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EU sectoral stocks amid geopolitical risk, market sentiment, and crude oil implied volatility: An asymmetric analysis of the Russia-Ukraine tensions

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  • Bossman, Ahmed
  • Gubareva, Mariya
  • Teplova, Tamara

Abstract

This study examines the asymmetric relationships between EU sectoral stocks and oil, oil implied volatility, geopolitical risk, and market sentiment during turbulent times of geopolitical unrest. In a set of parametric and nonparametric quantile-based techniques, we employ daily data on eleven sectors of economic activity in addition to crude oil prices (WTI) and three sentiment-driven indices tracking the crude oil volatility (OVX), geopolitical risk (GPR), and investor sentiment (VIX) over the period between January 2020 and October 2022. Findings from the causality-in-quantile-means test suggest that the sectoral stock returns from the EU are asymmetrically predicted by WTI, OVX, VIX and GPR. The findings from the quantile regression and quantile-on-quantile regression metrics demonstrate that (i) in bearish periods, EU sectoral stocks could hedge against GPR, (ii) WTI does not serve as a hedge for EU stocks regardless of the sector of economic activity, and (iii) OVX and VIX possess some hedging and safe-haven attributes against EU stocks. These findings have notable implications for market regulation and portfolio management.

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  • Bossman, Ahmed & Gubareva, Mariya & Teplova, Tamara, 2023. "EU sectoral stocks amid geopolitical risk, market sentiment, and crude oil implied volatility: An asymmetric analysis of the Russia-Ukraine tensions," Resources Policy, Elsevier, vol. 82(C).
    • Handle: RePEc:eee:jrpoli:v:82:y:2023:i:c:s0301420723002234
    DOI: 10.1016/j.resourpol.2023.103515
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    2. Bossman, Ahmed & Gubareva, Mariya & Teplova, Tamara, 2023. "Asymmetric effects of market uncertainties on agricultural commodities," Energy Economics, Elsevier, vol. 127(PB).
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    5. Khurshid, Adnan & Chen, Yufeng & Rauf, Abdur & Khan, Khalid, 2023. "Critical metals in uncertainty: How Russia-Ukraine conflict drives their prices?," Resources Policy, Elsevier, vol. 85(PB).

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    More about this item

    Keywords

    Geopolitical risk; Economic policy uncertainty; Investor sentiment; Russian-Ukrainian conflict; Causality-in-quantiles; Quantile regression model; Quantile-on-quantile regression; Hedge; Diversification; Safe-haven;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G01 - Financial Economics - - General - - - Financial Crises
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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