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Publication date: 23 January 2025

Muzammal Ilyas Sindhu, Windijarto, Wing-Keung Wong and Laila Maswadi

The study aimed to determine the static return connectedness between Brazil, Russia, India, China and South Africa (BRICS) equity markets and crypto assets.

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Abstract

Purpose

The study aimed to determine the static return connectedness between Brazil, Russia, India, China and South Africa (BRICS) equity markets and crypto assets.

Design/methodology/approach

The study employs the time-varying parameter vector autoregression (TVP-VAR) method to examine the static and dynamic connectedness between crypto assets and the BRICS stock market. The study sample size was segmented into full sample, pre-COVID-19 and post-COVID-19 for in-depth analysis.

Findings

Empirical findings pointed out the significant rise in the total connectedness between both markets in the pre-COVID-19 period. Our result also exhibits a lower level of connectedness during the post-COVID-19 period. During the full sample period, it was found that cryptocurrencies and Indian, Chinese and South African stock markets remained key return transmitters, while Russian and Brazilian stock markets were seen as recipients. Moreover, during the pre-COVID period, cryptocurrencies played the role of return transmitter while the stock markets in BRICS remained recipients of return spillover.

Practical implications

This study contains practical insights for investors and portfolio managers in diversifying their portfolios considering the aforementioned connectivity of both markets, especially during periods of instability.

Originality/value

The study highlighted the importance of the TVP-VAR method in analyzing the static and dynamic connectedness of returns between cryptocurrencies and BRICS stock markets in different periods, including pre- and post-COVID-19. It further pragmatized the dynamic roles of cryptocurrencies as transmitters of returns and the BRICS stock markets as receivers where investors and policymakers can navigate market uncertainties.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

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