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Wavelet dynamics for oil-stock world interactions

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  • Madaleno, Mara
  • Pinho, Carlos

Abstract

A previous research ignores the distinction between short term and long term, and by decomposing financial variables (world general and stock market indexes) and the macroeconomic variable (oil prices) at various time scales, we study the relationship among series on a daily scale by scale basis. Continuous time wavelets help to circumvent the problems associated to basic linear regressions and given that stock-oil relationships are usually described as complicated we extend previous findings by providing more generalized and convincing results, in analyzing contagion and interdependence issues as well as lead and lag effects for both world general and sector stock levels between December 1992 and October 2012. The relationship between oil prices and sector stock returns is ambiguous, because results seem to show that there are both phase and anti-phase relationships, where mostly it is oil that is the lagging variable, independently of the sector under analysis. There is higher coherence among series for higher scales thus supporting the interdependence hypothesis, showing that long run market dynamics are more uncertain. Empirical results indicate a bidirectional relationship between both series for large time horizons, which can be associated to fundamentalist traders, especially fund managers and institutional investors, and which depend on the historical period under analysis.

Suggested Citation

  • Madaleno, Mara & Pinho, Carlos, 2014. "Wavelet dynamics for oil-stock world interactions," Energy Economics, Elsevier, vol. 45(C), pages 120-133.
  • Handle: RePEc:eee:eneeco:v:45:y:2014:i:c:p:120-133
    DOI: 10.1016/j.eneco.2014.06.024
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    References listed on IDEAS

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    Cited by:

    1. Bilgili, Faik & Mugaloglu, Erhan & Koçak, Emrah, 2018. "The impact of oil prices on CO2 emissions in China: A Wavelet coherence approach," MPRA Paper 90170, University Library of Munich, Germany.
    2. repec:eee:finlet:v:24:y:2018:i:c:p:56-63 is not listed on IDEAS
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    4. repec:eee:energy:v:139:y:2017:i:c:p:617-629 is not listed on IDEAS
    5. repec:eee:ecmode:v:76:y:2019:i:c:p:172-181 is not listed on IDEAS
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    7. Caporale, Guglielmo Maria & Menla Ali, Faek & Spagnolo, Nicola, 2015. "Oil price uncertainty and sectoral stock returns in China: A time-varying approach," China Economic Review, Elsevier, vol. 34(C), pages 311-321.
    8. William Barnett & Zied Ftiti & Fredj Jawadi, 2018. "The Causal Relationships between Inflation and Inflation Uncertainty," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201803, University of Kansas, Department of Economics, revised Mar 2018.
    9. repec:eee:rensus:v:107:y:2019:i:c:p:1-19 is not listed on IDEAS
    10. Ftiti, Zied & Guesmi, Khaled & Abid, Ilyes, 2016. "Oil price and stock market co-movement: What can we learn from time-scale approaches?," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 266-280.
    11. repec:eee:eneeco:v:71:y:2018:i:c:p:253-272 is not listed on IDEAS
    12. repec:kap:rqfnac:v:51:y:2018:i:2:d:10.1007_s11156-017-0672-7 is not listed on IDEAS
    13. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Ugolini, Andrea, 2017. "Wavelet-based test of co-movement and causality between oil and renewable energy stock prices," Energy Economics, Elsevier, vol. 61(C), pages 241-252.
    14. Nagayev, Ruslan & Disli, Mustafa & Inghelbrecht, Koen & Ng, Adam, 2016. "On the dynamic links between commodities and Islamic equity," Energy Economics, Elsevier, vol. 58(C), pages 125-140.
    15. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Hao, Xiaoqing, 2016. "Unveiling heterogeneities of relations between the entire oil–stock interaction and its components across time scales," Energy Economics, Elsevier, vol. 59(C), pages 70-80.

    More about this item

    Keywords

    Oil price changes; Continuous wavelets; Sector stock markets; World index;

    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
    • F01 - International Economics - - General - - - Global Outlook
    • O50 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - General
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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