期刊
JOURNAL OF FINANCIAL MARKETS
卷 8, 期 4, 页码 377-399出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.finmar.2005.06.002
关键词
autoregressive conditional duration; GARCH; ultra high frequency data; empirical market microstructure
This paper presents a framework to model duration, volume and returns simultaneously, obtaining an econometric reduced form that incorporates causal and feedback effects among these variables. The methodology is applied to two groups of stocks, classified according to trade intensity. We find that: (1) all stocks exhibit trading volume clustering (which is significantly higher for frequently traded stocks); (2) times of greater activity coincide with a higher number of informed traders present in the market only for the frequently traded stocks; (3) the more frequently traded stocks converge more rapidly (in calendar time) to their long-run equilibrium, after an initial perturbation. (c) 2005 Elsevier B.V. All rights reserved.
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