Quantile price convergence and spillover effects among Bitcoin, Fintech, and artificial intelligence stocks

被引：48
作者：
Abakah, Emmanuel Joel Aikins [1 ]
Tiwari, Aviral Kumar [2 ]
Lee, Chi-Chuan [3 ]
Ntow-Gyamfi, Matthew [1 ]
机构：
[1] Univ Ghana Business Sch, Dept Finance, Accra, Ghana
[2] Indian Inst Management Bodh Gaya, Bodh Gaya, India
[3] Southwestern Univ Finance & Econ, Sch Publ Adm, Room 1105,Gezhi Bldg,555 Liutai Ave, Chengdu, Peoples R China
来源：
INTERNATIONAL REVIEW OF FINANCE | 2023年 / 23卷 / 01期
基金：
中国国家自然科学基金;
关键词：
artificial intelligence; Bitcoin; Fintech; predictability; quantile causality; CONSISTENT NONPARAMETRIC TEST; IMPULSE-RESPONSE ANALYSIS; FINANCIAL-MARKETS; CAUSALITY; GOLD; CRYPTOCURRENCY; DEPENDENCE; PREDICTABILITY;
D O I：
10.1111/irfi.12393
中图分类号：
F8 [财政、金融];
学科分类号：
0202 ;
摘要：
This research explores the distributional and directional predictabilities among Fintech, Bitcoin, and artificial intelligence stocks from March 2018 to January 2021 using nonparametric causality-in-quantile and crossquantilogram approaches. We also examine connectedness across the assets using a quantile VAR approach. The results indicate the existence of bidirectional causality-in-variance between the variables in a normal market. We also find that directional predictability among the assets is oscillatory over time lags. Finally, we observe a strong price connectedness for highly positive and negative changes. These results further document the diversification potential and safe-haven properties of technology-related assets for portfolio investors.
引用
收藏
页码：187 / 205
页数：19
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