文章基本信息

标题：Modelling Market Indices, Commodity Market Prices and Stock Prices of Energy Sector using VAR with Variance Decomposition Model
本地全文：下载
作者：Bharat Kumar Meher ; Iqbal Thonse Hawaldar ; Santosh Kumar 等
期刊名称：International Journal of Energy Economics and Policy
电子版ISSN：2146-4553
出版年度：2022
卷号：12
期号：4
页码：122-130
DOI：10.32479/ijeep.13161
语种：English
出版社：EconJournals
摘要：The study aims to examine the existence of a correlation between the stock prices of the energy sector, commodities prices of the energy sector, and market indices. The study uses an empirical approach to develop various VAR (Vector Autoregression) with Variance Decomposition Models for each company under the energy sector indexed in NIFTY50 by considering daily prices for 3 years. For a comparative study, the data have been divided into two parts. The first part is considered pre-COVID era, i.e., from July 1, 2018, to December 31, 2019, and the second part is considered post-COVID era, i.e., from January 1, 2020, to June 30, 2021. While observing the estimates of VAR of different companies, it can be said that crude oil is significant in most of the models during pre-COVID whereas, during post COVID, lag term of crude oil and NIFTYENGERGY are significant. On the other hand, while observing the estimates of variance decomposition in all the VAR models, the first lag term of the particular company's share price is strongly endogenous. In comparison, the other independent variable, i.e., lag term of the price of crude oil and natural gas, values of NIFTY50 and NIFTY ENERGY are strongly exogenous to the stock prices of the energy sector.
关键词：Vector Autoregression;VAR with Variance Decomposition;Market Index;NIFTY50;Nifty Energy;Commodity Market;COVID