Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

The dynamics of trading duration, volume and price volatility: a vector MEM model

Xu, Yongdeng ORCID: https://orcid.org/0000-0001-8275-1585 2013. The dynamics of trading duration, volume and price volatility: a vector MEM model. [Working Paper]. Cardiff Economics Working Papers, Cardiff: Cardiff University.

[thumbnail of e2013_7.pdf]
Preview
PDF - Published Version
Download (4MB) | Preview

Abstract

We propose a general form of vector Multiplicative Error Model (MEM) for the dynamics of duration, volume and price volatility. The vector MEM relaxes the two restrictions often imposed by previous empirical work in market microstructure research, by allowing interdependence among the variables and relaxing weak exogeneity restrictions. We further propose a multivariate lognormal distribution for the vector MEM. The model is applied to the trade and quote data from the New York Stock Exchange (NYSE). The empirical results show that the vector MEM captures the dynamics of the trivariate system successfully. We find that times of greater activity or trades with larger size coincide with a higher number of informed traders present in the market. But we highlight that it is unexpected component of trading duration or trading volume that carry the information content. Moreover, our empirical results also suggest a significant feedback effect from price process to trading intensity, while the persistent quote changes and transient quote changes affect trading intensity in different direction, confirming Hasbrouck (1988,1991).

Item Type: Monograph (Working Paper)
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > HB Economic Theory
Publisher: Cardiff University
Date of First Compliant Deposit: 30 March 2016
Last Modified: 28 Oct 2022 10:21
URI: https://orca.cardiff.ac.uk/id/eprint/77993

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics