IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v217y2021ics0360544220325238.html
   My bibliography  Save this article

Relationships and portfolios between oil and Chinese stock sectors: A study based on wavelet denoising-higher moments perspective

Author

Listed:
  • Zhu, Pengfei
  • Tang, Yong
  • Wei, Yu
  • Dai, Yimin
  • Lu, Tuantuan

Abstract

Shanghai crude oil futures contracts (SC) has been the third largest trading volume crude oil futures worldwide. From wavelet denoising-higher moment perspective, we investigate the relationships and portfolios between oil and Chinese stock sectors, based on the daily data of WTI, SC and Chinese sectors. Given the existence of noise and time-varying conditional higher moments in financial data, the Wavelet denoising-GARCHSK and Wavelet denoising-GARCHSK-Copula portfolio methods are proposed to model the margin of variables and construct oil-stock portfolios, respectively. The empirical results indicate that the Wavelet denoising-GARCHSK outperforms the other methods in terms of log likelihood, AIC and BIC. Then, these results also denote that there are the notable industry characteristics in the oil-stock relationships, depending on whether the sector is petroleum-dependent or petroleum-independent as well as locates upstream or downstream of petrochemical industry. In addition, most of the Chinese stock sectors have stronger upper tail dependence with SC than WTI, while the lower tail is the opposite. Finally, it is discovered that the oil-stock portfolios obtained by Wavelet denoising-GARCHSK-Copula portfolio model outperform the control groups in terms of return and ASR and that WTI is a better diversifier for investors in Chinese stock market in most cases.

Suggested Citation

  • Zhu, Pengfei & Tang, Yong & Wei, Yu & Dai, Yimin & Lu, Tuantuan, 2021. "Relationships and portfolios between oil and Chinese stock sectors: A study based on wavelet denoising-higher moments perspective," Energy, Elsevier, vol. 217(C).
    • Handle: RePEc:eee:energy:v:217:y:2021:i:c:s0360544220325238
    DOI: 10.1016/j.energy.2020.119416
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544220325238
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2020.119416?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yue, Wei & Wang, Yuping, 2017. "A new fuzzy multi-objective higher order moment portfolio selection model for diversified portfolios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 124-140.
    2. Elie, Bouri & Naji, Jalkh & Dutta, Anupam & Uddin, Gazi Salah, 2019. "Gold and crude oil as safe-haven assets for clean energy stock indices: Blended copulas approach," Energy, Elsevier, vol. 178(C), pages 544-553.
    3. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Huang, Xuan, 2015. "Identifying the multiscale impacts of crude oil price shocks on the stock market in China at the sector level," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 434(C), pages 13-24.
    4. Shaogao Lv & Yongchao Hou & Hongwei Zhou, 2019. "Financial Market Directional Forecasting With Stacked Denoising Autoencoder," Papers 1912.00712, arXiv.org.
    5. Chen, Yufeng & Zheng, Biao & Qu, Fang, 2020. "Modeling the nexus of crude oil, new energy and rare earth in China: An asymmetric VAR-BEKK (DCC)-GARCH approach," Resources Policy, Elsevier, vol. 65(C).
    6. Aloui, Riadh & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2013. "A time-varying copula approach to oil and stock market dependence: The case of transition economies," Energy Economics, Elsevier, vol. 39(C), pages 208-221.
    7. Lv, Fei & Yang, Chen & Fang, Libing, 2020. "Do the crude oil futures of the Shanghai International Energy Exchange improve asset allocation of Chinese petrochemical-related stocks?," International Review of Financial Analysis, Elsevier, vol. 71(C).
    8. Dariush Khezrimotlagh & Yao Chen, 2018. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 217-234, Springer.
    9. Yang, Liansheng & Zhu, Yingming & Wang, Yudong & Wang, Yiqi, 2016. "Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 255-265.
    10. El Hedi Arouri, Mohamed & Jouini, Jamel & Nguyen, Duc Khuong, 2011. "Volatility spillovers between oil prices and stock sector returns: Implications for portfolio management," Journal of International Money and Finance, Elsevier, vol. 30(7), pages 1387-1405.
    11. Huang, Shupei & An, Haizhong & Huang, Xuan & Jia, Xiaoliang, 2018. "Co-movement of coherence between oil prices and the stock market from the joint time-frequency perspective," Applied Energy, Elsevier, vol. 221(C), pages 122-130.
    12. Chen, Mei-Ping & Chen, Wen-Yi & Tseng, Tseng-Chan, 2017. "Co-movements of returns in the health care sectors from the US, UK, and Germany stock markets: Evidence from the continuous wavelet analyses," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 484-498.
    13. Liu, Xueyong & An, Haizhong & Huang, Shupei & Wen, Shaobo, 2017. "The evolution of spillover effects between oil and stock markets across multi-scales using a wavelet-based GARCH–BEKK model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 374-383.
    14. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Huang, Xuan, 2016. "Time–frequency featured co-movement between the stock and prices of crude oil and gold," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 985-995.
    15. Sukcharoen, Kunlapath & Zohrabyan, Tatevik & Leatham, David & Wu, Ximing, 2014. "Interdependence of oil prices and stock market indices: A copula approach," Energy Economics, Elsevier, vol. 44(C), pages 331-339.
    16. Badeeb, Ramez Abubakr & Lean, Hooi Hooi, 2018. "Asymmetric impact of oil price on Islamic sectoral stocks," Energy Economics, Elsevier, vol. 71(C), pages 128-139.
    17. Ping, Li & Ziyi, Zhang & Tianna, Yang & Qingchao, Zeng, 2018. "The relationship among China’s fuel oil spot, futures and stock markets," Finance Research Letters, Elsevier, vol. 24(C), pages 151-162.
    18. Basher, Syed Abul & Sadorsky, Perry, 2016. "Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH," Energy Economics, Elsevier, vol. 54(C), pages 235-247.
    19. Zhu, Pengfei & Tang, Yong & Wei, Yu & Dai, Yimin, 2019. "Portfolio strategy of International crude oil markets: A study based on multiwavelet denoising-integration MF-DCCA method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    20. Wu, Xinyu & Xia, Michelle & Zhang, Huanming, 2020. "Forecasting VaR using realized EGARCH model with skewness and kurtosis," Finance Research Letters, Elsevier, vol. 32(C).
    21. Kayalar, Derya Ezgi & Küçüközmen, C. Coşkun & Selcuk-Kestel, A. Sevtap, 2017. "The impact of crude oil prices on financial market indicators: copula approach," Energy Economics, Elsevier, vol. 61(C), pages 162-173.
    22. Wang, Xunxiao & Wang, Yudong, 2019. "Volatility spillovers between crude oil and Chinese sectoral equity markets: Evidence from a frequency dynamics perspective," Energy Economics, Elsevier, vol. 80(C), pages 995-1009.
    23. Antonakakis, Nikolaos & Cunado, Juncal & Filis, George & Gabauer, David & Perez de Gracia, Fernando, 2018. "Oil volatility, oil and gas firms and portfolio diversification," Energy Economics, Elsevier, vol. 70(C), pages 499-515.
    24. Ma, Yan-Ran & Zhang, Dayong & Ji, Qiang & Pan, Jiaofeng, 2019. "Spillovers between oil and stock returns in the US energy sector: Does idiosyncratic information matter?," Energy Economics, Elsevier, vol. 81(C), pages 536-544.
    25. Hedi Arouri, Mohamed El & Khuong Nguyen, Duc, 2010. "Oil prices, stock markets and portfolio investment: Evidence from sector analysis in Europe over the last decade," Energy Policy, Elsevier, vol. 38(8), pages 4528-4539, August.
    26. Sun, Edward W. & Meinl, Thomas, 2012. "A new wavelet-based denoising algorithm for high-frequency financial data mining," European Journal of Operational Research, Elsevier, vol. 217(3), pages 589-599.
    27. Jang, Jeewon & Kang, Jangkoo, 2017. "An intertemporal CAPM with higher-order moments," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 314-337.
    28. Ashfaq, Saleha & Tang, Yong & Maqbool, Rashid, 2019. "Volatility spillover impact of world oil prices on leading Asian energy exporting and importing economies’ stock returns," Energy, Elsevier, vol. 188(C).
    29. Lin, Boqiang & Wesseh, Presley K. & Appiah, Michael Owusu, 2014. "Oil price fluctuation, volatility spillover and the Ghanaian equity market: Implication for portfolio management and hedging effectiveness," Energy Economics, Elsevier, vol. 42(C), pages 172-182.
    30. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2018. "Addressing COP21 using a stock and oil market integration index," Energy Policy, Elsevier, vol. 116(C), pages 127-136.
    31. Natanelov, Valeri & Alam, Mohammad J. & McKenzie, Andrew M. & Van Huylenbroeck, Guido, 2011. "Is there co-movement of agricultural commodities futures prices and crude oil?," Energy Policy, Elsevier, vol. 39(9), pages 4971-4984, September.
    32. Narayan, Paresh Kumar & Liu, Ruipeng, 2018. "A new GARCH model with higher moments for stock return predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 56(C), pages 93-103.
    33. Leon, Angel & Rubio, Gonzalo & Serna, Gregorio, 2005. "Autoregresive conditional volatility, skewness and kurtosis," The Quarterly Review of Economics and Finance, Elsevier, vol. 45(4-5), pages 599-618, September.
    34. Jian Yang & Yinggang Zhou, 2020. "Return and volatility transmission between China's and international crude oil futures markets: A first look," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(6), pages 860-884, June.
    35. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    36. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-844.
    37. Lin, Chu-Hsiung & Changchien, Chang-Cheng & Kao, Tzu-Chuan & Kao, Wei-Shun, 2014. "High-order moments and extreme value approach for value-at-risk," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 421-434.
    38. Khalfaoui, Rabeh & Sarwar, Suleman & Tiwari, Aviral Kumar, 2019. "Analysing volatility spillover between the oil market and the stock market in oil-importing and oil-exporting countries: Implications on portfolio management," Resources Policy, Elsevier, vol. 62(C), pages 22-32.
    39. Mitra, Subrata Kumar & Bhatia, Vaneet & Jana, R.K. & Charan, Parikshit & Chattopadhyay, Manojit, 2018. "Changing value detrended cross correlation coefficient over time: Between crude oil and crop prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 671-678.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Lee, Hsiang-Tai, 2022. "Regime-switching angular correlation diversification," Finance Research Letters, Elsevier, vol. 50(C).
    3. Zheng, Chengli & Su, Kuangxi & Yao, Yinhong, 2021. "Hedging futures performance with denoising and noise-assisted strategies," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    4. Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2023. "Quantile spillovers and connectedness analysis between oil and African stock markets," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 60-83.
    5. Zhou, Yuqin & Wu, Shan & Zhang, Zeyi, 2022. "Multidimensional risk spillovers among carbon, energy and nonferrous metals markets: Evidence from the quantile VAR network," Energy Economics, Elsevier, vol. 114(C).
    6. Wang, Zi-Xin & Liu, Bing-Yue & Fan, Ying, 2023. "Network connectedness between China's crude oil futures and sector stock indices," Energy Economics, Elsevier, vol. 125(C).
    7. Mensi, Walid & Al Rababa'a, Abdel Razzaq & Alomari, Mohammad & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Dynamic frequency volatility spillovers and connectedness between strategic commodity and stock markets: US-based sectoral analysis," Resources Policy, Elsevier, vol. 79(C).
    8. Mensi, Walid & Yousaf, Imran & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Asymmetric spillover and network connectedness between gold, BRENT oil and EU subsector markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    9. Ghaemi Asl, Mahdi & Adekoya, Oluwasegun Babatunde & Rashidi, Muhammad Mahdi & Ghasemi Doudkanlou, Mohammad & Dolatabadi, Ali, 2022. "Forecast of Bayesian-based dynamic connectedness between oil market and Islamic stock indices of Islamic oil-exporting countries: Application of the cascade-forward backpropagation network," Resources Policy, Elsevier, vol. 77(C).
    10. Kuangxi Su & Yinhong Yao & Chengli Zheng & Wenzhao Xie, 2024. "Portfolio Selection Based on EMD Denoising with Correlation Coefficient Test Criterion," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 391-421, January.
    11. Zhu, Pengfei & Tang, Yong & Wei, Yu & Lu, Tuantuan, 2021. "Multidimensional risk spillovers among crude oil, the US and Chinese stock markets: Evidence during the COVID-19 epidemic," Energy, Elsevier, vol. 231(C).
    12. Shao Ying-Hui & Liu Ying-Lin & Yang Yan-Hong, 2022. "The short-term effect of COVID-19 pandemic on China's crude oil futures market: A study based on multifractal analysis," Papers 2204.05199, arXiv.org.
    13. Chen, Ying & Zhu, Xuehong & Chen, Jinyu, 2022. "Spillovers and hedging effectiveness of non-ferrous metals and sub-sectoral clean energy stocks in time and frequency domain," Energy Economics, Elsevier, vol. 111(C).

    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. Zhu, Pengfei & Tang, Yong & Wei, Yu & Lu, Tuantuan, 2021. "Multidimensional risk spillovers among crude oil, the US and Chinese stock markets: Evidence during the COVID-19 epidemic," Energy, Elsevier, vol. 231(C).
    2. Asl, Mahdi Ghaemi & Canarella, Giorgio & Miller, Stephen M., 2021. "Dynamic asymmetric optimal portfolio allocation between energy stocks and energy commodities: Evidence from clean energy and oil and gas companies," Resources Policy, Elsevier, vol. 71(C).
    3. Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    4. Imran Yousaf & Shoaib Ali & Muhammad Naveed & Ifraz Adeel, 2021. "Risk and Return Transmissions From Crude Oil to Latin American Stock Markets During the Crisis: Portfolio Implications," SAGE Open, , vol. 11(2), pages 21582440211, April.
    5. Ghaemi Asl, Mahdi & Adekoya, Oluwasegun Babatunde & Rashidi, Muhammad Mahdi & Ghasemi Doudkanlou, Mohammad & Dolatabadi, Ali, 2022. "Forecast of Bayesian-based dynamic connectedness between oil market and Islamic stock indices of Islamic oil-exporting countries: Application of the cascade-forward backpropagation network," Resources Policy, Elsevier, vol. 77(C).
    6. Tsuji, Chikashi, 2018. "New DCC analyses of return transmission, volatility spillovers, and optimal hedging among oil futures and oil equities in oil-producing countries," Applied Energy, Elsevier, vol. 229(C), pages 1202-1217.
    7. Sarwar, Suleman & Shahbaz, Muhammad & Anwar, Awais & Tiwari, Aviral Kumar, 2019. "The importance of oil assets for portfolio optimization: The analysis of firm level stocks," Energy Economics, Elsevier, vol. 78(C), pages 217-234.
    8. Kang, Sang Hoon & Arreola Hernandez, Jose & Rehman, Mobeen Ur & Shahzad, Syed Jawad Hussain & Yoon, Seong-Min, 2023. "Spillovers and hedging between US equity sectors and gold, oil, islamic stocks and implied volatilities," Resources Policy, Elsevier, vol. 81(C).
    9. Sarwar, Suleman & Khalfaoui, Rabeh & Waheed, Rida & Dastgerdi, Hamidreza Ghorbani, 2019. "Volatility spillovers and hedging: Evidence from Asian oil-importing countries," Resources Policy, Elsevier, vol. 61(C), pages 479-488.
    10. Khalfaoui, Rabeh & Sarwar, Suleman & Tiwari, Aviral Kumar, 2019. "Analysing volatility spillover between the oil market and the stock market in oil-importing and oil-exporting countries: Implications on portfolio management," Resources Policy, Elsevier, vol. 62(C), pages 22-32.
    11. Kuang, Wei, 2023. "The equity-oil hedge: A comparison between volatility and alternative risk frameworks," Energy, Elsevier, vol. 271(C).
    12. Belhassine, Olfa & Karamti, Chiraz, 2021. "Volatility spillovers and hedging effectiveness between oil and stock markets: Evidence from a wavelet-based and structural breaks analysis," Energy Economics, Elsevier, vol. 102(C).
    13. Cui, Jinxin & Goh, Mark & Li, Binlin & Zou, Huiwen, 2021. "Dynamic dependence and risk connectedness among oil and stock markets: New evidence from time-frequency domain perspectives," Energy, Elsevier, vol. 216(C).
    14. Hou, Yang & Li, Steven & Wen, Fenghua, 2019. "Time-varying volatility spillover between Chinese fuel oil and stock index futures markets based on a DCC-GARCH model with a semi-nonparametric approach," Energy Economics, Elsevier, vol. 83(C), pages 119-143.
    15. Hassan, Kamrul & Hoque, Ariful & Gasbarro, Dominic, 2019. "Separating BRIC using Islamic stocks and crude oil: dynamic conditional correlation and volatility spillover analysis," Energy Economics, Elsevier, vol. 80(C), pages 950-969.
    16. Belhassine, Olfa, 2020. "Volatility spillovers and hedging effectiveness between the oil market and Eurozone sectors: A tale of two crises," Research in International Business and Finance, Elsevier, vol. 53(C).
    17. Iglesias-Casal, Ana & López-Penabad, María-Celia & López-Andión, Carmen & Maside-Sanfiz, José Manuel, 2020. "Diversification and optimal hedges for socially responsible investment in Brazil," Economic Modelling, Elsevier, vol. 85(C), pages 106-118.
    18. Esparcia, Carlos & Jareño, Francisco & Umar, Zaghum, 2022. "Revisiting the safe haven role of Gold across time and frequencies during the COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    19. Yousaf, Imran & Beljid, Makram & Chaibi, Anis & Ajlouni, Ahmed AL, 2022. "Do volatility spillover and hedging among GCC stock markets and global factors vary from normal to turbulent periods? Evidence from the global financial crisis and Covid-19 pandemic crisis," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
    20. Mensi, Walid & Al Rababa'a, Abdel Razzaq & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Asymmetric spillover and network connectedness between crude oil, gold, and Chinese sector stock markets," Energy Economics, Elsevier, vol. 98(C).

    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:eee:energy:v:217:y:2021:i:c:s0360544220325238. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.