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An empirical study on information spillover effects between the Chinese copper futures market and spot market

Author Info

Listed author(s):
  • Liu, Xiangli
  • Cheng, Siwei
  • Wang, Shouyang
  • Hong, Yongmiao
  • Li, Yi
Registered author(s):

    Abstract

    This study employs a parametric approach based on TGARCH and GARCH models to estimate the VaR of the copper futures market and spot market in China. Considering the short selling mechanism in the futures market, the paper introduces two new notions: upside VaR and extreme upside risk spillover. And downside VaR and upside VaR are examined by using the above approach. Also, we use Kupiec’s [P.H. Kupiec, Techniques for verifying the accuracy of risk measurement models, Journal of Derivatives 3 (1995) 73–84] backtest to test the power of our approaches. In addition, we investigate information spillover effects between the futures market and the spot market by employing a linear Granger causality test, and Granger causality tests in mean, volatility and risk respectively. Moreover, we also investigate the relationship between the futures market and the spot market by using a test based on a kernel function. Empirical results indicate that there exist significant two-way spillovers between the futures market and the spot market, and the spillovers from the futures market to the spot market are much more striking.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0378437107010230
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    Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

    Volume (Year): 387 (2008)
    Issue (Month): 4 ()
    Pages: 899-914

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    Handle: RePEc:eee:phsmap:v:387:y:2008:i:4:p:899-914
    DOI: 10.1016/j.physa.2007.09.044
    Contact details of provider: Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

    Keywords: Futures market; Kernel function; Backtest; Information spillover; Granger causality; Conditional VaR; Extreme upside risk; Extreme downside risk;

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    1. Hasbrouck, Joel, 1995. " One Security, Many Markets: Determining the Contributions to Price Discovery," Journal of Finance, American Finance Association, vol. 50(4), pages 1175-1199, September.
    2. Giorgio Valente & Lucio Sarno, 2005. "Modelling and forecasting stock returns: exploiting the futures market, regime shifts and international spillovers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(3), pages 345-376.
    3. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    4. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    5. Sequeira, John M & Chiat, Pang Chia & McAleer, Michael, 2004. "Volatility models of currency futures in developed and emerging markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 64(1), pages 79-93.
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    8. Granger, C. W. J., 1980. "Testing for causality : A personal viewpoint," Journal of Economic Dynamics and Control, Elsevier, vol. 2(1), pages 329-352, May.
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    Cited by:

    1. Atukeren, Erdal & Cevik, Emrah Ismail & Korkmaz, Turhan, 2015. "Downside Business Confidence Spillovers in Europe: Evidence from Causality-in-Risk Tests," MPRA Paper 76038, University Library of Munich, Germany.
    2. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2011. "Structural changes and volatility transmission in crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4317-4324.
    3. Todorova, Neda & Worthington, Andrew & Souček, Michael, 2014. "Realized volatility spillovers in the non-ferrous metal futures market," Resources Policy, Elsevier, vol. 39(C), pages 21-31.
    4. Liu, Xueyong & An, Haizhong & Li, Huajiao & Chen, Zhihua & Feng, Sida & Wen, Shaobo, 2017. "Features of spillover networks in international financial markets: Evidence from the G20 countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 265-278.
    5. Todorova, Neda, 2015. "The course of realized volatility in the LME non-ferrous metal market," Economic Modelling, Elsevier, vol. 51(C), pages 1-12.
    6. Wang, Gang-Jin & Xie, Chi & Jiang, Zhi-Qiang & Stanley, H. Eugene, 2016. "Extreme risk spillover effects in world gold markets and the global financial crisis," International Review of Economics & Finance, Elsevier, vol. 46(C), pages 55-77.
    7. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2013. "Intraday volatility spillovers between spot and futures indices: Evidence from the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1795-1802.
    8. Arık, Evren & Mutlu, Elif, 2014. "Chinese steel market in the post-futures period," Resources Policy, Elsevier, vol. 42(C), pages 10-17.

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