Relationship Between Bitcoin, Gold, Crude Oil, United States Stock Market, and China Stock Market during COVID-19 and Russia-Ukraine War Vector Autoregressive Regressions and Granger Causality Analysis

This study examines the relationships between the United States and China stock markets, bitcoin, oil, and gold, during the COVID-19 pandemic and the Russian-Ukraine war. The data is extracted from the Bloomberg terminal, and through vector autoregressive regression model and Granger causality tests, relationships and effects between one financial asset and another are investigated. The key findings indicate a Granger causality where the lagged 2-day price of The U.S. stock market can predict the China stock market movement. Besides that, the lagged 2-day price of gold can also predict the United States stock market, China stock market, and crude oil on that day. This study gives insights for investors to understand what variables must be analyzed as a concern before making an investment decision during COVID-19 and the Russia-Ukraine War on each variable investigated in this research. Knowing about the relationship of each asset with vector autoregressive regressions an investor can select more relevant variables to be analyzed before making an investment decision. This research also gives insight for investors to predict the price evidenced by Granger causality during COVID-19 and the Russia-Ukraine War.

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Publication Details

Published
2024-09-04
DOI
https://doi.org/10.1109/iciss62896.2024.10751609
Primary Topic
Market Dynamics and Volatility
Type
article
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article

Relationship Between Bitcoin, Gold, Crude Oil, United States Stock Market, and China Stock Market during COVID-19 and Russia-Ukraine War Vector Autoregressive Regressions and Granger Causality Analysis

Eric Carlo Wibisono, Edwin Hendra, Cindy Patricia, Febian Billy Sutanto
Market Dynamics and Volatility
article

Relationship Between Bitcoin, Gold, Crude Oil, United States Stock Market, and China Stock Market during COVID-19 and Russia-Ukraine War Vector Autoregressive Regressions and Granger Causality Analysis

Eric Carlo Wibisono, Edwin Hendra, Cindy Patricia, Febian Billy Sutanto
article en

Abstract

This study examines the relationships between the United States and China stock markets, bitcoin, oil, and gold, during the COVID-19 pandemic and the Russian-Ukraine war. The data is extracted from the Bloomberg terminal, and through vector autoregressive regression model and Granger causality tests, relationships and effects between one financial asset and another are investigated. The key findings indicate a Granger causality where the lagged 2-day price of The U.S. stock market can predict the China stock market movement. Besides that, the lagged 2-day price of gold can also predict the United States stock market, China stock market, and crude oil on that day. This study gives insights for investors to understand what variables must be analyzed as a concern before making an investment decision during COVID-19 and the Russia-Ukraine War on each variable investigated in this research. Knowing about the relationship of each asset with vector autoregressive regressions an investor can select more relevant variables to be analyzed before making an investment decision. This research also gives insight for investors to predict the price evidenced by Granger causality during COVID-19 and the Russia-Ukraine War.

Binus University (ID)
Decent work and economic growth
Openalex Percentile: Top 75%
Market Dynamics and Volatility
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