Market Moods and Network Dynamics of Stock Returns: The Bipolar Behavior
Ali Irannezhad Ajirlou,
Hamidreza Esmalifalak,
Maryam Esmalifalak,
Sahar Pordeli Behrouz and
Farid Soltanalizadeh
Journal of Behavioral Finance, 2019, vol. 20, issue 2, 239-254
Abstract:
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.
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://hdl.handle.net/10.1080/15427560.2018.1508022 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:hbhfxx:v:20:y:2019:i:2:p:239-254
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/hbhf20
DOI: 10.1080/15427560.2018.1508022
Access Statistics for this article
Journal of Behavioral Finance is currently edited by Brian Bruce
More articles in Journal of Behavioral Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().