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Statistical analysis of the overnight and daytime return

Author

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  • Fengzhong Wang
  • Shwu-Jane Shieh
  • Shlomo Havlin
  • H. Eugene Stanley

Abstract

We investigate the two components of the total daily return (close-to-close), the overnight return (close-to-open) and the daytime return (open-to-close), as well as the corresponding volatilities of the 2215 NYSE stocks from 1988 to 2007. The tail distribution of the volatility, the long-term memory in the sequence, and the cross-correlation between different returns are analyzed. Our results suggest that: (i) The two component returns and volatilities have similar features as that of the total return and volatility. The tail distribution follows a power law for all volatilities, and long-term correlations exist in the volatility sequences but not in the return sequences. (ii) The daytime return contributes more to the total return. Both the tail distribution and the long-term memory of the daytime volatility are more similar to that of the total volatility, compared to the overnight records. In addition, the cross-correlation between the daytime return and the total return is also stronger. (iii) The two component returns tend to be anti-correlated. Moreover, we find that the cross-correlations between the three different returns (total, overnight, and daytime) are quite stable over the entire 20-year period.

Suggested Citation

  • Fengzhong Wang & Shwu-Jane Shieh & Shlomo Havlin & H. Eugene Stanley, 2009. "Statistical analysis of the overnight and daytime return," Papers 0903.0993, arXiv.org.
    • Handle: RePEc:arx:papers:0903.0993
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    1. Gu, Gao-Feng & Ren, Fei & Ni, Xiao-Hui & Chen, Wei & Zhou, Wei-Xing, 2010. "Empirical regularities of opening call auction in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(2), pages 278-286.
    2. de Oliveira Santos, Maíra & Stosic, Tatijana & Stosic, Borko D., 2012. "Long-term correlations in hourly wind speed records in Pernambuco, Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1546-1552.
    3. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2020. "Volatility forecasting using related markets’ information for the Tokyo stock exchange," Economic Modelling, Elsevier, vol. 90(C), pages 143-158.
    4. Tsai, Kuo-Ting & Lih, Jiann-Shing & Ko, Jing-Yuan, 2012. "The overnight effect on the Taiwan stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6497-6505.
    5. Marcin Wk{a}torek & Jaros{l}aw Kwapie'n & Stanis{l}aw Dro.zd.z, 2021. "Financial Return Distributions: Past, Present, and COVID-19," Papers 2107.06659, arXiv.org.
    6. Ham, Hyuna & Ryu, Doojin & Webb, Robert I., 2022. "The effects of overnight events on daytime trading sessions," International Review of Financial Analysis, Elsevier, vol. 83(C).
    7. Aki-Hiro Sato & Takaki Hayashi & Janusz Hołyst, 2012. "Comprehensive analysis of market conditions in the foreign exchange market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 167-179, October.
    8. Wang, Gang-Jin & Xie, Chi & He, Ling-Yun & Chen, Shou, 2014. "Detrended minimum-variance hedge ratio: A new method for hedge ratio at different time scales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 70-79.
    9. Aki-Hiro Sato & Takaki Hayashi & Janusz A. Ho{l}yst, 2012. "Comprehensive Analysis of Market Conditions in the Foreign Exchange Market: Fluctuation Scaling and Variance-Covariance Matrix," Papers 1204.0426, arXiv.org.
    10. Tong, Bin & Diao, Xundi & Wu, Chongfeng, 2015. "Modeling asymmetric and dynamic dependence of overnight and daytime returns: An empirical evidence from China Banking Sector," Economic Modelling, Elsevier, vol. 51(C), pages 366-382.
    11. Bartoš, Erik & Pinčák, Richard, 2017. "Identification of market trends with string and D2-brane maps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 57-70.
    12. Krzysztof Borowski, 2015. "Analysis of the Weekend Effect on the Markets of 121 Equity Indices and 29 Commodities," Eurasian Journal of Business and Management, Eurasian Publications, vol. 3(4), pages 23-35.
    13. A. K. M. Azhar & Vincent B. Y. Gan & W. A. T. Wan Abdullah & H. Zainuddin, 2015. "On the Fractal Geometry of the Balance Sheet and the Fractal Index of Insolvency Risk," Papers 1512.09280, arXiv.org.
    14. Zheng, Zeyu & Gui, Jun & Qiao, Zhi & Fu, Yang & Stanley, H.Eugene & Li, Baowen, 2019. "New dynamics between volume and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1343-1350.
    15. Stosic, Tatijana & Telesca, Luciano & Stosic, Borko, 2021. "Multiparametric statistical and dynamical analysis of angular high-frequency wind speed time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    16. Insana, Alessandra, 2022. "Does systematic risk change when markets close? An analysis using stocks’ beta," Economic Modelling, Elsevier, vol. 109(C).
    17. dos Anjos, Priscilla Sales & da Silva, Antonio Samuel Alves & Stošić, Borko & Stošić, Tatijana, 2015. "Long-term correlations and cross-correlations in wind speed and solar radiation temporal series from Fernando de Noronha Island, Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 90-96.
    18. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2016. "Forecasting stock volatility using after-hour information: Evidence from the Australian Stock Exchange," Economic Modelling, Elsevier, vol. 52(PB), pages 592-608.
    19. Kallinterakis, Vasileios & Karaa, Rabaa, 2023. "From dusk till dawn (and vice versa): Overnight-versus-daytime reversals and feedback trading," International Review of Financial Analysis, Elsevier, vol. 85(C).
    20. Huabin Bian & Renhai Hua & Qingfu Liu & Ping Zhang, 2022. "Petroleum market volatility tracker in China," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(11), pages 2022-2040, November.

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