The information content of overnight information for volatility forecasting : evidence from China's stock market

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Zhang, Yi and Zhou, Long and Liu, Zhidong (2025) The information content of overnight information for volatility forecasting : evidence from China's stock market. Journal of Forecasting, 44 (8). pp. 2331-2345. ISSN 0277-6693 (https://doi.org/10.1002/for.70011)

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Abstract

Using overnight volatility as the proxy for overnight information, this paper models future Chinese stock market realized range–based volatility (RRV) within a class of heterogeneous autoregressive models augmented by this proxy. We confirm the important role of overnight information in volatility forecasting models with strong evidence from in-sample and out-of-sample analyses. Moreover, such forecasting improvement is considerable at the short-term prediction horizon but weakens as the prediction horizon extends. We conduct numerous robust tests to strengthen our findings, with alternative rolling window lengths, alternative loss criteria, and alternative volatility estimators. We also provide evidence that our forecasting model incorporating overnight volatility performs extremely well in volatility forecasting during times of market turbulence.

ORCID iDs

Zhang, Yi, Zhou, Long ORCID logoORCID: https://orcid.org/0000-0001-9687-1406 and Liu, Zhidong;
  • Item type:Article
    ID code:93577
    Dates:
    Date
    Event
    1 December 2025
    Published
    4 August 2025
    Published Online
    7 July 2025
    Accepted
    24 December 2023
    Submitted
    Subjects:Science > Mathematics > Probabilities. Mathematical statistics
    Department:?? 15452 ??
    Depositing user: Pure Administrator
    Date deposited:24 Jul 2025 14:48
    Last modified:12 Aug 2026 12:52
    URI:https://strathprints.strath.ac.uk/id/eprint/93577
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