнь 18, 2024

This study identifies the regime changes and investigates extreme risk spillovers of China's first international crude oil futures (INECOFs). The novelty this is that a non-linear process incorporated to examine structural breaks INECOFs capture movements risk. To facilitate traders global financial investors hedge against risk, between market are investigated. We find that: (1) two-regime GJRGARCH-SGED model can identify generate more accurate measures; (2) probability in tranquil 86.01% agitated 13.99%; (3) plays modest role spillover network, while benchmark an important role; (4) upside receiver downside transmitter. make attempt volatility spillovers.

Язык: Английский

Burden of the global energy price crisis on households DOI Open Access
Yuru Guan, Yan Jin, Yuli Shan

и другие.

Nature Energy, Год журнала: 2023, Номер 8(3), С. 304 - 316

Опубликована: Фев. 16, 2023

Язык: Английский

Процитировано

277

Quantile spillovers and connectedness between oil shocks and stock markets of the largest oil producers and consumers DOI Creative Commons
Waqas Hanif, Sinda Hadhri, Rim El Khoury

и другие.

Journal of commodity markets, Год журнала: 2024, Номер 34, С. 100404 - 100404

Опубликована: Апрель 21, 2024

This study explores the connectedness between major oil-producing and consuming countries' stock markets (United States, China, Russia, India) different oil shocks categorized as demand, supply, risk shocks, following Ready's (2018) framework. Employing a quantile-based approach quantile cross-spectral dependence, our analysis spans from July 02, 2007 to May 31, 2023, encompassing diverse market conditions events. These methodologies help identify interdependence patterns in extreme scenarios at time intervals. Key findings show variations how these respond depending on quantiles. Demand-related have most significant spillover effects United India, while risk-related dominate transmitters of India median Market interconnectedness strengthens during conditions, reflecting historical Additionally, bearish offer diversification opportunities countries crude oil. emphasizes need for tailored investment strategies, monitoring global demand trends, dynamic portfolio management, inclusion portfolios, proactive responses players geopolitical insights benefit investors policymakers seeking optimize strategies interconnected financial landscape.

Язык: Английский

Процитировано

24

Liquid hydrogen superconducting transmission based super energy pipeline for Pacific Rim in the context of global energy sustainable development DOI
Boyu Qin, Hongzhen Wang, Yong Liao

и другие.

International Journal of Hydrogen Energy, Год журнала: 2024, Номер 56, С. 1391 - 1396

Опубликована: Янв. 4, 2024

Язык: Английский

Процитировано

21

Impact of natural resources and technology on economic development and sustainable environment – Analysis of resources-energy-growth-environment linkages in BRICS DOI
Hewu Kuang, Yiyan Liang, Wenjia Zhao

и другие.

Resources Policy, Год журнала: 2023, Номер 85, С. 103865 - 103865

Опубликована: Июль 8, 2023

Язык: Английский

Процитировано

42

Forecasting oil, coal, and natural gas prices in the pre-and post-COVID scenarios: Contextual evidence from India using time series forecasting tools DOI Open Access
Md Shabbir Alam, Muntasir Murshed, Palanisamy Manigandan

и другие.

Resources Policy, Год журнала: 2023, Номер 81, С. 103342 - 103342

Опубликована: Фев. 11, 2023

Язык: Английский

Процитировано

37

Asymmetric efficiency in petroleum markets before and during COVID-19 DOI
Muhammad Abubakr Naeem, Saqib Farid, Imran Yousaf

и другие.

Resources Policy, Год журнала: 2023, Номер 86, С. 104194 - 104194

Опубликована: Сен. 25, 2023

Язык: Английский

Процитировано

35

Do geopolitical risks facilitate the global energy transition? Evidence from 39 countries in the world DOI
Shanyong Wang, Jing Wang, Wenfu Wang

и другие.

Resources Policy, Год журнала: 2023, Номер 85, С. 103952 - 103952

Опубликована: Июль 22, 2023

Язык: Английский

Процитировано

32

A novel deep-learning technique for forecasting oil price volatility using historical prices of five precious metals in context of green financing – A comparison of deep learning, machine learning, and statistical models DOI
Muhammad Mohsin, Fouad Jamaani

Resources Policy, Год журнала: 2023, Номер 86, С. 104216 - 104216

Опубликована: Окт. 1, 2023

Язык: Английский

Процитировано

28

Volatility forecasting of crude oil futures based on Bi-LSTM-Attention model: The dynamic role of the COVID-19 pandemic and the Russian-Ukrainian conflict DOI
Yan Xu,

Tianli Liu,

Pei Du

и другие.

Resources Policy, Год журнала: 2023, Номер 88, С. 104319 - 104319

Опубликована: Ноя. 15, 2023

Язык: Английский

Процитировано

25

Extreme risk spillovers between SC, WTI and Brent crude oil futures-Evidence from Time-varying Granger causality test DOI
Xiaohang Ren, Yue He,

Chuanwang Liu

и другие.

Energy, Год журнала: 2025, Номер unknown, С. 135495 - 135495

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

1