The Autoregressive Conditional Marked Duration model: Statistical inference to market microstructure

Sai Man Simon KWOK, Wai Keung LI, Leung Ho Philip YU

Research output: Contribution to journalArticles

Abstract

We consider the Autoregressive Conditional Marked Duration (ACMD) model and apply it to 16 stocks traded in Hong Kong Stock Exchange (SEHK). By examining the orderings of appropriate sets of model parameters, market microstructure phenomena can be explained. To substantiate these conclusions, likelihood ratio test is used for testing the significance of the parameter orderings of the ACMD model. While some of our results resolve a few controversial market microstructure hypotheses and echo some of the existing empirical evidence, we discover some interesting market microstructure phenomena that may be characteristic to SEHK. Copyright © 2009 Journal of Data Science.
Original languageEnglish
Pages (from-to)189-201
JournalJournal of Data Science
Volume7
Issue number2
DOIs
Publication statusPublished - Apr 2009

Citation

Kwok, S. S. M., Li, W. K., & Yu, P. L. H. (2009). The Autoregressive Conditional Marked Duration model: Statistical inference to market microstructure. Journal of Data Science, 7(2), 189-201. doi: 10.6339/JDS.2009.07(2).438

Keywords

  • Autoregressive conditional duration
  • Likelihood ratio test
  • Market microstructure
  • Statistical inference

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