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Asymmetric effect of COVID-19 pandemic on E7 stock indices: Evidence from quantile-on-quantile regression approach

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  • Hashmi, Shabir Mohsin
  • Chang, Bisharat Hussain
  • Rong, Li

Abstract

Various studies have been conducted to examine the effect of COVID-19 on stock prices. However, these studies failed to examine the effect across quantile distributions of both dependent and independent variables. This study pays particular attention to the emerging 7 countries and examines the effect of the novel coronavirus 2019 (COVID-19) pandemic on stock prices. We use quantile unit root and quantile cointegration tests to examine the integrating properties of COVID-19 cases and deaths with stock prices and use quantile-on-quantile regression (QQR) to examine the relationship across quantile distributions of both dependent and independent variables. Quantile cointegration estimates indicate that stock prices are integrated with COVID-19 cases whereas QQR estimates indicate a weak positive relationship at the upper quantiles of stock prices, and a strong negative effect is found at the lower quantiles of stock prices. Policy implications are recommended based on the findings of this study.

Suggested Citation

  • Hashmi, Shabir Mohsin & Chang, Bisharat Hussain & Rong, Li, 2021. "Asymmetric effect of COVID-19 pandemic on E7 stock indices: Evidence from quantile-on-quantile regression approach," Research in International Business and Finance, Elsevier, vol. 58(C).
    • Handle: RePEc:eee:riibaf:v:58:y:2021:i:c:s0275531921001069
    DOI: 10.1016/j.ribaf.2021.101485
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    Cited by:

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    2. Wang, Kai-Hua & Su, Chi-Wei & Xiao, Yidong & Liu, Lu, 2022. "Is the oil price a barometer of China's automobile market? From a wavelet-based quantile-on-quantile regression perspective," Energy, Elsevier, vol. 240(C).
    3. Bisharat Hussain Chang & Omer Faruk Derindag & Nuri Hacievliyagil & Mehmet Canakci, 2022. "Exchange rate response to economic policy uncertainty: evidence beyond asymmetry," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-14, December.
    4. Kuan-Min Wang & Yuan-Ming Lee, 2023. "Are life insurance futures a safe haven during COVID-19?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.
    5. Liu, Fang & Umair, Muhammad & Gao, Junjun, 2023. "Assessing oil price volatility co-movement with stock market volatility through quantile regression approach," Resources Policy, Elsevier, vol. 81(C).
    6. Bossman, Ahmed & Umar, Zaghum & Teplova, Tamara, 2022. "Modelling the asymmetric effect of COVID-19 on REIT returns: A quantile-on-quantile regression analysis," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    7. Wang, Kai-Hua & Liu, Lu & Zhong, Yifan & Lobonţ, Oana-Ramona, 2022. "Economic policy uncertainty and carbon emission trading market: A China's perspective," Energy Economics, Elsevier, vol. 115(C).
    8. Feipeng Zhang & Yun Hong & Yanhui Jiang & Jiayi Yu, 2022. "Impact of national media reporting concerning COVID-19 on stock market in China: empirical evidence from a quantile regression," Applied Economics, Taylor & Francis Journals, vol. 54(33), pages 3861-3881, July.
    9. Emre Cevik & Buket Kirci Altinkeski & Emrah Ismail Cevik & Sel Dibooglu, 2022. "Investor sentiments and stock markets during the COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-34, December.
    10. Ștefan Cristian Gherghina & Daniel Ștefan Armeanu & Camelia Cătălina Joldeș, 2021. "COVID-19 Pandemic and Romanian Stock Market Volatility: A GARCH Approach," JRFM, MDPI, vol. 14(8), pages 1-29, July.

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    More about this item

    Keywords

    Quantile-on-quantile regression; COVID-19; Quantile cointegration; E7 stock markets;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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