Interest in cryptocurrencies predicts conditional correlation dynamics
被引:9
|
作者:
Chuffart, Thomas
论文数: 0引用数: 0
h-index: 0
机构:
Univ Paris Nanterre, EconomiX CNRS, Nanterre, France
Univ Franche Comte, CRESE, Besancon, FranceUniv Paris Nanterre, EconomiX CNRS, Nanterre, France
Chuffart, Thomas
[1
,2
]
机构:
[1] Univ Paris Nanterre, EconomiX CNRS, Nanterre, France
Bitcoin;
Cryptocurrencies;
Conditional correlations;
Google searches data;
BITCOIN;
CURRENCY;
D O I:
10.1016/j.frl.2021.102239
中图分类号:
F8 [财政、金融];
学科分类号:
0202 ;
摘要:
Using a Smooth Transition Conditional Correlation model with Google search data as a transition variable, I investigate correlation dynamics between a set of crypto-currencies. A major change in the correlation dynamics after the 2017 bubble burst is explained by the attention subsequently surrounding cryptocurrencies. Google searches are found to be a good predictor of correlation between cryptocurrencies and could provide useful input to portfolio management.
机构:
Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R China