IDEAS home Printed from https://ideas.repec.org/a/eco/journ2/2020-05-37.html
   My bibliography  Save this article

Identifying the Dynamic Connectedness between Propane and Oil Prices: Evidence from Wavelet Analysis

Author

Listed:
  • Ngo Thai Hung

    (University of Finance-Marketing, Ho Chi Minh City, Vietnam)

Abstract

This paper takes into account the LPG markets and aims to examine the short run and long run dependencies between crude oil and propane prices during the period 2006-2018. Our empirical study is based on the wavelet transform approach, which allows us to evaluate the co-movement in both time-frequency spaces. The techniques employed on the dataset includes maximal overlap discrete wavelet transform, wavelet covariance, wavelet correlation, continuous wavelet power spectrum, wavelet coherence and wavelet-based Granger causality tests to measure the intercorrelation between crude oil and propane markets. The findings suggest that the existence of strong interconnectedness between crude oil and propane series in the short and medium run. However, there is a unidirectional impact of propane returns on crude oil markets in the very long term. Furthermore, we construct the wavelet-based Granger causality test at different time scales to provide additional support to our nexus results. Our results provide significant implications for policymakers, portfolio managers, and practitioners who are invited to consider the dynamics of return and volatility spillovers between crude oil and propane markets to create sound policy based on a clear comprehension of the transmission between these markets.

Suggested Citation

  • Ngo Thai Hung, 2020. "Identifying the Dynamic Connectedness between Propane and Oil Prices: Evidence from Wavelet Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 315-326.
  • Handle: RePEc:eco:journ2:2020-05-37
    as

    Download full text from publisher

    File URL: https://www.econjournals.com/index.php/ijeep/article/download/9631/5290
    Download Restriction: no

    File URL: https://www.econjournals.com/index.php/ijeep/article/view/9631/5290
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2020. "Dynamic frequency connectedness between oil and natural gas volatilities," Economic Modelling, Elsevier, vol. 84(C), pages 181-189.
    2. 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.
    3. Caporin, Massimiliano & Chang, Chia-Lin & McAleer, Michael, 2019. "Are the S&P 500 index and crude oil, natural gas and ethanol futures related for intra-day data?," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 50-70.
    4. Shekhar Mishra & Avik Sinha & Arshian Sharif & Norazah Mohd Suki, 2020. "Dynamic linkages between tourism, transportation, growth and carbon emission in the USA: evidence from partial and multiple wavelet coherence," Current Issues in Tourism, Taylor & Francis Journals, vol. 23(21), pages 2733-2755, November.
    5. David J. Ramberg and John E. Parsons, 2012. "The Weak Tie Between Natural Gas and Oil Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    6. Tiwari, Aviral Kumar & Khalfaoui, Rabeh & Solarin, Sakiru Adebola & Shahbaz, Muhammad, 2018. "Analyzing the time-frequency lead–lag relationship between oil and agricultural commodities," Energy Economics, Elsevier, vol. 76(C), pages 470-494.
    7. Ederington, Louis H. & Fernando, Chitru S. & Hoelscher, Seth A. & Lee, Thomas K. & Linn, Scott C., 2019. "A review of the evidence on the relation between crude oil prices and petroleum product prices," Journal of Commodity Markets, Elsevier, vol. 13(C), pages 1-15.
    8. Arfaoui, Mongi, 2018. "On the spot-futures relationship in crude-refined petroleum prices: New evidence from an ARDL bounds testing approach," Journal of Commodity Markets, Elsevier, vol. 11(C), pages 48-58.
    9. Wenming Shi & Zhongzhi Yang & Kevin X. Li, 2013. "The impact of crude oil price on the tanker market," Maritime Policy & Management, Taylor & Francis Journals, vol. 40(4), pages 309-322, July.
    10. Al-Sharkas, A.A., 2004. "Dynamic Relations Between Macroeconomic Factors and the Jordanian Stock Market," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 1(1), pages 97-114.
    11. Atle Oglend, Morten E. Lindbäck, and Petter Osmundsen, 2015. "Shale Gas Boom Affecting the Relationship Between LPG and Oil Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    12. Yang, Lu & Cai, Xiao Jing & Zhang, Huimin & Hamori, Shigeyuki, 2016. "Interdependence of foreign exchange markets: A wavelet coherence analysis," Economic Modelling, Elsevier, vol. 55(C), pages 6-14.
    13. Tun‐Hsiang (Edward) Yu & David A. Bessler & Stephen W. Fuller, 2007. "Price Dynamics in U.S. Grain and Freight Markets," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 55(3), pages 381-397, September.
    14. Bai, Xiwen & Lam, Jasmine Siu Lee, 2019. "A copula-GARCH approach for analyzing dynamic conditional dependency structure between liquefied petroleum gas freight rate, product price arbitrage and crude oil price," Energy Economics, Elsevier, vol. 78(C), pages 412-427.
    15. Polanco-Martínez, J.M. & Fernández-Macho, J. & Neumann, M.B. & Faria, S.H., 2018. "A pre-crisis vs. crisis analysis of peripheral EU stock markets by means of wavelet transform and a nonlinear causality test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1211-1227.
    16. Raza, Syed Ali & Shahbaz, Muhammad & Amir-ud-Din, Rafi & Sbia, Rashid & Shah, Nida, 2018. "Testing for wavelet based time-frequency relationship between oil prices and US economic activity," Energy, Elsevier, vol. 154(C), pages 571-580.
    17. Asche, Frank & Gjolberg, Ole & Volker, Teresa, 2003. "Price relationships in the petroleum market: an analysis of crude oil and refined product prices," Energy Economics, Elsevier, vol. 25(3), pages 289-301, May.
    18. Aloui, Chaker & Hkiri, Besma, 2014. "Co-movements of GCC emerging stock markets: New evidence from wavelet coherence analysis," Economic Modelling, Elsevier, vol. 36(C), pages 421-431.
    19. Raza, Syed Ali & Shah, Nida & Sharif, Arshian, 2019. "Time frequency relationship between energy consumption, economic growth and environmental degradation in the United States: Evidence from transportation sector," Energy, Elsevier, vol. 173(C), pages 706-720.
    20. Sun, Xiaolei & Tang, Ling & Yang, Yuying & Wu, Dengsheng & Li, Jianping, 2014. "Identifying the dynamic relationship between tanker freight rates and oil prices: In the perspective of multiscale relevance," Economic Modelling, Elsevier, vol. 42(C), pages 287-295.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bai, Xiwen & Lam, Jasmine Siu Lee, 2019. "A copula-GARCH approach for analyzing dynamic conditional dependency structure between liquefied petroleum gas freight rate, product price arbitrage and crude oil price," Energy Economics, Elsevier, vol. 78(C), pages 412-427.
    2. Ngo Thai HUNG, 2022. "Re-Study on Dynamic Connectedness between Macroeconomic Indicators and the Stock Market in China," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 104-124, April.
    3. Albulescu, Claudiu Tiberiu & Mutascu, Mihai Ioan, 2021. "Fuel price co-movements among France, Germany and Italy: A time-frequency investigation," Energy, Elsevier, vol. 225(C).
    4. Zhang, Hao & Cai, Guixin & Yang, Dongxiao, 2020. "The impact of oil price shocks on clean energy stocks: Fresh evidence from multi-scale perspective," Energy, Elsevier, vol. 196(C).
    5. D. O. Olayungbo & T. A. Ojeyinka, 2022. "Crude oil prices pass-through to retail petroleum product prices in Nigeria: evidence from hidden cointegration approach," Economic Change and Restructuring, Springer, vol. 55(2), pages 951-972, May.
    6. Saba Qureshi & Muhammad Aftab, 2023. "Exchange Rate Interdependence in ASEAN Markets: A Wavelet Analysis," Global Business Review, International Management Institute, vol. 24(6), pages 1180-1204, December.
    7. Muhammad Azmat Hayat & Huma Ghulam & Maryam Batool & Muhammad Zahid Naeem & Abdullah Ejaz & Cristi Spulbar & Ramona Birau, 2021. "Investigating the Causal Linkages among Inflation, Interest Rate, and Economic Growth in Pakistan under the Influence of COVID-19 Pandemic: A Wavelet Transformation Approach," JRFM, MDPI, vol. 14(6), pages 1-22, June.
    8. Gong, Yuting & Li, Kevin X. & Chen, Shu-Ling & Shi, Wenming, 2020. "Contagion risk between the shipping freight and stock markets: Evidence from the recent US-China trade war," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    9. Chiappini, Raphaël & Jégourel, Yves & Raymond, Paul, 2019. "Towards a worldwide integrated market? New evidence on the dynamics of U.S., European and Asian natural gas prices," Energy Economics, Elsevier, vol. 81(C), pages 545-565.
    10. Zhao, Lu-Tao & Zheng, Zhi-Yi & Wei, Yi-Ming, 2023. "Forecasting oil inventory changes with Google trends: A hybrid wavelet decomposer and ARDL-SVR ensemble model," Energy Economics, Elsevier, vol. 120(C).
    11. Tong, Yuan & Wan, Ning & Dai, Xingyu & Bi, Xiaoyi & Wang, Qunwei, 2022. "China's energy stock market jumps: To what extent does the COVID-19 pandemic play a part?," Energy Economics, Elsevier, vol. 109(C).
    12. Bakhat, Mohcine & Rosselló, Jaume & Sansó, Andreu, 2022. "Price transmission between oil and gasoline and diesel: A new measure for evaluating time asymmetries," Energy Economics, Elsevier, vol. 106(C).
    13. Ederington, Louis H. & Fernando, Chitru S. & Lee, Thomas K. & Linn, Scott C. & Zhang, Huiming, 2021. "The relation between petroleum product prices and crude oil prices," Energy Economics, Elsevier, vol. 94(C).
    14. Elsayed, Ahmed H. & Nasreen, Samia & Tiwari, Aviral Kumar, 2020. "Time-varying co-movements between energy market and global financial markets: Implication for portfolio diversification and hedging strategies," Energy Economics, Elsevier, vol. 90(C).
    15. Meng, Xiangcai & Huang, Chia-Hsing, 2019. "The time-frequency co-movement of Asian effective exchange rates: A wavelet approach with daily data," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 131-148.
    16. Bai, Xiwen, 2021. "Tanker freight rates and economic policy uncertainty: A wavelet-based copula approach," Energy, Elsevier, vol. 235(C).
    17. Chen, Qitong & Zhu, Huiming & Yu, Dongwei & Hau, Liya, 2022. "How does investor attention matter for crude oil prices and returns? Evidence from time-frequency quantile causality analysis," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    18. Farid, Saqib & Karim, Sitara & Naeem, Muhammad A. & Nepal, Rabindra & Jamasb, Tooraj, 2023. "Co-movement between dirty and clean energy: A time-frequency perspective," Energy Economics, Elsevier, vol. 119(C).
    19. Hoque, Mohammad Enamul & Soo-Wah, Low & Billah, Mabruk, 2023. "Time-frequency connectedness and spillover among carbon, climate, and energy futures: Determinants and portfolio risk management implications," Energy Economics, Elsevier, vol. 127(PB).
    20. Ahmed, Walid M.A., 2022. "On the higher-order moment interdependence of stock and commodity markets: A wavelet coherence analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 135-151.

    More about this item

    Keywords

    Crude oil; liquefied petroleum gas; co-movement; wavelet analysis; propane.;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F30 - International Economics - - International Finance - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eco:journ2:2020-05-37. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ilhan Ozturk (email available below). General contact details of provider: http://www.econjournals.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.