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

DOI:

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

Keywords:

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

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.

References

Abdullah, A. M., & Aman, A. (2024). Energy prices and their impact on US stock indices: A wavelet-based quantile-on-quantile regression approach. International Journal of Energy Economics and Policy, 14(3), 216–234.

Adebayo, T. S., Akadiri, S. S., & Rjoub, H. (2022). On the relationship between economic policy uncertainty, geopolitical risk and stock market returns in South Korea: A quantile causality analysis. Annals of Financial Economics, 17(1), Article 2250008.

Ahmad, A. (2023). Financial development, exchange rate stability and trade in Nigeria. International Journal of Research and Innovation in Social Science, 7(11), 1552–1557.

Akighir, D. T. (2023). Foreign exchange market pressure, exchange rate and trade balance in Nigeria: Is there evidence of the J-curve effect? Journal of Developing Economies, 8(2).

Aldawsari, S. H., Tan, W. S., Elsherazy, T. A., Chang, B. H., Alzoubi, H. M., & Ognjanovic, I. (2024). A quantile dependence among exchange rate, stock prices and oil prices: An empirical evidence from India. Annals of Financial Economics, 19(2), Article 2450010.

Ali, W., Gohar, R., Chang, B. H., & Wong, W. K. (2022). Revisiting the impacts of globalization, renewable energy consumption, and economic growth on environmental quality in South Asia. Advances in Decision Sciences, 26(3), 78–98.

Almazyad, T., Maydybura, A., Chang, A. G., Channa, K. A., Pan, S. H., Alzoubi, H. M., & Chang, B. H. (2024). Carbon emissions and the rising effect of foreign direct investment and trade openness: Evidence from panel data countries. Advances in Decision Sciences, 28(4), 1–22.

Alsanusi, M., Altintas, H., & Alnour, M. (2022). The role of real exchange rate in the trade balance between Turkey and Libya: Evidence from nonlinear and wavelet-based approaches. Journal of Ekonomi, 4(2), 46–56.

Andini, C. (2025). Exchange-rate stability as a trade union's discipline device. Journal of Economic Studies. Advance online publication. https://doi.org/10.1108/JES-07-2024-0469

Arshad, R., Zada, H., Sohag, K., Wong, W. K., Ullah, E., & Raza, H. (2024). Does US monetary policy uncertainty affect returns of Asian developed, emerging, and frontier equity markets? Empirical evidence by using the quantile-on-quantile approach. Heliyon, 10(12), Article e32706.

Bagadeem, S., Gohar, R., Wong, W. K., Salman, A., & Chang, B. H. (2024). Nexus between foreign direct investment, trade openness, and carbon emissions: Fresh insights using innovative methodologies. Cogent Economics & Finance, 12(1), Article 2295721.

Banik, B., & Roy, C. K. (2021). Effect of exchange rate uncertainty on bilateral trade performance in SAARC countries: A gravity model analysis. International Trade, Politics and Development, 5(1), 32–50.

Bhatty, K. A., Laurinavicius, A., Laurinavicius, A., Chang, B. H., Alzoubi, H. M., & Channa, W. A. (2025). Impact of oil prices on Islamic stock prices: Evidence from Pakistan using bootstrap ARDL approach. Advances in Decision Sciences, 29(2), 1–35.

Bouri, E., Gupta, R., Marfatia, H. A., & Nel, J. (2025). Do climate risks predict US housing returns and volatility? Evidence from a quantiles-based approach. Annals of Financial Economics, 20(1), Article 2550004.

Caytuiro-Valle, A., Vilchez-Julca, C., & Cordova-Buiza, F. (2025). Exchange rate volatility and its impact on foreign trade: Evidence from Peru in a period of global and domestic turbulence (2019-2023). Investment Management and Financial Innovations, 22(4), 158–169.

Chang, B. H., Alzoubi, H. M., Salman, A., Chang, A. G., Uddin, M. A., & Khan, J. A. (2024a). The nexus between energy demand and currency valuation: Evidence from selected OECD countries. Annals of Financial Economics, 19(1), Article 2450002.

Chang, B. H., Auxilia, P. M., Kalra, A., Wong, W. K., & Uddin, M. A. (2023). Greenhouse gas emissions and the rising effects of renewable energy consumption and climate risk development finance: Evidence from BRICS countries. Annals of Financial Economics, 18(3), Article 2350007.

Chang, B. H., Saxena, A. K., Privara, A., Uddin, M. A., & Cruz, S. (2024b). Asymmetric effects of local and global variables on domestic food prices in China: An evidence from quantile on quantile regression technique. Journal of International Commerce, Economics and Policy, 15(3), Article 2450019.

Chen, N., Chung, W., & Novy, D. (2022). Vehicle currency pricing and exchange rate pass-through. Journal of the European Economic Association, 20(1), 312–351. https://doi.org/10.1093/jeea/jvab025

Chen, Z. (2022). The impact of trade and financial expansion on volatility of real exchange rate. PLoS ONE, 17(1), Article e0262230.

Cheng, Y., Hui, Y., Liu, S., & Wong, W. K. (2022). Could significant regression be treated as insignificant: An anomaly in statistics? Communications in Statistics: Case Studies, Data Analysis and Applications, 8(1), 133–151.

Cheng, Y., Hui, Y., McAleer, M., & Wong, W. K. (2021). Spurious relationships for nearly non-stationary series. Journal of Risk and Financial Management, 14(8), Article 366.

Dornbusch, R. (1976). Expectations and exchange rate dynamics. Journal of Political Economy, 84(6), 1161–1176. https://doi.org/10.1086/260506

Dridi, I., Gafrej, O., & Salhi, J. (2026). Determinants of reward crowdfunding success for technology projects: The moderating role of platform age. Advances in Decision Sciences, 30(2), 68–113.

Dudzich, V. (2020). Relationships between exchange rate regime, real exchange rate volatility and currency structure of government bonds in emerging markets. Review of Economic Perspectives, 20(1), 3–22.

Edgeworth, F. Y. (1888). On a new method of reducing observations relating to several quantities. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, 25(154), 184–191.

Edoja, P. E., Aye, G. C., & Gupta, R. (2024). Effects of energy consumption, agricultural trade, and productivity on carbon emissions in Nigeria: A quantile regression approach. Commodities, 3(4), 494–511.

Effiom, L., & Uche, E. (2021). Oil price, exchange rate and stock price in Nigeria: Fresh insights based on quantile ARDL model. Economics and Policy of Energy and Environment, 2021(1), 59–79.

Fan, L., Chang, B. H., & Kim, E. (2025). Green total factor productivity and its nonlinear relationship with coordinated FDI development: Evidence from panel models. Natural Resource Modeling, 38(1), Article e12418.

Galton, F. (1886). Regression towards mediocrity in hereditary stature. The Journal of the Anthropological Institute of Great Britain and Ireland, 15, 246–263.

Gayweh, D. (2025). Impact of exchange rate volatility on sectoral output in Liberia. Journal of Economics, Management and Trade, 31(1), 41–50.

Ghosh, S. (2023). COVID-19, stock market, exchange rate, oil prices, unemployment, inflation, geopolitical risk nexus, the case of the BRICS nations: Evidence quantile regression. In Research anthology on macroeconomics and the achievement of global stability (pp. 1811–1830). IGI Global.

Gohar, R., Bhatty, K., Osman, M., Wong, W. K., & Chang, B. H. (2022). Oil prices and sectorial stock indices of Pakistan: Empirical evidence using bootstrap ARDL model. Advances in Decision Sciences, 26(4), 1–27.

Gohar, R., Salman, A., Uche, E., Derindag, O. F., & Chang, B. H. (2023). Does US infectious disease equity market volatility index predict G7 stock returns? Evidence beyond symmetry. Annals of Financial Economics, 18(2), Article 2250028.

Guo, Y., Wong, W. K., Su, N., Ghardallou, W., Gavilan, J. C. O., Uyen, P. T. M., & Cong, P. T. (2023). Resource curse hypothesis and economic growth: A global analysis using bootstrapped panel quantile regression analysis. Resources Policy, 85, Article 103790.

Gupta, M., & Varshney, S. (2021). Exchange rate volatility and import trade flow: Evidence from India-US at industry level. International Journal of Asian Business and Information Management, 12(3), 1–21.

Hadebe, N., & Msomi, S. (2023). Focusing on the exchange rate volatility and international trade relationship: Evidence from South Africa. Journal of Management and Economics, 8(3).

Hashmi, S. M., Chang, B. H., Huang, L., & Uche, E. (2022). Revisiting the relationship between oil prices, exchange rate, and stock prices: An application of quantile ARDL model. Resources Policy, 75, Article 102543.

He, P., & Zhao, N. (2024). The effects of artificial intelligence on oil shocks: Evidence from a wavelet-based quantile-on-quantile approach. Review of Economic Assessment, 3(2), 56–71.

Hidayah, N. (2024). Exchange rate volatility and international trade in Turkey. International Journal of Finance and Accounting, 9(1), 46–56.

Hoang, D. C., & Tuan, D. C. (2023). Evaluating the role of green financing, international trade and alternative energies on environmental performance in case of Chinese provinces: Application of quantile regression approach. International Journal of Energy Economics and Policy, 13(2), 500–508.

Hoxhaj, M., Habili, M., & Qorri, D. (2025). Currency fluctuations and trade balance: Assessing EUR-ALL exchange rate effects in Albania. WSEAS Transactions on Business and Economics, 22, 768–772.

Hui, Y., Wong, W. K., Bai, Z., & Zhu, Z. Z. (2017). A new nonlinearity test to circumvent the limitation of Volterra expansion with application. Journal of the Korean Statistical Society, 46, 365–374.

Ijasan, K., Owusu Junior, P., Tweneboah, G., Oyedokun, T., & Adam, A. M. (2021). Analyzing the relationship between global REITs and exchange rates: Fresh evidence from frequency-based quantile regressions. Advances in Decision Sciences, 25(3), 58–91.

Imane, E., Chang, B. H., Elsherazy, T. A., Wong, W. K., & Uddin, M. A. (2023). The external exchange rate volatility influence on the trade flows: Evidence from nonlinear ARDL model. Advances in Decision Sciences, 27(2), 75–98.

Imane, E., & Ghizlane, K. (2025). Exploring tail risk transmission between volatility indices and cryptocurrencies: Evidence from quantile connectedness. Advances in Decision Sciences, 29(3), 119–157.

Jin, X., Chang, B. H., Han, C., & Uddin, M. A. (2025). The tail connectedness among conventional, religious, and sustainable investments: An empirical evidence from neural network quantile regression approach. International Journal of Finance & Economics, 30(2), 1124–1142.

Juarez, L. (2024). Research insights: How does buyer market power influence exchange rate pass-through in international trade? [Working paper].

Kim, C.-B. (2023). Effect of trade policy uncertainty spillover on exchange rate volatility in Korea, China, and Japan: The application of network connectedness analysis and panel PMG methods. Journal of International Trade & Commerce, 19(3), 215–229.

Kirikkaleli, D., Athari, S. A., Olushola, O. V., & Hassan, H. (2025). Financial risk and investment in artificial intelligence in the USA: A fresh evidence from quantile wavelet regression and quantile wavelet correlation tests. The Journal of Risk Finance, 26(4), 639–652.

Koenker, R. (2000). Galton, Edgeworth, Frisch, and prospects for quantile regression in econometrics. Journal of Econometrics, 95(2), 347–374. https://doi.org/10.1016/S0304-4076(99)00043-3

Koenker, R., & Bassett, G., Jr. (1978). Regression quantiles. Econometrica, 46(1), 33–50. https://doi.org/10.2307/1913643

Krishnan, D., & Dagar, V. (2022). Exchange rate and stock markets during trade conflicts in the USA, China, and India. Global Journal of Emerging Market Economies, 14(2), 185–203.

Laurinavicius, A., Vongmileuth, C., Vongmileuth, S., Laurinavicius, A., Pan, S. H., & Chang, B. H. (2025). Energy demand response to the dynamics of the currency valuation: Evidence from G7 countries. Advances in Decision Sciences, 29(1), 1–34.

Le, T. T. M., Martin, F., & Nguyen, D. K. (2023). Tail risk transmission in the foreign exchange market: A quantile LASSO regression approach. In Contemporary financial management (pp. 607–623).

Li, M., & Koh, E.-H. (2024). A study on the exchange rate linkage between Korea and China following the reform of the yuan exchange rate system. Journal of Korea Trade, 28(2), 103–128.

Lima, M., & Islam, T. (2023). Estimating the exchange rate volatility and its impact on international trade flow: Evidence from Bangladesh. Journal of Finance, 20(1–2).

Mallick, L., Behera, S. R., & Bhattacharya, M. (2024). Impact of exchange rate on trade balance of India: Evidence from threshold cointegration with asymmetric error correction approach. Foreign Trade Review, 59(2), 279–308. https://doi.org/10.1177/00157325231158855

Mansouri, Z., Liouaeddine, M., & Laamire, J. (2024). The analysis of the link between the exchange rate and inflation: Evidence from a quantile regression approach (SSRN Working Paper No. 4707059). SSRN. https://doi.org/10.2139/ssrn.4707059

Maydybura, A., Gohar, R., Salman, A., Wong, W. K., & Chang, B. H. (2023). The asymmetric effect of the extreme changes in the economic policy uncertainty on the exchange rates: Evidence from emerging seven countries. Annals of Financial Economics, 18(2), Article 2250031.

Mendali, G., & Das, S. (2024). Asymmetric exchange rate pass-through in India: A non-linear ARDL approach. Foreign Trade Review, 59(3), 429–447. https://doi.org/10.1177/00157325231190474

Nam, S., Lu, G., & Moon, J.-Y. (2023). Volatility, volume, and FX policy uncertainty: Evidence from Seoul and Shanghai Chinese-Korean direct exchange rate market. Journal of International Trade, 19(2), 51–63.

Ng, P., Wong, W. K., & Xiao, Z. (2017). Stochastic dominance via quantile regression with applications to investigate arbitrage opportunity and market efficiency. European Journal of Operational Research, 261(2), 666–678.

Ngondo, M., & Phiri, A. (2024). The effect of exchange rate volatility on trade between South Africa and her top trading partners: Fresh insights from ARDL and quantile ARDL models. Managing Global Transitions, 22(3).

Ogede, J. S., & Adegboyega, S. B. (2021). Heterogeneous impact of oil price volatility on exchange rate in African countries: Evidence from quantile regression approach. Studies of Applied Economics, 39(8).

Olubiyi, E., & Biala, M. (2022). Asymmetry behaviour of real exchange rate volatility and trade flows: A bilateral analysis [Working paper].

Ouattara, Z. (2023). The impact of exchange rate volatility on international trade in developing countries: Evidence from Turkiye. Press Academia Procedia, 17(1), 140–148.

Oyadeyi, O. O. (2024). The macroeconomic determinants of exchange rate volatility and the impact of currency volatility on the performance of the Nigerian economy. Foreign Trade Review. Advance online publication.

Parray, W. A., Bhat, J. A., Yasmin, E., & Bhat, S. A. (2023). Exchange rate changes and the J-curve effect: Asymmetric evidence from a panel of five emerging market economies. Foreign Trade Review, 58(4), 524–543.

Percival, D. B., & Walden, A. T. (2000). Wavelet methods for time series analysis. Cambridge University Press.

Privara, A., Gohar, R., Alzoubi, H. M., Kalra, A., Uddin, M. A., & Chang, B. H. (2025). Exploring exchange rate sensitivity to crude oil futures: A study of selected global economies. International Economics and Economic Policy, 22(1), Article 5.

Qureshi, A. H. (2021). US surveillance of foreign currency exchange and macroeconomic practices. World Trade Review, 20(5), 690–706.

Ramsey, J. B., & Lampart, C. (1998a). The decomposition of economic relationships by time scale using wavelets: Expenditure and income. Studies in Nonlinear Dynamics and Econometrics, 3(1), 23–42.

Ramsey, J. B., & Lampart, C. (1998b). Decomposition of economic relationships by timescale using wavelets. Macroeconomic Dynamics, 2(1), 49–71.

Ramzan, M., Adebayo, T. S., Iqbal, H. A., Razi, U., & Wong, W. K. (2023). Analyzing the nexus between financial risk and economic risk in India: Evidence through the lens of wavelet coherence and non-parametric approaches. Heliyon, 9(3), Article e14180.

Rashid, A., & Basit, M. (2022). Empirical determinants of exchange-rate volatility: Evidence from selected Asian economies. Journal of Chinese Economic and Foreign Trade Studies, 15(1), 63–86.

Rattanapanurak, J. (2017). Effect of exchange rate volatility on currency carry trade and risk factor compensation of currency carry trade in G10 and emerging market [Working paper].

Raup o'g'li, S. Z. (2025). Mechanism for optimizing interbank currency exchange to enhance market liquidity and ensure exchange rate stability. Journal of Management and Economics, 5(4), 59–62.

Rehman, A., & Batool, S. (2024). Currency exchange rate volatility: Consequences on international trade in Pakistan. Pakistan Journal of Humanities and Social Sciences, 12(3), 2569–2579.

Rehman, K. U., & Chen, R. (2025). Monetary policy uncertainty and green finance resilience: A wavelet quantile on quantile approach in developed economies. Journal of International Commerce, Economics and Policy. Advance online publication.

Rehman, K. U., & Ghouse, G. (2024). Examining inflation expectations within Asian economies: Application of wavelet quantile analysis towards assessing monetary policy credibility. Journal of Economic Impact, 6(1), 70–80.

Sahin, G., & Sahin, A. (2023). An empirical examination of asymmetry on exchange rate spread using the quantile autoregressive distributed lag (QARDL) model. Journal of Risk and Financial Management, 16(1), Article 38.

Saint Akadiri, S., & Olanipekun, I. O. (2025). Trade policy uncertainty and renewable energy transition in MENA: A quantile regression approach. Asian Economic and Financial Review, 15(11), 1774–1785.

Salman, A., Chang, B. H., Abdul Razzaq, M. G., Wong, W. K., & Uddin, M. A. (2023). The emerging stock markets and their asymmetric response to infectious disease equity market volatility (ID-EMV) index. Annals of Financial Economics, 18(2), Article 2350008.

Saygili, H. (2023). Invoicing currency, exchange rate pass-through, and value-added trade: The case of Turkey. International Journal of Finance & Economics, 28(4), 4401–4419. https://doi.org/10.1002/ijfe.2657

Sim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking & Finance, 55, 1–8. https://doi.org/10.1016/j.jbankfin.2015.01.013

Singh, S. (2025). Exchange rate variability and India's bilateral trade with the USA and China [Working paper].

Sohrabji, N. (2024). Asymmetric exchange rate effects on trade flows in India [Working paper].

Sunde, T. (2025). Impact of trade openness and exchange rate volatility on South Africa's industrial growth: Assessment using ARDL and SVAR models. Sustainability, 17(11), Article 4933.

Tetin, I., Antonenko, E., & Nuryyev, G. (2023). Asymmetric effects of exchange rate volatility on Taiwan-China trade: A non-linear ARDL analysis of 20 industries. Bulletin of Applied Economics, 10(2), 173–189.

Uddin, M. A., Chang, B. H., Aldawsari, S. H., & Li, R. (2025). The interplay between green finance, policy uncertainty and carbon market volatility: A time frequency approach. Sustainability, 17(3), Article 1198.

Uzair, L., Amin, B., & Amin, S. (2022). Yuan as a medium of trade: Volatility in bilateral exchange rate of China and Pakistan. Forman Journal of Economic Studies, 18(1).

Vongmileuth, C., Yeniley, U., Auxilia, P. M., Ahmed, H. M. S., Wong, W. K., & Chang, B. H. (2025). Wavelet coherency analysis of stock market volatility and housing costs: Insights from international financial hubs. Annals of Financial Economics, 20(1), Article 2550012.

Wang, K. (2025). Modeling the impact of exchange rate volatility on trade flows: Evidence from AUD/USD and China-Australia trade. Advances in Economics, Management and Political Sciences, 211, 197–201.

Wang, M. (2025). Trade policy uncertainty and exchange rate volatility: Evidence from the 2025 U.S.-China tariff announcement. Advances in Economics, Management and Political Sciences, 193, 262–270.

Wieloch, J., Becerril-Torres, O. U., & Vazquez, G. M. (2024). Trade war or currency war? How do import duties translate into the RMB/USD exchange rate? International Journal of Management and Economics, 61(2), 97–109.

Wong, W. K., Cheng, Y., & Yue, M. (2024). Could regression of stationary series be spurious? Asia-Pacific Journal of Operational Research, 41(2), Article 2440017.

Wong, W. K., & Pham, M. T. (2022a). Could the test from the standard regression model make significant regression with autoregressive noise become insignificant? The International Journal of Finance, 34, 1–18.

Wong, W. K., & Pham, M. T. (2022b). Could the test from the standard regression model make significant regression with autoregressive noise become insignificant - A note. The International Journal of Finance, 34, 19–39.

Wong, W. K., & Pham, M. T. (2023a). Could the test from the standard regression model make significant regression with autoregressive Yt and Xt become insignificant? The International Journal of Finance, 35, 1–19.

Wong, W. K., & Pham, M. T. (2023b). Could the test from the standard regression model make significant regression with autoregressive Yt and Xt become insignificant - A note. The International Journal of Finance, 35, 20–41.

Wong, W. K., & Pham, M. T. (2025a). Could the correlation of a stationary series with a non-stationary series obtain meaningful outcomes? Annals of Financial Economics. Advance online publication.

Wong, W. K., & Pham, M. T. (2025b). How to model a simple stationary series with a non-stationary series? The International Journal of Finance, 37, 1–19.

Wong, W. K., & Pham, M. T. (2026a). Could the panel regression be used to examine the relationship between I(0) and I(1) series? Advances in Decision Sciences, 30(2). Advance online publication.

Wong, W. K., & Pham, M. T. (2026b). Could we use correlation to examine panel data with I(0) and I(1) variables? The International Journal of Finance, 38. Advance online publication.

Wong, W. K., Pham, M. T., & Yue, M. (2024). Could regressing a stationary series on a non-stationary series obtain meaningful outcomes - A remedy. The International Journal of Finance, 36, 1–20.

Wong, W. K., & Yue, M. (2024). Could regressing a stationary series on a non-stationary series obtain meaningful outcomes? Annals of Financial Economics, 19(3), Article 2450011.

Xu, J. (2023). Exchange rate risk management of foreign trade enterprises. BCP Business & Management, 38, 1292–1298.

Yang, Z., Wang, M. C., Chang, T., Wong, W. K., & Li, F. (2022). Which factors determine CO2 emissions in China? Trade openness, financial development, coal consumption, economic growth or urbanization: Quantile Granger causality test. Energies, 15(7), Article 2450.

Yoshimori, M. (2025). Asymmetric currency turbulence with US dollar/Japanese yen carry trade: Insights into central bank interventions and exchange-rate dynamics. Financial Markets, Institutions and Risks, 9(1), 74–98.

Zada, H., Mansoor, A., Khan, N., Wong, W. K., & Jibir, A. (2026). Monetary policy uncertainty and stock market returns in developed and emerging countries: Evidence from a quantile-on-quantile approach. Advances in Decision Sciences, 30(3), 89–113.

Zhang, D., Wang, X., Gao, L., & Gong, Y. (2021). Predict and analyze exchange rate fluctuations accordingly based on quantile regression model and K-nearest neighbor. Journal of Physics: Conference Series, 1813(1), Article 012016.

Published

2026-08-04

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