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Which liquidity indicator is more informative to market volatility? Spectrum analysis of China’s base metal futures market

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  • Chen, Xiangyu
  • Tongurai, Jittima

Abstract

By applying the frequency domain causality test and cross-spectral coherence analysis, this study investigates the informational effects of liquidity indicators on the volatility of China’s base metal futures market from January 2016 to June 2022. We find that trading volume is more informative in economically explaining the price variations of most base metal futures for all frequency horizons, while open interest is more informative to Granger-cause economic innovations in the market volatility of the lead and nickel futures markets both in the short and long run. The coherence levels between the underlying frequency components for open interest are found to be greater than those for trading volume, suggesting that price volatility in China’s base metal futures market would be more responsive to shocks in open interest.

Suggested Citation

  • Chen, Xiangyu & Tongurai, Jittima, 2023. "Which liquidity indicator is more informative to market volatility? Spectrum analysis of China’s base metal futures market," The North American Journal of Economics and Finance, Elsevier, vol. 68(C).
    • Handle: RePEc:eee:ecofin:v:68:y:2023:i:c:s1062940823000852
    DOI: 10.1016/j.najef.2023.101962
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    1. Karkowska, Renata & Palczewski, Andrzej, 2023. "Does high-frequency trading actually improve market liquidity? A comparative study for selected models and measures," Research in International Business and Finance, Elsevier, vol. 64(C).
    2. Bessembinder, Hendrik & Chan, Kalok & Seguin, Paul J., 1996. "An empirical examination of information, differences of opinion, and trading activity," Journal of Financial Economics, Elsevier, vol. 40(1), pages 105-134, January.
    3. Bohl, Martin T. & Henke, Harald, 2003. "Trading volume and stock market volatility: The Polish case," International Review of Financial Analysis, Elsevier, vol. 12(5), pages 513-525.
    4. 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.
    5. 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.
    6. Fernando, Chitru S. & Krishnamurthy, Srinivasan & Spindt, Paul A., 2004. "Are share price levels informative? Evidence from the ownership, pricing, turnover and performance of IPO firms," Journal of Financial Markets, Elsevier, vol. 7(4), pages 377-403, October.
    7. Ye, Wuyi & Guo, Ranran & Jiang, Ying & Liu, Xiaoquan & Deschamps, Bruno, 2019. "Professional macroeconomic forecasts and Chinese commodity futures prices," Finance Research Letters, Elsevier, vol. 28(C), pages 130-136.
    8. Ripple, Ronald D. & Moosa, Imad A., 2009. "The effect of maturity, trading volume, and open interest on crude oil futures price range-based volatility," Global Finance Journal, Elsevier, vol. 20(3), pages 209-219.
    9. M. F. Omran & E. McKenzie, 2000. "Heteroscedasticity in stock returns data revisited: volume versus GARCH effects," Applied Financial Economics, Taylor & Francis Journals, vol. 10(5), pages 553-560.
    10. Darrat, Ali F. & Rahman, Shafiqur & Zhong, Maosen, 2003. "Intraday trading volume and return volatility of the DJIA stocks: A note," Journal of Banking & Finance, Elsevier, vol. 27(10), pages 2035-2043, October.
    11. Magkonis, Georgios & Tsouknidis, Dimitris A., 2017. "Dynamic spillover effects across petroleum spot and futures volatilities, trading volume and open interest," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 104-118.
    12. Breitung, Jorg & Candelon, Bertrand, 2006. "Testing for short- and long-run causality: A frequency-domain approach," Journal of Econometrics, Elsevier, vol. 132(2), pages 363-378, June.
    13. Hong, Harrison & Yogo, Motohiro, 2012. "What does futures market interest tell us about the macroeconomy and asset prices?," Journal of Financial Economics, Elsevier, vol. 105(3), pages 473-490.
    14. Toshiaki Watanabe, 2001. "Price volatility, trading volume, and market depth: evidence from the Japanese stock index futures market," Applied Financial Economics, Taylor & Francis Journals, vol. 11(6), pages 651-658.
    15. Pyun, Chong Soo & Lee, Sa Young & Nam, Kiseok, 2000. "Volatility and information flows in emerging equity market: A case of the Korean Stock Exchange," International Review of Financial Analysis, Elsevier, vol. 9(4), pages 405-420.
    16. Ma, Junjun & Xiong, Xiong & Feng, Xu, 2021. "News release and the role of different types of investors," International Review of Financial Analysis, Elsevier, vol. 73(C).
    17. Ciner, Cetin, 2011. "Information transmission across currency futures markets: Evidence from frequency domain tests," International Review of Financial Analysis, Elsevier, vol. 20(3), pages 134-139, June.
    18. Kao, Yu-Sheng & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2020. "The empirical linkages among market returns, return volatility, and trading volume: Evidence from the S&P 500 VIX Futures," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    19. Kumar, Satish, 2016. "Evidence of information transmission across currency futures markets using frequency domain tests," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 319-327.
    20. Guo, Jin, 2018. "Co-movement of international copper prices, China's economic activity, and stock returns: Structural breaks and volatility dynamics," Global Finance Journal, Elsevier, vol. 36(C), pages 62-77.
    21. Wei, Yanfeng & Guo, Xiaoying, 2016. "An empirical analysis of the relationship between oil prices and the Chinese macro-economy," Energy Economics, Elsevier, vol. 56(C), pages 88-100.
    22. Czudaj, Robert L., 2019. "Dynamics between trading volume, volatility and open interest in agricultural futures markets: A Bayesian time-varying coefficient approach," Econometrics and Statistics, Elsevier, vol. 12(C), pages 78-145.
    23. Chng, Michael T., 2009. "Economic linkages across commodity futures: Hedging and trading implications," Journal of Banking & Finance, Elsevier, vol. 33(5), pages 958-970, May.
    24. Louhichi, Waël, 2011. "What drives the volume-volatility relationship on Euronext Paris?," International Review of Financial Analysis, Elsevier, vol. 20(4), pages 200-206, August.
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