Suppr超能文献

高阶矩在能源、碳和旅游市场间的溢出:时频域证据。

Higher-order moments spillovers among energy, carbon and tourism markets: Time- and frequency-domain evidence.

机构信息

School of Finance, Hebei University of Economics and Business, Shijiazhuang, China.

School of Statistics, Renmin University of China, Beijing, China.

出版信息

PLoS One. 2024 Nov 14;19(11):e0313002. doi: 10.1371/journal.pone.0313002. eCollection 2024.

Abstract

This paper uses the GJRSK model to estimate the high-order moments of energy (oil, natural gas, and coal), the carbon market, and tourism stocks. Then, it utilizes a novel TVP-VAR time-frequency connectedness approach to examine higher-order moments spillovers among them. The results show a strong connectedness among the three markets. The energy market is the emitter of volatility, skewness and kurtosis spillovers; tourism stock is the receiver; and the carbon market is the transmitter. From a time-domain perspective, the higher-order moments spillovers of the three markets are time-varying, especially during extreme periods, where the energy market's spillover effects on tourism stocks are significantly enhanced, indicating that tourism stocks bear a greater risk at leptokurtosis and fat-tail moment. From a frequency-domain perspective, the long-term asymmetric spillovers of oil, natural gas, and tourism markets on the carbon market are more pronounced than the short-term. Moreover, the COVID-19 pandemic exacerbated the higher-moment spillovers of energy and tourism stocks on the carbon market. Meanwhile, the Russia-Ukraine conflict led to extreme risk transmission within the energy market. These findings have significant implications for cross-industry investors and green finance risk management.

摘要

本文运用 GJRSK 模型估算了能源(石油、天然气和煤炭)、碳市场和旅游股票的高阶矩。然后,采用新颖的 TVP-VAR 时频关联方法来检验它们之间的高阶矩溢出效应。结果表明,这三个市场之间存在很强的关联性。能源市场是波动、偏度和峰度溢出的发射器;旅游股票是接收器;而碳市场是传递者。从时域角度来看,三个市场的高阶矩溢出是时变的,尤其是在极端时期,能源市场对旅游股票的溢出效应显著增强,表明旅游股票在尖峰厚尾方面承担更大的风险。从频域角度来看,石油、天然气和旅游市场对碳市场的长期非对称溢出比短期更为明显。此外,COVID-19 大流行加剧了能源和旅游股票对碳市场的高阶矩溢出。同时,俄乌冲突导致能源市场内部的极端风险传递。这些发现对跨行业投资者和绿色金融风险管理具有重要意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f6c/11563386/ca6066934315/pone.0313002.g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验