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

• Published date: 01 March 2023
• Author: Emmanuel Joel Aikins Abakah,Aviral Kumar Tiwari,Chi‐Chuan Lee,Matthew Ntow‐Gyamfi
• Date: 01 March 2023
• DOI: http://doi.org/10.1111/irfi.12393

ORIGINAL ARTICLE

Quantile price convergence and spillover

effects among Bitcoin, Fintech, and artificial

intelligence stocks

Emmanuel Joel Aikins Abakah

1

| Aviral Kumar Tiwari

2

|

Chi-Chuan Lee

3

| Matthew Ntow-Gyamfi

1

1

Department of Finance, University of Ghana

Business School, Accra, Ghana

2

Indian Institute of Management Bodh Gaya,

Bodh Gaya, India

3

School of Public Administration,

Southwestern University of Finance and

Economics, Chengdu, China

Correspondence

Chi-Chuan Lee, School of Public

Administration, Southwestern University of

Finance and Economics, Room 1105, Gezhi

Building, No.555 Liutai Ave, Wenjiang

District, Chengdu, China.

Email: leechichuan@swufe.edu.cn

Abstract

This research explores the distributional and directional pre-

dictabilities among Fintech, Bitcoin, and artificial intelligence

stocks from March 2018 to January2021 using nonparamet-

ric 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 highlypositive and

negative changes. These results further document the diver-

sification potential and safe-haven properties of technology-

related assets for portfolio investors.

KEYWORDS

artificial intelligence, Bitcoin, Fintech, predictability, quantile

causality

JEL CLASSIFICATION

C32, C58, G10, G12

1|INTRODUCTION

In recent years, the financial landscape across the globe has witnessed swift modifications following the rapidly

evolving technology environment and the corresponding emergence of technology-related asset markets

Received: 30 January 2022 Revised: 4 August 2022 Accepted: 6 September 2022

DOI: 10.1111/irfi.12393

© 2022 International Review of Finance Ltd.

International Review of Finance. 2023;23:187–205. wileyonlinelibrary.com/journal/irfi 187

(Arslanian & Fischer, 2019). Among these changes, one of the most heated topics attracting academic and practical

attention has been whether and how markets with different characteristics and purposes integrate with each other.

Different opinions have been raised. Some note that the increasing integration, which has further birthed connected-

ness, is because of the nature of the markets (Lee et al., 2022; Lee, Lee, & Li, 2021; Uddin et al., 2019), while others

argue that the close connection among markets is caused by the process of globalization (Le, Abakah, &

Tiwari, 2021; Mensi et al., 2019). More recent studies even emphasize that markets become highly integrated during

extreme events such as financial crises (Caporale et al., 2014; Labidi et al., 2018) and coronavirus disease (COVID-

19) outbreaks (Adekoya & Oliyide, 2021; Haroon & Rizvi, 2020; Lee, Lee, & Wu, 2021).

Technology-related assets (also called 21st-century assets) are alternative emerging asset classes driven mainly

by technology. It is worth mentioning that the technology-driven asset classes include cryptocurrencies, financial

technology (Fintech), and artificial intelligence and robotics (AI). These assets have become highly prominent in the

investment scene after the 2008 global financial crisis, with the literature deliberating on the all-pervading impor-

tance of such assets (Abakah et al., 2020; Shahzad et al., 2019; Tiwari et al., 2021). The significant role of

technology-related assets to portfolio investors, coupled with the rapid forces of global financial market integration,

has prompted a cumulating spillover from a range of emerging technology asset markets to traditional asset markets

(Gil-Alana et al., 2020; Le, Abakah, & Tiwari, 2021; Umar et al., 2021). So far, a growing stream of literature has

explored the connectedness between technology-related assets and other traditional assets, with most studies

focusing on cryptocurrencies. For example, Bhuiyan et al. (2021) examined the interdependencies between Bitcoin

and conventional assets, such as gold, oil, US Dollar index, and Dow Jones index. Similarly, Gil-Alana et al. (2020)

assessed the integration of cryptocurrency markets and stock markets, while Le, Abakah, and Tiwari (2021) explored

the connectedness among Fintech, green bonds, and cryptocurrencies. Other studies, including Vergara and Agudo

(2021), reveal that Fintech has the potential to make the entire financial industry more sustainable by fostering envi-

ronmentally responsible financing. In addition, Huynh et al. (2020) provide empirical evidence on the relationship

between AI, green bonds, and cryptocurrencies.

While the above-mentioned studies help our understanding of the global integration of technology-related

assets with global stock markets and green bonds, knowledge of domestic integration is limited to only the interde-

pendencies between Fintech and cryptocurrencies. We extend the literature on the domestic integration of

technology-related assets by examining quantile price convergence and spillover effects among Bitcoin, Fintech, and

AI markets in the wake of the fourth industrial revolution. We assess the level of connectedness and predictability

among these markets for the following reasons. First, the interconnection of financial markets and the synchroniza-

tion of business cycles are essential factors in market turbulence and spillover (Nasir & Du, 2018). Given that price

fluctuations of these technology-related assets cause ripple effects that affect major financial markets sequentially

(Le, Abakah, & Tiwari, 2021), it is important to investigate how these technology-related assets correlate for the pur-

pose of diversification. Second, extreme events enhance market interconnectedness and financial contagion.

Technology-related assets can provide more investment strategies, resulting in a more diversified portfolio. There-

fore, the thrust of the current research is to assess the price convergence, distributional predictability,and directional

predictability among Bitcoin, Fintech, and AI stocks.

Fintech combines the use of modern technology and innovation in the provision of financial services (Le,

Abakah, & Tiwari, 2021; Lee, Li, Yu, & Zhao, 2021; Zhao et al., 2022). The provision of technology-oriented financial

products and services has attracted a wide array of customers as these products and services extend beyond con-

ventional financial intermediation services and even include risk management and insurance, asset management, and

other third-party services (Anagnostopoulos, 2018). The ease of conducting business, real-time information sharing,

and the provision of up-to-date security have contributed to increasing interest in Fintech markets. Gai et al. (2018)

indicate that improvement in the Fintech space has evolved into areas such as mobile network transactions, large

data, and data analytic techniques. As an important pillar of Fintech, the operations of a cryptocurrency are growing

with the rapid development of Fintech (Shrestha, 2021). By extension, the application of Fintech to blockchain and

cryptocurrency has seen much relevance in financial markets as it offers secure platforms for transactions. In

188 ABAKAH ET AL.