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Research on cojumps of electronic commerce overnight factors in volatility prediction based on joint BW test

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Abstract

Volatility is an important feature of e-commerce activities, and overnight information has the greatest impact on the market volatility of e-commerce. The identification of contemporaneous jumps (cojumps) is crucial to studying the effect of overnight information on market volatility. This paper takes stock and futures e-commerce as the research object, based on the heterogeneous autoregression model of the Realized Volatility under high-frequency data, not only the characteristics of cojumps between the CSI 300 stock index and the future index are investigated, but also the effects of overnight factors on the future volatility. The results indicate that the Extended-Weighted Realized Volatility (EWRV) modifying both the intraday and overnight effects may be a better estimator of volatility. The joint BW test could be more efficient in the identification of cojumps with significant overnight characteristics. The effect of the overnight cojumps on the future volatility is significantly positive and greater than that of the intraday cojumps. In the Electronic Commerce stock index market, there is not enough evidence of the transmission from the overnight cojumps to the intraday volatility, which means the future index market may have no significant spillover to the stock index market.

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Acknowledgements

The authors hereby transfer copyrights of the article entitled: Research on Cojumps of electronic commerce overnight factors in volatility prediction based on joint BW test to the Journal of Electronic Commerce Research. The authors agree to publish the above paper on an open access basis in all forms and media, and to publish the paper under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0). However, the authors retain the copyrights of all parts of the article for noncommercial use. All rights other than copyrights, e.g., patent rights, can be excluded from this agreement. The data that support the findings of this study are available from the corresponding author upon request.

Funding

Science and Technology Project of Chongqing Education Commission (KJQN202001221). National Natural Science Foundation of China (71873023).

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Authors and Affiliations

  1. School of Finance and Economics, Chongqing Three Gorges University, Wanzhou, 404130, China

    Liling Deng

  2. School of Finance, Dongbei University of Finance and Economics, Dalian, 116025, China

    Haifang Xiong & Zhiqiang Wang

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  1. Liling Deng
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  2. Haifang Xiong
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Correspondence to Liling Deng.

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Deng, L., Xiong, H. & Wang, Z. Research on cojumps of electronic commerce overnight factors in volatility prediction based on joint BW test. Electron Commer Res 23, 115–135 (2023). https://doi.org/10.1007/s10660-022-09545-9

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