JOURNAL ARTICLE

An examination of impact of gold and oil prices on the stock markets indices during COVID-19.

  • Published In: International Journal of Financial Engineering, 2025, v. 12, n. 2. P. 1 1 of 3

  • Database: Mathematics Source 2 of 3

  • Authored By: Fatima, Samreen; Sohail, Fouzia; Sajid, Yumna 3 of 3

Abstract

Understanding stock market volatility has remained significantly important because of its diverse implications. The current pandemic COVID-19 has brutally exaggerated the financial market across the board. This study inspects the volatility of Pakistan, India and USA stock markets due to pandemic of COVID-19 using the GARCH model. Furthermore, the price of oil and gold is used as exogenous variables in the conditional mean equation of the GARCH (1,1) model to assess the volatility of stock indices KSE-100 (Pakistan), BSESN (India) and NASDAQ (USA). Moreover, the data covering the period from 1st June 2018 to 31st December 2022 are divided into pre-COVID-19 (1st June 2018 to 30th January 2020) and during-COVID-19 (31st January 2020 to 31st December 2022. Findings reveal that the stock market dependency of NASDAQ experienced oil and gold impact followed by pre-COVID-19 and during-COVID-19 periods, respectively. Whereas, the Indian stock market had a significant impact on gold and oil during the COVID-19 period but the Pakistani stock market was not influenced by oil and gold in the entire considered study period. In addition, NASDAQ market and BSESN have the highest risk-return trade-off and are more persistent followed by pre-COVID-19 and during-COVID-19 periods, respectively. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Financial Engineering. 2025/06, Vol. 12, Issue 2, p1
  • Document Type:Article
  • Subject Area:Economics
  • Publication Date:2025
  • ISSN:2424-7863
  • DOI:10.1142/S2424786323500111
  • Accession Number:186254931
  • Copyright Statement:Copyright of International Journal of Financial Engineering is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.