IDEAS home Printed from https://ideas.repec.org/a/eee/quaeco/v68y2018icp23-30.html
   My bibliography  Save this article

Does oil product pricing reform increase returns and uncertainty in the Chinese stock market?

Author

Listed:
  • Wen, Xiaoqian
  • Bouri, Elie
  • Roubaud, David

Abstract

This paper examines whether and to what extent the oil product pricing reform in 2013 has affected uncertainty in the Chinese stock market at both the aggregate and sectoral levels. Based on daily data from 17 March 2011 to 27 March 2015 and univariate GARCH-based modelling augmented with interaction terms, the main empirical results can be summarized as follows: first, the 2013 reform has improved the risk-return pattern of the Chinese aggregate stock market. Second, since the reform, Chinese sectoral stocks have become more sensitive to the price adjustments of oil products. In particular, upward price adjustments impose larger effects on stock market volatility than downward price adjustments, primarily leading to a significant reduction in stock market volatility. Counter-intuitively, the main conclusions show that China’s 2013 oil product pricing reform has significantly reduced the risks of stock investments and financing, implying that a market-oriented pricing mechanism can actually decrease the financial market uncertainty surrounding domestic oil product price adjustments.

Suggested Citation

  • Wen, Xiaoqian & Bouri, Elie & Roubaud, David, 2018. "Does oil product pricing reform increase returns and uncertainty in the Chinese stock market?," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 23-30.
    • Handle: RePEc:eee:quaeco:v:68:y:2018:i:c:p:23-30
    DOI: 10.1016/j.qref.2017.08.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062976917300558
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.qref.2017.08.003?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. Kyrtsou, Catherine & Labys, Walter C., 2007. "Detecting positive feedback in multivariate time series: The case of metal prices and US inflation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 227-229.
    2. Brooks,Chris, 2008. "RATS Handbook to Accompany Introductory Econometrics for Finance," Cambridge Books, Cambridge University Press, number 9780521896955.
    3. Li, Raymond & Leung, Guy C.K., 2011. "The integration of China into the world crude oil market since 1998," Energy Policy, Elsevier, vol. 39(9), pages 5159-5166, September.
    4. Lin, Boqiang & Jiang, Zhujun, 2011. "Estimates of energy subsidies in China and impact of energy subsidy reform," Energy Economics, Elsevier, vol. 33(2), pages 273-283, March.
    5. Moya-Martínez, Pablo & Ferrer-Lapeña, Román & Escribano-Sotos, Francisco, 2014. "Oil price risk in the Spanish stock market: An industry perspective," Economic Modelling, Elsevier, vol. 37(C), pages 280-290.
    6. Hong, Li & Liang, Dong & Di, Wang, 2013. "Economic and environmental gains of China's fossil energy subsidies reform: A rebound effect case study with EIMO model," Energy Policy, Elsevier, vol. 54(C), pages 335-342.
    7. Zhang, Jin & Xie, Mingjia, 2016. "China's oil product pricing mechanism: What role does it play in China's macroeconomy?," China Economic Review, Elsevier, vol. 38(C), pages 209-221.
    8. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    9. Jiang, Zhujun & Tan, Jijun, 2013. "How the removal of energy subsidy affects general price in China: A study based on input–output model," Energy Policy, Elsevier, vol. 63(C), pages 599-606.
    10. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    11. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    12. Li, Ke & Lin, Boqiang, 2015. "How does administrative pricing affect energy consumption and CO2 emissions in China?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 952-962.
    13. Wen, Xiaoqian & Wei, Yu & Huang, Dengshi, 2012. "Measuring contagion between energy market and stock market during financial crisis: A copula approach," Energy Economics, Elsevier, vol. 34(5), pages 1435-1446.
    14. Lin, Boqiang & Liu, Xia, 2013. "Reform of refined oil product pricing mechanism and energy rebound effect for passenger transportation in China," Energy Policy, Elsevier, vol. 57(C), pages 329-337.
    15. Beine, Michel & Laurent, Sebastien, 2003. "Central bank interventions and jumps in double long memory models of daily exchange rates," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 641-660, December.
    16. Guo, Yanfeng & Wen, Xiaoqian & Wu, Yanrui & Guo, Xiumei, 2016. "How is China's coke price related with the world oil price? The role of extreme movements," Economic Modelling, Elsevier, vol. 58(C), pages 22-33.
    17. Fan, Ruguo & Luo, Ming & Zhang, Pengfei, 2016. "A study on evolution of energy intensity in China with heterogeneity and rebound effect," Energy, Elsevier, vol. 99(C), pages 159-169.
    18. Mobarek, Asma & Fiorante, Angelo, 2014. "The prospects of BRIC countries: Testing weak-form market efficiency," Research in International Business and Finance, Elsevier, vol. 30(C), pages 217-232.
    19. Bouri, Elie, 2015. "Oil volatility shocks and the stock markets of oil-importing MENA economies: A tale from the financial crisis," Energy Economics, Elsevier, vol. 51(C), pages 590-598.
    20. Adrian R. Pagan & Kirill A. Sossounov, 2003. "A simple framework for analysing bull and bear markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 23-46.
    21. Reboredo, Juan C. & Wen, Xiaoqian, 2015. "Are China’s new energy stock prices driven by new energy policies?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 624-636.
    22. Yao, Lixia & Chang, Youngho, 2015. "Shaping China's energy security: The impact of domestic reforms," Energy Policy, Elsevier, vol. 77(C), pages 131-139.
    23. Liu, Wei & Li, Hong, 2011. "Improving energy consumption structure: A comprehensive assessment of fossil energy subsidies reform in China," Energy Policy, Elsevier, vol. 39(7), pages 4134-4143, July.
    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. He, Zhifang, 2020. "Dynamic impacts of crude oil price on Chinese investor sentiment: Nonlinear causality and time-varying effect," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 131-153.
    2. 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.
    3. Yue Zhang, 2021. "The COVID-19 Outbreak and Oil Stock Price Fluctuations - Evidence From China," Energy RESEARCH LETTERS, Asia-Pacific Applied Economics Association, vol. 2(3), pages 1-5.
    4. Lin, Ling & Kuang, Yuanpei & Jiang, Yong & Su, Xianfang, 2019. "Assessing risk contagion among the Brent crude oil market, London gold market and stock markets: Evidence based on a new wavelet decomposition approach," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    5. Zhao-Yong Sun & Wei-Chiao Huang, 2023. "The effects of unexpected crude oil price shocks on Chinese stock markets," Economic Change and Restructuring, Springer, vol. 56(3), pages 1683-1697, June.
    6. Niu, Hongli & Hu, Ziang, 2021. "Information transmission and entropy-based network between Chinese stock market and commodity futures market," Resources Policy, Elsevier, vol. 74(C).
    7. Chang, Kai & Ge, Fangping & Zhang, Chao & Wang, Weihong, 2018. "The dynamic linkage effect between energy and emissions allowances price for regional emissions trading scheme pilots in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 415-425.
    8. Stoupos, Nikolaos & Kiohos, Apostolos, 2021. "Energy commodities and advanced stock markets: A post-crisis approach," Resources Policy, Elsevier, vol. 70(C).
    9. 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).

    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. Du, Gang & Sun, Chuanwang & Fang, Zhongnan, 2015. "Evaluating the Atkinson index of household energy consumption in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1080-1087.
    2. Xu, Shang & Zhang, Jun, 2023. "The welfare impacts of removing coal subsidies in rural China," Energy Economics, Elsevier, vol. 118(C).
    3. Al-Khazali, Osamah & Bouri, Elie & Roubaud, David & Zoubi, Taisier, 2017. "The impact of religious practice on stock returns and volatility," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 172-189.
    4. Bouri, Elie & Chen, Qian & Lien, Donald & Lv, Xin, 2017. "Causality between oil prices and the stock market in China: The relevance of the reformed oil product pricing mechanism," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 34-48.
    5. Saeed Solaymani, 2016. "Impacts of energy subsidy reform on poverty and income inequality in Malaysia," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(6), pages 2707-2723, November.
    6. Wen, Xiaoqian & Bouri, Elie & Roubaud, David, 2017. "Can energy commodity futures add to the value of carbon assets?," Economic Modelling, Elsevier, vol. 62(C), pages 194-206.
    7. Bouri, Elie & Jalkh, Naji & Roubaud, David, 2019. "Commodity volatility shocks and BRIC sovereign risk: A GARCH-quantile approach," Resources Policy, Elsevier, vol. 61(C), pages 385-392.
    8. Bouri, Elie & de Boyrie, Maria E. & Pavlova, Ivelina, 2017. "Volatility transmission from commodity markets to sovereign CDS spreads in emerging and frontier countries," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 155-165.
    9. Wei Kuang, 2022. "Oil tail-risk forecasts: from financial crisis to COVID-19," Risk Management, Palgrave Macmillan, vol. 24(4), pages 420-460, December.
    10. Li, Ke & Lin, Boqiang, 2015. "Heterogeneity in rebound effects: Estimated results and impact of China’s fossil-fuel subsidies," Applied Energy, Elsevier, vol. 149(C), pages 148-160.
    11. Alex Huang, 2013. "Value at risk estimation by quantile regression and kernel estimator," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 225-251, August.
    12. M. Hashem Pesaran & Paolo Zaffaroni, 2004. "Model Averaging and Value-at-Risk Based Evaluation of Large Multi Asset Volatility Models for Risk Management," CESifo Working Paper Series 1358, CESifo.
    13. Vincenzo Candila, 2013. "A Comparison of the Forecasting Performances of Multivariate Volatility Models," Working Papers 3_228, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno.
    14. Grané, Aurea & Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    15. Nikkin L. Beronilla & Dennis S. Mapa, 2008. "Range-based models in estimating value-at-risk (VaR)," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 45(2), pages 87-99, December.
    16. Ñíguez, Trino-Manuel & Perote, Javier, 2017. "Moments expansion densities for quantifying financial risk," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 53-69.
    17. Gerlach, Richard & Wang, Chao, 2020. "Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 489-506.
    18. Herrera, R. & Clements, A.E., 2018. "Point process models for extreme returns: Harnessing implied volatility," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 161-175.
    19. Abdul Hakim & Michael McAleer, 2009. "VaR Forecasts and Dynamic Conditional Correlations for Spot and Futures Returns on Stocks and Bonds," CIRJE F-Series CIRJE-F-676, CIRJE, Faculty of Economics, University of Tokyo.
    20. B M, Lithin & chakraborty, Suman & iyer, Vishwanathan & M N, Nikhil & ledwani, Sanket, 2022. "Modeling asymmetric sovereign bond yield volatility with univariate GARCH models: Evidence from India," MPRA Paper 117067, University Library of Munich, Germany, revised 05 Jan 2023.

    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:quaeco:v:68:y:2018:i:c:p:23-30. 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.elsevier.com/locate/inca/620167 .

    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.