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Advances in Decision Sciences (ADS)

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Does Settling Trade in National Currency Stabilize the Rupee? Nonlinear, Asymmetric, and Horizon-Dependent Evidence from India

Does Settling Trade in National Currency Stabilize the Rupee? Nonlinear, Asymmetric, and Horizon-Dependent Evidence from India

Title

Does Settling Trade in National Currency Stabilize the Rupee? Nonlinear, Asymmetric, and Horizon-Dependent Evidence from India

Authors

  • Antanas Laurinavicius
    Department of Finance, Faculty of Economics and Business Administration, Vilnius University, Vilnius, Lithuania
  • Hussein Moselhy Sayed Ahmed
    Department of Business Administration, College of Business, University of Bisha, Saudi Arabia
    Kafrelsheikh University, Egypt
  • Algimantas Laurinavicius
    Department of Finance, Faculty of Economics and Business Administration, Vilnius University, Vilnius, Lithuania
  • Safaa Sayed Mahmoud
    Department of Business Administration, College of Business, University of Bisha, Bisha 61922, Saudi Arabia
    Professor, Ain Shams University, Egypt
  • Komolov Odiljon Sayfidinovich
    Department of International Finance, Tashkent State University of Economics, 100066, Tashkent, Uzbekistan

Abstract

Purpose – This study asks whether settling international trade in the national currency enhances exchange rate stability in India, and whether the relationship is nonlinear, asymmetric, and horizon-dependent. Motivated by the Reserve Bank of India’s 2022 framework for international trade settlement in rupees and the broader fragmentation of the dollar-centric monetary order, it addresses a gap left by linear, mean-based studies.
Design/methodology/approach – Using monthly data from April 2002 to September 2025 (282 observations), the study combines maximal-overlap wavelet decomposition with quantile-on-quantile regression (WQQR) to estimate how a standardized National Currency Trade Settlement Index (NCTSI), a constructed proxy, relates to INR/USD exchange rate volatility (the inverse of stability) across short-, medium-, and long-run horizons and across the full distribution of both variables.
Findings – The aggregate association is modestly negative, but this masks pronounced heterogeneity. Over long horizons, national-currency settlement is significantly and negatively associated with volatility across most of the distribution, with the association strongest in high-volatility (turbulent) regimes; over medium horizons, it is weak and occasionally positive; and over short horizons, it is statistically negligible. The patterns are robust to alternative volatility measures, an alternative wavelet basis, and a post-2022 sub-sample that isolates the rupee-settlement framework era.
Implications – The results support an invoicing- and settlement-currency interpretation in which reduced reliance on a vehicle currency dampens imported volatility only gradually and most powerfully when external pressure is acute. For policymakers, national-currency settlement operates over long rather than short horizons (conditional on the proxy used), complementing reserves and intervention during periods of external stress rather than substituting for them.
Originality/value – The paper provides, to our knowledge, among the first horizon- and regime-explicit assessments of the settlement-stability nexus for the Indian rupee, extending the invoicing- and vehicle-currency literatures to the volatility margin for a major emerging economy.

Keywords

National currency trade settlement, exchange rate volatility, rupee, quantile-on-quantile regression, wavelet decomposition, India

Classification-JEL

F31; F33; E58; C22; G15

Pages

249-282

How to Cite

Laurinavicius, A., Ahmed, H. M. S., LAURINAVICIUS, A., Mahmoud, S. S., & Sayfidinovich, K. O. (2026). Does Settling Trade in National Currency Stabilize the Rupee? Nonlinear, Asymmetric, and Horizon-Dependent Evidence from India. Advances in Decision Sciences, 30(3), 249-282.

https://doi.org/10.47654/v30y2026i3p249-282

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ISSN 2090-3359 (Print)
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Scientific and Business World

Asia University, Taiwan

8.3
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