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Does solar activity affect the price of crude oil? A causality and volatility analysis

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  • Daglis, Theodoros
  • Yfanti, Stavroula
  • Xidonas, Panos
  • Konstantakis, Konstantinos N.
  • Michaelides, Panayotis G.

Abstract

This study examines how solar activity affects the oil volatility index. To test whether solar phenomena affect the oil volatility price index, the Granger and Step-by-Step causality techniques are applied. Furthermore, we employ the autoregressive distributed lag order model (ARDL), which introduces as exogenous variables the Dow Jones Equity REIT index, the 3-month U.S. Government bond, the Oil Volatility Index, and the spread. As part of the model, we also include a solar variable, namely, the solar wind velocity, which is one of the most significant characteristics of the solar wind plasma. According to the results, the solar wind velocity "Granger causes" and "step-by-step causes" the oil volatility price index. All variables analyzed provide useful information for the modeling of the oil volatility index, which shows that solar activity does indeed influence the market for oil prices.

Suggested Citation

  • Daglis, Theodoros & Yfanti, Stavroula & Xidonas, Panos & Konstantakis, Konstantinos N. & Michaelides, Panayotis G., 2023. "Does solar activity affect the price of crude oil? A causality and volatility analysis," Finance Research Letters, Elsevier, vol. 55(PA).
    • Handle: RePEc:eee:finlet:v:55:y:2023:i:pa:s1544612323002064
    DOI: 10.1016/j.frl.2023.103833
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    References listed on IDEAS

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    1. Dufour, Jean-Marie & Pelletier, Denis & Renault, Eric, 2006. "Short run and long run causality in time series: inference," Journal of Econometrics, Elsevier, vol. 132(2), pages 337-362, June.
    2. Daglis, Theodoros & Konstantakis, Konstantinos N. & Michaelides, Panayotis G. & Papadakis, Theodoulos Eleftherios, 2020. "The forecasting ability of solar and space weather data on NASDAQ’s finance sector price index volatility," Research in International Business and Finance, Elsevier, vol. 52(C).
    3. Daglis, Theodoros & Konstantakis, Konstantinos N. & Michaelides, Panayotis G., 2019. "Solar events and economic activity: Evidence from the US Telecommunications industry (1996–2014)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    4. Jean-Marie Dufour & Eric Renault, 1998. "Short Run and Long Run Causality in Time Series: Theory," Econometrica, Econometric Society, vol. 66(5), pages 1099-1126, September.
    5. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    6. Jean-Marie Dufour & David Tessier, 2006. "Short-Run and Long-Run Causality between Monetary Policy Variables and Stock Prices," Staff Working Papers 06-39, Bank of Canada.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Oil volatility index; Solar wind; ARDL; Macroeconomic variables;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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