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Limit order books and liquidity around scheduled and non-scheduled announcements: Empirical evidence from NASDAQ Nordic

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  • Siikanen, Milla
  • Kanniainen, Juho
  • Valli, Jaakko

Abstract

Information arrivals may drive investors to require immediacy, generating sudden liquidity demand across multiple price levels in limit order books. We document significant intraday changes in stock limit order book characteristics and liquidity beyond the best levels around scheduled and non-scheduled company announcements. At aggregated level, liquidity beyond the best levels behaves quite differently from the bid–ask spread around scheduled announcements. Moreover, scheduled announcements improve multi-level liquidity to an exceptionally good level. We also provide evidence for pre-reactions in order books before non-scheduled announcements, which suggest the possibility of information leakage.

Suggested Citation

  • Siikanen, Milla & Kanniainen, Juho & Valli, Jaakko, 2017. "Limit order books and liquidity around scheduled and non-scheduled announcements: Empirical evidence from NASDAQ Nordic," Finance Research Letters, Elsevier, vol. 21(C), pages 264-271.
    • Handle: RePEc:eee:finlet:v:21:y:2017:i:c:p:264-271
    DOI: 10.1016/j.frl.2016.12.016
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    Cited by:

    1. Adamantios Ntakaris & Martin Magris & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2017. "Benchmark Dataset for Mid-Price Forecasting of Limit Order Book Data with Machine Learning Methods," Papers 1705.03233, arXiv.org, revised Mar 2020.
    2. Nguyen, Dinh Trung & Pham, Thu Phuong & Tran, Ngoc Anh & Zurbruegg, Ralf, 2024. "The dynamic effects of debtor bankruptcy on unsecured creditors' stock liquidity," Journal of Financial Stability, Elsevier, vol. 74(C).
    3. Martin Magris & Jiyeong Kim & Esa Rasanen & Juho Kanniainen, 2017. "Long-range Auto-correlations in Limit Order Book Markets: Inter- and Cross-event Analysis," Papers 1711.03534, arXiv.org.
    4. Ymir Makinen & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2018. "Forecasting of Jump Arrivals in Stock Prices: New Attention-based Network Architecture using Limit Order Book Data," Papers 1810.10845, arXiv.org.
    5. Feng, Wenjun & Wang, Yiming & Zhang, Zhengjun, 2018. "Informed trading in the Bitcoin market," Finance Research Letters, Elsevier, vol. 26(C), pages 63-70.
    6. Milla Siikanen & Kk{e}stutis Baltakys & Juho Kanniainen & Ravi Vatrapu & Raghava Mukkamala & Abid Hussain, 2017. "Facebook drives behavior of passive households in stock markets," Papers 1709.07300, arXiv.org, revised May 2018.
    7. Priyanka Naik & Y. V. Reddy, 2021. "Stock Market Liquidity: A Literature Review," SAGE Open, , vol. 11(1), pages 21582440209, January.
    8. Siikanen, Milla & Kanniainen, Juho & Luoma, Arto, 2017. "What drives the sensitivity of limit order books to company announcement arrivals?," Economics Letters, Elsevier, vol. 159(C), pages 65-68.
    9. Siikanen, Milla & Baltakys, Kęstutis & Kanniainen, Juho & Vatrapu, Ravi & Mukkamala, Raghava & Hussain, Abid, 2018. "Facebook drives behavior of passive households in stock markets," Finance Research Letters, Elsevier, vol. 27(C), pages 208-213.
    10. Juho Kanniainen & Ye Yue, 2019. "The Arrival of News and Return Jumps in Stock Markets: A Nonparametric Approach," Papers 1901.02691, arXiv.org.
    11. Dat Thanh Tran & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2021. "Bilinear Input Normalization for Neural Networks in Financial Forecasting," Papers 2109.00983, arXiv.org.

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    More about this item

    Keywords

    Limit order book; Liquidity; Company announcement; High-frequency data;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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