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

被引：55

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

页码：187 / 205

页数：19

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