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Volatility forecasting: The role of lunch-break returns, overnight returns, trading volume and leverage effects

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  • Wang, Xunxiao
  • Wu, Chongfeng
  • Xu, Weidong

Abstract

This article extends the HAR-RV model to enable it to forecast volatility by including lunch-break returns, overnight returns, trading volume and leverage effects in the Chinese stock market. The findings show the significant role of additional leverage effects, captured by negative lunch-break returns and negative overnight returns, in volatility forecasting, in addition to the trading volume’s impact. Moreover, there is a strong significance of the usual leverage effects, which turn out to be persistent even for SHCI. Surprisingly, squared lunch-break returns, measured as additional volatilities during the lunch-break period, have a large long-run impact on the volatility for SHCI but not for SZCI. This new empirical evidence is robust to alternative realized measurements and unconditional variance, and, in particular, confirms the impact of intermittent trading, captured by the returns and volatilities outside the trading hours. Overall, our model performs much better than the benchmark HAR-RV model when various forecasting horizons are considered, and our findings have important implications for investors and policy makers.

Suggested Citation

  • Wang, Xunxiao & Wu, Chongfeng & Xu, Weidong, 2015. "Volatility forecasting: The role of lunch-break returns, overnight returns, trading volume and leverage effects," International Journal of Forecasting, Elsevier, vol. 31(3), pages 609-619.
  • Handle: RePEc:eee:intfor:v:31:y:2015:i:3:p:609-619
    DOI: 10.1016/j.ijforecast.2014.10.007
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    2. Dimos Kambouroudis & David McMillan & Katerina Tsakou, 2019. "Forecasting Realized Volatility: The role of implied volatility, leverage effect, overnight returns and volatility of realized volatility," Working Papers 2019-03, Swansea University, School of Management.
    3. Chu, Xiaojun & Gu, Zherong & Zhou, Haigang, 2019. "Intraday momentum and reversal in Chinese stock market," Finance Research Letters, Elsevier, vol. 30(C), pages 83-88.
    4. Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
    5. Zhu, Xuehong & Zhang, Hongwei & Zhong, Meirui, 2017. "Volatility forecasting using high frequency data: The role of after-hours information and leverage effects," Resources Policy, Elsevier, vol. 54(C), pages 58-70.
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    7. Gong, Xu & Lin, Boqiang, 2019. "Modeling stock market volatility using new HAR-type models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 194-211.
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    9. Fei, Tianlun & Liu, Xiaoquan & Wen, Conghua, 2019. "Cross-sectional return dispersion and volatility prediction," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    10. Meng, Xiaochun & Taylor, James W., 2018. "An approximate long-memory range-based approach for value at risk estimation," International Journal of Forecasting, Elsevier, vol. 34(3), pages 377-388.
    11. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2017. "Forecasting market returns: bagging or combining?," International Journal of Forecasting, Elsevier, vol. 33(1), pages 102-120.
    12. Yi-Hsuan Chen, Cathy & Fengler, Matthias & Härdle, Wolfgang Karl & Liu, Yanchu, 2018. "Textual Sentiment, Option Characteristics, and Stock Return Predictability," Economics Working Paper Series 1808, University of St. Gallen, School of Economics and Political Science.
    13. Zhang, Heng-Guo & Su, Chi-Wei & Song, Yan & Qiu, Shuqi & Xiao, Ran & Su, Fei, 2017. "Calculating Value-at-Risk for high-dimensional time series using a nonlinear random mapping model," Economic Modelling, Elsevier, vol. 67(C), pages 355-367.
    14. Ma, Feng & Wahab, M.I.M. & Huang, Dengshi & Xu, Weiju, 2017. "Forecasting the realized volatility of the oil futures market: A regime switching approach," Energy Economics, Elsevier, vol. 67(C), pages 136-145.
    15. Newaz, Mohammad Khaleq & Park, Jin Suk, 2019. "The impact of trade intensity and Market characteristics on asymmetric volatility, spillovers and asymmetric spillovers: Evidence from the response of international stock markets to US shocks," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 79-94.
    16. Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.

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