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Market moods and network dynamics of stock returns: the bipolar behavior


Ajirlou, AI and Esmalifalak, H and Esmalifalak, M and Behrouz, SP and Soltanalizadeh, F, Market moods and network dynamics of stock returns: the bipolar behavior, Journal of Behavioral Finance, 20, (2) pp. 239-254. ISSN 1542-7560 (2019) [Refereed Article]

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Copyright Statement

Copyright 2019 The Institute of Behavioral Finance. This is an Accepted Manuscript of an article published by Taylor & Francis Group in The Journal of Behavioral Finance on 24/01/2019, available online:

DOI: doi:10.1080/15427560.2018.1508022


The authors show that a simple mood-separable preference in a network study of stock returns captures a variety of stylized facts regarding stocks’ provisional (ab)normal behavior. These behaviors are articulated in a multistate complete Euclidean network model that specifies the existence, direction, and magnitude of a self-organized dynamics for each individual stock during abnormal market moods. In the empirical setting, the authors apply suggested model along with 2 established visual approaches (multidimensional scaling and agglomerative hierarchical clustering) for benchmark purposes. Results reveal different levels of erratic return dynamics for each stock and the entire market in different abnormal market moods. The authors model and interpret these self-organized dynamics as evidence of stocks’ and market’s bipolar behavior.

Item Details

Item Type:Refereed Article
Keywords:complete euclidean network, alpha measure, stocks’ bipolar behavior, market’s bipolar behavior
Research Division:Mathematical Sciences
Research Group:Applied mathematics
Research Field:Applied mathematics not elsewhere classified
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the mathematical sciences
UTAS Author:Esmalifalak, H ( Hamidreza Esmalifalak)
ID Code:133588
Year Published:2019
Web of Science® Times Cited:3
Deposited By:TSBE
Deposited On:2019-07-02
Last Modified:2020-07-24
Downloads:10 View Download Statistics

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