IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v95y2024ipbs1057521924003879.html
   My bibliography  Save this article

Analysis of rare events using multidimensional liquidity measures

Author

Listed:
  • Zaika, Margarita
  • Bozdog, Dragos
  • Florescu, Ionut

Abstract

In this paper we develop a framework to analyze high-frequency (HF) financial transaction data focused on estimating a multidimensional intraday liquidity measure and detecting rare events. Many liquidity measures based on Trade and Quote (TAQ) and Limit Order Book (LOB) datasets are consolidated for this purpose through dimensionality reduction techniques. Several outlier methods based on extreme value theory, distance-based outlier methods, and tree-based algorithms are implemented to identify clusters of rare liquidity events. These methods provide insights into the behavior and occurrence of outliers. The methodology is optimized for HF intraday implementation. The framework is applied to transaction level data covering the beginning of COVID-19 outbreak period. We observe that after peak news activity, high-volume stocks experience extreme low-liquidity events almost immediately, while low-volume stocks have a time delayed reaction. The behavior of a select number of tickers is analyzed in detail over the outbreak period. The framework proposed can detect extreme liquidity events in real time and thus can be used to monitor market activity and provide early warnings about liquidity trends. A new intensity indicator measure is developed to assess and visualize extreme liquidity events.

Suggested Citation

  • Zaika, Margarita & Bozdog, Dragos & Florescu, Ionut, 2024. "Analysis of rare events using multidimensional liquidity measures," International Review of Financial Analysis, Elsevier, vol. 95(PB).
  • Handle: RePEc:eee:finana:v:95:y:2024:i:pb:s1057521924003879
    DOI: 10.1016/j.irfa.2024.103455
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521924003879
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.irfa.2024.103455?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Cao, Charles & Chen, Yong & Liang, Bing & Lo, Andrew W., 2013. "Can hedge funds time market liquidity?," Journal of Financial Economics, Elsevier, vol. 109(2), pages 493-516.
    2. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
    3. Díaz, Antonio & Escribano, Ana, 2022. "Liquidity dimensions in the U.S. corporate bond market," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 1163-1179.
    4. Gerety, Mason S & Mulherin, J Harold, 1992. "Trading Halts and Market Activity: An Analysis of Volume at the Open and the Close," Journal of Finance, American Finance Association, vol. 47(5), pages 1765-1784, December.
    5. Turan G. Bali & Lin Peng & Yannan Shen & Yi Tang, 2013. "Liquidity Shocks and Stock Market Reactions," Koç University-TUSIAD Economic Research Forum Working Papers 1304, Koc University-TUSIAD Economic Research Forum.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Plat, Richard, 2009. "Stochastic portfolio specific mortality and the quantification of mortality basis risk," Insurance: Mathematics and Economics, Elsevier, vol. 45(1), pages 123-132, August.
    2. Kondylis, Athanassios & Whittaker, Joe, 2008. "Spectral preconditioning of Krylov spaces: Combining PLS and PC regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2588-2603, January.
    3. Ouyang, Yaofu & Li, Peng, 2018. "On the nexus of financial development, economic growth, and energy consumption in China: New perspective from a GMM panel VAR approach," Energy Economics, Elsevier, vol. 71(C), pages 238-252.
    4. Paschalis Arvanitidis & Athina Economou & Christos Kollias, 2016. "Terrorism’s effects on social capital in European countries," Public Choice, Springer, vol. 169(3), pages 231-250, December.
    5. Rizvi, Syed Kumail Abbas & Rahat, Birjees & Naqvi, Bushra & Umar, Muhammad, 2024. "Revolutionizing finance: The synergy of fintech, digital adoption, and innovation," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    6. Zheng, Yao & Osmer, Eric & Zhang, Ruiyi, 2018. "Sentiment hedging: How hedge funds adjust their exposure to market sentiment," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 147-160.
    7. Teerachai Amnuaylojaroen & Pavinee Chanvichit, 2024. "Historical Analysis of the Effects of Drought on Rice and Maize Yields in Southeast Asia," Resources, MDPI, vol. 13(3), pages 1-18, March.
    8. Bali, Turan G. & Brown, Stephen J. & Caglayan, Mustafa O., 2019. "Upside potential of hedge funds as a predictor of future performance," Journal of Banking & Finance, Elsevier, vol. 98(C), pages 212-229.
    9. Chen, Yong & Kelly, Bryan & Wu, Wei, 2020. "Sophisticated investors and market efficiency: Evidence from a natural experiment," Journal of Financial Economics, Elsevier, vol. 138(2), pages 316-341.
    10. Weili Duan & Bin He & Daniel Nover & Guishan Yang & Wen Chen & Huifang Meng & Shan Zou & Chuanming Liu, 2016. "Water Quality Assessment and Pollution Source Identification of the Eastern Poyang Lake Basin Using Multivariate Statistical Methods," Sustainability, MDPI, vol. 8(2), pages 1-15, January.
    11. Adele Ravagnani & Fabrizio Lillo & Paola Deriu & Piero Mazzarisi & Francesca Medda & Antonio Russo, 2024. "Dimensionality reduction techniques to support insider trading detection," Papers 2403.00707, arXiv.org, revised May 2024.
    12. Li, Lu & Li, Yihang & Wang, Xueding & Xiao, Tusheng & Zhu, Hongjun, 2022. "Hedge fund networks, information dissemination, and stock price comovement: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 83(C).
    13. Zheng, Yao & Osmer, Eric & Zu, Dingding, 2024. "Timing sentiment with style: Evidence from mutual funds," Journal of Banking & Finance, Elsevier, vol. 164(C).
    14. Cling, Jean-Pierre & Delecourt, Clément, 2022. "Interlinkages between the Sustainable Development Goals," World Development Perspectives, Elsevier, vol. 25(C).
    15. Hino, Hideitsu & Wakayama, Keigo & Murata, Noboru, 2013. "Entropy-based sliced inverse regression," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 105-114.
    16. Angelucci, Federica & Conforti, Piero, 2010. "Risk management and finance along value chains of Small Island Developing States. Evidence from the Caribbean and the Pacific," Food Policy, Elsevier, vol. 35(6), pages 565-575, December.
    17. Poskitt, D.S. & Sengarapillai, Arivalzahan, 2013. "Description length and dimensionality reduction in functional data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 98-113.
    18. Taner Akan & Tim Solle, 2022. "Do macroeconomic and financial governance matter? Evidence from Germany, 1950–2019," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(4), pages 993-1045, October.
    19. Paolo Rizzi & Paola Graziano & Antonio Dallara, 2018. "A capacity approach to territorial resilience: the case of European regions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 60(2), pages 285-328, March.
    20. Karstanje, Dennis & Sojli, Elvira & Tham, Wing Wah & van der Wel, Michel, 2013. "Economic valuation of liquidity timing," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5073-5087.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finana:v:95:y:2024:i:pb:s1057521924003879. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620166 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.