Predicting the Symmetric and Asymmetric Volatility of Energy Market: Evidence from COVID Outbreak in India and USA

Author:

Panwar Kajal1,Yadav Miklesh Prasad2,Puri Neha3

Affiliation:

1. Amity College of Commerce and Finance (ACCF), Amity University, Noida, Uttar Pradesh, India

2. Indian Institute of Foreign Trade, Kakinada, India

3. Amity University, Noida, Uttar Pradesh, India

Abstract

The COVID-19 pandemic had a tremendous impact on the energy sector because of demand factor. Volatility has emerged as a major concern in the energy industry and COVID-19 has cast a dark shadow over this characteristic. We predict the symmetrical and asymmetric volatility of energy market in India and USA during COVID-19 outbreak tenure. The energy market is proxied by crude oil and natural gas of these two countries. For an empirical estimation, standard generalized autoregressive conditional heteroscedasticity (s-GARCH) and exponential GARCH (e-GARCH) are employed based on daily observations spanning from March 25, 2020 to January 31, 2022. The result reveals that new information is captured and there is volatility persistence in both Indian and US energy markets. The conditional volatility decays over the time of these markets since it is backed by mean reversion and Indian energy market decays fast comparatively. Additionally, it depicts that there is no leverage effect in both Indian and US energy markets. This study furnishes an insight to the investors and portfolio managers with respect to risk prediction considering impact of good and bad news.

Publisher

SAGE Publications

Subject

Strategy and Management,Business and International Management

Reference28 articles.

1. Analysis of the electricity demand trends amidst the COVID-19 coronavirus pandemic

2. COVID-Induced Economic Uncertainty

3. Black F. (1976). Studies of stock market volatility changes. Proceedings of the American Statistical Association Bisiness and Economic Statistics Section (pp. 177–181). http://ci.nii.ac.jp/naid/10018822970/en/

4. Generalized autoregressive conditional heteroskedasticity

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3