<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The study aims to investigate capital market volatility during crises, exploring the relationships between three key financial indicators: oil prices, the VIX index, and gold prices, using monthly data covering the period from January 2013 to May 2023, based on the Granger causality approach and the impulse response function testing empirically the existence of the long-run relationship using Johansen multivariate approach and the estimation of the VAR/VECM model. By analysing their interdependencies, the research sheds light on how these indicators respond to economic turbulence. The study employs robust econometric methods to investigate causal relationships and predictive patterns, providing valuable insights for investors, policymakers, and analysts navigating uncertain financial landscapes. The findings reveal nuanced dynamics, such as the momentum in oil prices, the inverse relationship between oil prices and the VIX index, and a significant Granger causality relationship running from the VIX index to oil and gold prices. Furthermore, based on the impulse response patterns, the shock in the VIX index caused a notable oil price decrease in the second quarter after the shock, followed by oscillations. Gold prices exhibit a minor initial decline after the VIX shock, with no lasting effects.</p>
</abstract>

The study aims to investigate capital market volatility during crises, exploring the relationships between three key financial indicators: oil prices, the VIX index, and gold prices, using monthly data covering the period from January 2013 to May 2023, based on the Granger causality approach and the impulse response function testing empirically the existence of the long-run relationship using Johansen multivariate approach and the estimation of the VAR/VECM model. By analysing their interdependencies, the research sheds light on how these indicators respond to economic turbulence. The study employs robust econometric methods to investigate causal relationships and predictive patterns, providing valuable insights for investors, policymakers, and analysts navigating uncertain financial landscapes. The findings reveal nuanced dynamics, such as the momentum in oil prices, the inverse relationship between oil prices and the VIX index, and a significant Granger causality relationship running from the VIX index to oil and gold prices. Furthermore, based on the impulse response patterns, the shock in the VIX index caused a notable oil price decrease in the second quarter after the shock, followed by oscillations. Gold prices exhibit a minor initial decline after the VIX shock, with no lasting effects.

Capital Market Volatility During Crises: Oil Price Insights, VIX Index, and Gold Price Analysis

Management & Marketing

This work is licensed under the Creative Commons Attribution 4.0 International License.

The study aims to investigate capital market volatility during crises, exploring the relationships between three key financial indicators: oil prices, the VIX...

Capital Market Volatility During Crises: Oil Price Insights, VIX Index, and Gold Price Analysis

Pubblicato online: 28 set 2023

Pagine: 290 - 314

DOI: https://doi.org/10.2478/mmcks-2023-0016

Parole chiave
Capital Market Volatility, Oil Price Insights, VIX Index, Gold Price Analysis, Granger causality analysis, VAR models

© 2023 Razvan Gabriel Hapau, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Capital Market Volatility During Crises: Oil Price Insights, VIX Index, and Gold Price Analysis

Pubblicato online: 28 set 2023

Pagine: 290 - 314

DOI: https://doi.org/10.2478/mmcks-2023-0016

Parole chiaveCapital Market Volatility, Oil Price Insights, VIX Index, Gold Price Analysis, Granger causality analysis, VAR models

© 2023 Razvan Gabriel Hapau, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
Capital Market Volatility, Oil Price Insights, VIX Index, Gold Price Analysis, Granger causality analysis, VAR models