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The Autoregressive Conditional Marked Duration Model: Statistical Inference to Market Microstructure
Volume 7, Issue 2 (2009), pp. 189–201
Simon Sai Man Kwok  

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https://doi.org/10.6339/JDS.2009.07(2).438
Pub. online: 4 August 2022      Type: Research Article      Open accessOpen Access

Published
4 August 2022

Abstract

Abstract: We consider the Autoregressive Conditional Marked Duration (ACMD) model and apply it to 16 stocks traded in Hong Kong Stock Ex change (SEHK). By examining the orderings of appropriate sets of model parameters, market microstructure phenomena can be explained. To sub stantiate these conclusions, likelihood ratio test is used for testing the sig nificance 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.

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Keywords
Autoregressive conditional duration, likelihood ratio test statistical inference

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