TY - JOUR
T1 - Co-movements between Shanghai Composite Index and some fund sectors in China
AU - Wang, Jian
AU - Shao, Wei
AU - Ma, Chenmin
AU - Chen, Wenbing
AU - Kim, Junseok
N1 - Funding Information:
The corresponding author (J.S. Kim) expresses gratitude for the support from the BK21 FOUR, Republic of Korea program. The authors appreciate the reviewers for their constructive comments, which have improved the quality of this paper.
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/7/1
Y1 - 2021/7/1
N2 - In this article, we analyzed the cross-correlations between Shanghai Composite Index (SSEC) and some fund sectors in China. Four high-volume fund sectors such as finance, medicine, new energy, and consumption sectors were investigated. Multifractal Cross-Correlation Analysis (MFCCA) approach was conducted for the empirical researches of the long-range correlations for time series pairs. The obtained multifractal characteristics showed that the finance sector achieved the highest persistence of cross-correlations, then the new energy, consumption, and medicine sector. Furthermore, the Δλ of finance sector is the greatest among other sectors, which indicated that the multifractality of cross-correlations between SSEC and finance sector was the strongest, and then the medicine sector has the weakest multifractality of cross-correlations. In addition, we utilized one-tailed Student's t-test to further evaluate the multifractality of cross-correlations, the results verified our conclusion.
AB - In this article, we analyzed the cross-correlations between Shanghai Composite Index (SSEC) and some fund sectors in China. Four high-volume fund sectors such as finance, medicine, new energy, and consumption sectors were investigated. Multifractal Cross-Correlation Analysis (MFCCA) approach was conducted for the empirical researches of the long-range correlations for time series pairs. The obtained multifractal characteristics showed that the finance sector achieved the highest persistence of cross-correlations, then the new energy, consumption, and medicine sector. Furthermore, the Δλ of finance sector is the greatest among other sectors, which indicated that the multifractality of cross-correlations between SSEC and finance sector was the strongest, and then the medicine sector has the weakest multifractality of cross-correlations. In addition, we utilized one-tailed Student's t-test to further evaluate the multifractality of cross-correlations, the results verified our conclusion.
KW - Fund
KW - Hurst exponent
KW - Multifractality
KW - SSEC
UR - http://www.scopus.com/inward/record.url?scp=85104083542&partnerID=8YFLogxK
U2 - 10.1016/j.physa.2021.125981
DO - 10.1016/j.physa.2021.125981
M3 - Article
AN - SCOPUS:85104083542
SN - 0378-4371
VL - 573
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
M1 - 125981
ER -
