Exchange Rate Dynamics and Its Spillover Effect among the BRICS Nations

The recent financial crisis in the United States, followed by Europe’s debt crisis, has significantly impacted global economic performance, particularly in the financial sector. Globalization has led to increased interdependence and growth in international trade. This paper examines exchange rate return spillovers and connectedness among BRICS countries’ currencies against the US Dollar using Diebold and Yilmaz’s methodology. By analyzing weekly data from April 2004 to March 2023, we find low spillover levels between these currency pairs. The Indian Rupee is identified as a net transmitter, while the South African Rand is a net receiver. Notably, the Indian Rupee and Chinese Yuan show no Granger causality with other currencies, whereas the Russian Ruble, Brazilian Real, and South African Rand display univariate relationships. These insights can aid traders, portfolio managers, policymakers, and market participants in identifying volatility sources and making informed investment decisions.

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Publication Details

Journal
MUDRA Journal of Finance and Accounting
Published
2025-05-03
DOI
https://doi.org/10.17492/jpi.mudra.v12i1.1212502
Primary Topic
Global trade and economics
Type
article
Field-Weighted Citation Impact
0.00
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article

Exchange Rate Dynamics and Its Spillover Effect among the BRICS Nations

A. Karmakar, Sourav Chakraborty, M. Roy, Bhaskar Goswami
MUDRA Journal of Finance and Accounting
Global trade and economics
article

Exchange Rate Dynamics and Its Spillover Effect among the BRICS Nations

A. Karmakar, Sourav Chakraborty, M. Roy, Bhaskar Goswami
article en

Abstract

The recent financial crisis in the United States, followed by Europe’s debt crisis, has significantly impacted global economic performance, particularly in the financial sector. Globalization has led to increased interdependence and growth in international trade. This paper examines exchange rate return spillovers and connectedness among BRICS countries’ currencies against the US Dollar using Diebold and Yilmaz’s methodology. By analyzing weekly data from April 2004 to March 2023, we find low spillover levels between these currency pairs. The Indian Rupee is identified as a net transmitter, while the South African Rand is a net receiver. Notably, the Indian Rupee and Chinese Yuan show no Granger causality with other currencies, whereas the Russian Ruble, Brazilian Real, and South African Rand display univariate relationships. These insights can aid traders, portfolio managers, policymakers, and market participants in identifying volatility sources and making informed investment decisions.

MUDRA Journal of Finance and AccountingVol. 12(1)
Openalex Percentile: Top 86%
Global trade and economics
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