Market Moods and Network Dynamics of Stock Returns: The Bipolar Behavior

Ali Irannezhad Ajirlou, Hamidreza Esmalifalak, Maryam Esmalifalak, Sahar Pordeli Behrouz, Farid Soltanalizadeh

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)239-254
Number of pages16
JournalJournal of Behavioral Finance
Issue number2
Publication statusPublished - 2019


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