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Neural network predictions of the high-frequency CSI300 first distant futures trading volume

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  • Xiaojie Xu

    (North Carolina State University)

  • Yun Zhang

    (North Carolina State University)

Abstract

Predictions of financial index trading volumes represent an essential issue to market participants and policy makers. We investigate this problem for the high-frequency one-minute CSI300 first distant futures trading volume from the launch of the futures index to two years after all its constituent stocks becoming shortable, a period with generally continuously expanding trading magnitude. We utilize the neural network to model this complex and irregular trading volume series and attempt to answer the following questions: can the trading volume be predicted by its own lags, and if so, how far to predict and how well; can the nearby futures or spot trading volume series help predictions, and if so, by how much; how complex does the model need to be and how robust can it be? We find that the trading volume could be predicted using one to thirty minutes ahead data through a relatively low complex model with five hidden neurons based on its own lags, resulting in generally accurate and stable performance based on the relative root mean square error. Incorporating the nearby futures or spot trading volume series generally does not help improve predictions. Results here should be of interest and use to design trading platforms, monitor system risk, and form index price predictions.

Suggested Citation

  • Xiaojie Xu & Yun Zhang, 2023. "Neural network predictions of the high-frequency CSI300 first distant futures trading volume," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(2), pages 191-207, June.
    • Handle: RePEc:kap:fmktpm:v:37:y:2023:i:2:d:10.1007_s11408-022-00421-y
    DOI: 10.1007/s11408-022-00421-y
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    1. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Intra-daily Volume Modeling and Prediction for Algorithmic Trading," Journal of Financial Econometrics, Oxford University Press, vol. 9(3), pages 489-518, Summer.
    2. Ng, Lilian & Wu, Fei, 2007. "The trading behavior of institutions and individuals in Chinese equity markets," Journal of Banking & Finance, Elsevier, vol. 31(9), pages 2695-2710, September.
    3. Yang, Jian & Cabrera, Juan & Wang, Tao, 2010. "Nonlinearity, data-snooping, and stock index ETF return predictability," European Journal of Operational Research, Elsevier, vol. 200(2), pages 498-507, January.
    4. Muhammad Ali Nasir & Toan Luu Duc Huynh & Sang Phu Nguyen & Duy Duong, 2019. "Forecasting cryptocurrency returns and volume using search engines," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-13, December.
    5. Xiaojie Xu & Yun Zhang, 2022. "Second-hand house price index forecasting with neural networks," Journal of Property Research, Taylor & Francis Journals, vol. 39(3), pages 215-236, July.
    6. Roger A. Fujihara & Mbodja Mougoué, 1997. "An examination of linear and nonlinear causal relationships between price variability and volume in petroleum futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 17(4), pages 385-416, June.
    7. Silvapulle, Param & Choi, Jong-Seo, 1999. "Testing for linear and nonlinear granger causality in the stock price-volume relation: Korean evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 39(1), pages 59-76.
    8. Jian Yang & Zihui Yang & Yinggang Zhou, 2012. "Intraday price discovery and volatility transmission in stock index and stock index futures markets: Evidence from China," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(2), pages 99-121, February.
    9. Susheng Wang & Guanglu Li & Junbo Wang, 2019. "Dynamic Interactions between Intraday Returns and Trading Volume on the CSI 300 Index Futures: An Application of an SVAR Model," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-18, August.
    10. Wang, Dong-Hua & Suo, Yuan-Yuan & Yu, Xiao-Wen & Lei, Man, 2013. "Price–volume cross-correlation analysis of CSI300 index futures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1172-1179.
    11. Dharmaraja Selvamuthu & Vineet Kumar & Abhishek Mishra, 2019. "Indian stock market prediction using artificial neural networks on tick data," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-12, December.
    12. Yang, Jian & Su, Xiaojing & Kolari, James W., 2008. "Do Euro exchange rates follow a martingale? Some out-of-sample evidence," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 729-740, May.
    13. Xiaojie Xu & Yun Zhang, 2021. "Rent index forecasting through neural networks," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 49(8), pages 1321-1339, November.
    14. Shaojun Ma & Pengcheng Li, 2021. "Predicting Daily Trading Volume via Various Hidden States," Papers 2107.07678, arXiv.org.
    15. Xiaojie Xu, 2018. "Causal structure among US corn futures and regional cash prices in the time and frequency domain," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(13), pages 2455-2480, October.
    16. Zhou, Weijie & Pan, Jiao & Wu, Xiaoli, 2019. "Forecasting the realized volatility of CSI 300," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    17. Xiaojie Xu, 2018. "Intraday price information flows between the CSI300 and futures market: an application of wavelet analysis," Empirical Economics, Springer, vol. 54(3), pages 1267-1295, May.
    18. Wang, Tao & Yang, Jian, 2010. "Nonlinearity and intraday efficiency tests on energy futures markets," Energy Economics, Elsevier, vol. 32(2), pages 496-503, March.
    19. Xiaojie Xu & Yun Zhang, 2022. "Contemporaneous causality among one hundred Chinese cities," Empirical Economics, Springer, vol. 63(4), pages 2315-2329, October.
    20. Rashid, Abdul, 2007. "Stock prices and trading volume: An assessment for linear and nonlinear Granger causality," Journal of Asian Economics, Elsevier, vol. 18(4), pages 595-612, August.
    21. Juan Cabrera & Tao Wang & Jian Yang, 2011. "Linear and Nonlinear Predictability of International Securitized Real Estate Returns: A Reality Check," Journal of Real Estate Research, American Real Estate Society, vol. 33(4), pages 565-594.
    22. David Bessler & Zijun Wang, 2012. "D-separation, forecasting, and economic science: a conjecture," Theory and Decision, Springer, vol. 73(2), pages 295-314, August.
    23. Xiaojie Xu, 2019. "Price dynamics in corn cash and futures markets: cointegration, causality, and forecasting through a rolling window approach," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(2), pages 155-181, June.
    24. Xiaojie Xu, 2017. "The rolling causal structure between the Chinese stock index and futures," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(4), pages 491-509, November.
    25. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    26. Xiaojie Xu, 2019. "Contemporaneous Causal Orderings of CSI300 and Futures Prices through Directed Acyclic Graphs," Economics Bulletin, AccessEcon, vol. 39(3), pages 2052-2077.
    27. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    28. Xiaojie Xu, 2017. "Short-run price forecast performance of individual and composite models for 496 corn cash markets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(14), pages 2593-2620, October.
    29. Huang, Wei & Lai, Pei-Chun & Bessler, David A., 2018. "On the changing structure among Chinese equity markets: Hong Kong, Shanghai, and Shenzhen," European Journal of Operational Research, Elsevier, vol. 264(3), pages 1020-1032.
    30. Xu, Xiaojie & Thurman, Walter, 2015. "Forecasting Local Grain Prices: An Evaluation of Composite Models in 500 Corn Cash Markets," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205332, Agricultural and Applied Economics Association.
    31. Xiaojie Xu, 2017. "Contemporaneous causal orderings of US corn cash prices through directed acyclic graphs," Empirical Economics, Springer, vol. 52(2), pages 731-758, March.
    32. Xiaojie Xu, 2015. "Cointegration among regional corn cash prices," Economics Bulletin, AccessEcon, vol. 35(4), pages 2581-2594.
    33. Joseph, Kissan & Babajide Wintoki, M. & Zhang, Zelin, 2011. "Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1116-1127, October.
    34. Hou, Yang & Li, Steven, 2014. "The impact of the CSI 300 stock index futures: Positive feedback trading and autocorrelation of stock returns," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 319-337.
    35. Yan Yan & Ouyang Hongbing, 2018. "Dynamic probability of informed trading and price movements: evidence from the CSI300 index futures market," Applied Economics Letters, Taylor & Francis Journals, vol. 25(14), pages 998-1003, August.
    36. Xiaojie Xu, 2018. "Cointegration and price discovery in US corn cash and futures markets," Empirical Economics, Springer, vol. 55(4), pages 1889-1923, December.
    37. Sungbin Sohn & Xiaofeng Zhang, 2017. "Could the Extended Trading of CSI 300 Index Futures Facilitate Its Role of Price Discovery?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(7), pages 717-740, July.
    38. Xiaojie Xu & Yun Zhang, 2022. "Commodity price forecasting via neural networks for coffee, corn, cotton, oats, soybeans, soybean oil, sugar, and wheat," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 29(3), pages 169-181, July.
    39. Yang Hou & Steven Li, 2013. "Price Discovery in Chinese Stock Index Futures Market: New Evidence Based on Intraday Data," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 20(1), pages 49-70, March.
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