TY - JOUR
T1 - Dynamics of hierarchical clustering in stocks market during financial crises
AU - Jaroonchokanan, Nawee
AU - Termsaithong, Teerasit
AU - Suwanna, Sujin
N1 - Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2022/12/1
Y1 - 2022/12/1
N2 - We examine the behaviors of stocks in the Stock Exchange of Thailand (SET) during financial crises from 2008 to 2020 by using a variety of indicators such as average entropy, average correlation, and average Fisher information distance. All of these indicators increased dramatically during a financial crisis, which agreed with the Ulcer index indicating the root mean square of the percentage price drawdown. We investigate the dynamics of the hierarchical tree structure of 37 stocks in SET, using the correlation and the Fisher information distance between stocks in different time windows. The Fisher information distance is more robust, can provide earlier information, and yields a much-slower decay of signal-to-noise ratio as the averaging window size increases. As the hierarchical clustering evolves during a period of a financial crisis, its structure has lower tendency than usual to change the clusters, as evidenced by the low variation of information and anticorrelation of stocks. The dynamic hierarchical using the Fisher information distance gives less-variant clustering and can shed some insight on stock behaviors during a financial crisis.
AB - We examine the behaviors of stocks in the Stock Exchange of Thailand (SET) during financial crises from 2008 to 2020 by using a variety of indicators such as average entropy, average correlation, and average Fisher information distance. All of these indicators increased dramatically during a financial crisis, which agreed with the Ulcer index indicating the root mean square of the percentage price drawdown. We investigate the dynamics of the hierarchical tree structure of 37 stocks in SET, using the correlation and the Fisher information distance between stocks in different time windows. The Fisher information distance is more robust, can provide earlier information, and yields a much-slower decay of signal-to-noise ratio as the averaging window size increases. As the hierarchical clustering evolves during a period of a financial crisis, its structure has lower tendency than usual to change the clusters, as evidenced by the low variation of information and anticorrelation of stocks. The dynamic hierarchical using the Fisher information distance gives less-variant clustering and can shed some insight on stock behaviors during a financial crisis.
KW - Financial robustness
KW - Fisher information
KW - Hierarchical tree structure
KW - Variation of information
UR - http://www.scopus.com/inward/record.url?scp=85139011301&partnerID=8YFLogxK
U2 - 10.1016/j.physa.2022.128183
DO - 10.1016/j.physa.2022.128183
M3 - Article
AN - SCOPUS:85139011301
SN - 0378-4371
VL - 607
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
M1 - 128183
ER -