A behavioural model of investor sentiment in limit order markets

Chiarella, C; He, XZ; Shi, L; Wei, L

A behavioural model of investor sentiment in limit order markets

Chiarella, C He, XZ

Shi, L

Wei, L

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Publication Type:: Journal Article
Citation:: Quantitative Finance, 2017, 17 (1), pp. 71 - 86
Issue Date:: 2017-01-02

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Field	Value	Language
dc.contributor.author	Chiarella, C	en_US
dc.contributor.author	He, XZ https://orcid.org/0000-0003-1446-9996	en_US
dc.contributor.author	Shi, L https://orcid.org/0000-0002-6226-1762	en_US
dc.contributor.author	Wei, L	en_US
dc.date.available	2020-05-25T19:09:37Z
dc.date.issued	2017-01-02	en_US
dc.identifier.citation	Quantitative Finance, 2017, 17 (1), pp. 71 - 86	en_US
dc.identifier.issn	1469-7688	en_US
dc.identifier.uri	http://hdl.handle.net/10453/110556
dc.description.abstract	© 2016 Informa UK Limited, trading as Taylor & Francis Group. By incorporating behavioural sentiment in a model of a limit order market, we show that behavioural sentiment not only helps to replicate most of the stylized facts in limit order markets simultaneously, but it also plays a unique role in explaining those stylized facts that cannot be explained by noise trading, such as fat tails in the return distribution, long memory in the trading volume, an increasing and non-linear relationship between trade imbalance and mid-price returns, as well as the diagonal effect, or event clustering, in order submission types. The results show that behavioural sentiment is an important driving force behind many of the well-documented stylized facts in limit order markets.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP130103210
dc.relation.ispartof	Quantitative Finance	en_US
dc.relation.isbasedon	10.1080/14697688.2016.1184756	en_US
dc.subject.classification	Finance	en_US
dc.title	A behavioural model of investor sentiment in limit order markets	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	17	en_US
utslib.for	0102 Applied Mathematics	en_US
utslib.for	1501 Accounting, Auditing and Accountability	en_US
utslib.for	1402 Applied Economics	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	14 Economics	en_US
utslib.for	15 Commerce, Management, Tourism and Services	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Finance Discipline
pubs.organisational-group	/University of Technology Sydney/Strength - QFRC - Quantitative Finance Research Centre
utslib.copyright.status	open_access
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	17	en_US

Abstract:

© 2016 Informa UK Limited, trading as Taylor & Francis Group. By incorporating behavioural sentiment in a model of a limit order market, we show that behavioural sentiment not only helps to replicate most of the stylized facts in limit order markets simultaneously, but it also plays a unique role in explaining those stylized facts that cannot be explained by noise trading, such as fat tails in the return distribution, long memory in the trading volume, an increasing and non-linear relationship between trade imbalance and mid-price returns, as well as the diagonal effect, or event clustering, in order submission types. The results show that behavioural sentiment is an important driving force behind many of the well-documented stylized facts in limit order markets.

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http://hdl.handle.net/10453/110556