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Intra-day variability of the stock market activity versus stationarity of the financial time series

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  • Gubiec, T.
  • Wiliński, M.

Abstract

In this paper we propose a new approach to a well-known phenomena of intra-day activity pattern on the stock market. We suggest that seasonality of inter-transaction times has a more significant impact than intra-day pattern of volatility. Our aim is not to remove the intra-day pattern from the data but to describe its impact on autocorrelation function estimators. We obtain an exact, analytical formula relating estimators of the autocorrelation functions of non-stationary (seasonal) process to its stationary counterpart. Hence, we prove that the day seasonality of inter-transaction times extends the memory of the process. That is, autocorrelation of both, price returns and their absolute values, relaxation to zero is longer.

Suggested Citation

  • Gubiec, T. & Wiliński, M., 2015. "Intra-day variability of the stock market activity versus stationarity of the financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 216-221.
    • Handle: RePEc:eee:phsmap:v:432:y:2015:i:c:p:216-221
    DOI: 10.1016/j.physa.2015.03.033
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    References listed on IDEAS

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    Cited by:

    1. Ponta, Linda & Trinh, Mailan & Raberto, Marco & Scalas, Enrico & Cincotti, Silvano, 2019. "Modeling non-stationarities in high-frequency financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 173-196.
    2. Jaros{l}aw Klamut & Tomasz Gubiec, 2018. "Directed Continuous-Time Random Walk with memory," Papers 1807.01934, arXiv.org.
    3. Niu, Hongli & Wang, Jun & Lu, Yunfan, 2016. "Fluctuation behaviors of financial return volatility duration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 30-40.

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