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New Evidence on Nonlinear Causal Relationships between the Cryptocurrency and the Foreign Exchange Markets

Author

Listed:
  • Xunfa Lu

    (Nanjing University of Information Science and Technology, School of Management Science and Engineering)

  • Zhijie Chu

    (Nanjing University of Information Science and Technology, School of Management Science and Engineering)

  • Nicholas Apergis

    (University of Piraeus, Department of Banking and Financial Management)

  • David Roubaud

    (Montpellier Business School, Department of Finance
    Gulf University for Science and Technology, Gulf Financial Center)

  • Kin Keung Lai

    (Shaanxi Normal University, International Business School)

Abstract

This paper applies a novel time-varying causality test as well as the wavelet coherence analysis, to investigate the nonlinear causal relationships between the cryptocurrency and the exchange rate markets, spanning the period January 3, 2017 to December 23, 2022. The time-varying causality test shows evidence of significant dynamic characteristics in the causal relationships between the cryptocurrency and the exchange rate markets for both the return and the volatility series across the sample period. Specifically, after the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, a unidirectional causality emerges from the cryptocurrency market to the exchange rate market at the return level, while a bidirectional causality is observed between the two markets at the volatility level. Furthermore, the wavelet coherence analysis enables us to determine the direction of causality and the correlation in the time-frequency domain. The results reveal that in the short term, extreme events amplify the causal relationships between the two markets at both the return and volatility levels, though the direction of causality is capricious. In the middle and long term, a significantly positive causal relationship emerges from the cryptocurrency market to the exchange rate market at the return level, while a positive causal link flows in the opposite direction at the volatility level. The findings offer useful insights for investors, policymakers, and regulators and contribute to the literature on the cryptocurrency markets, thus, providing certain reference, for future studies in this area.

Suggested Citation

  • Xunfa Lu & Zhijie Chu & Nicholas Apergis & David Roubaud & Kin Keung Lai, 2026. "New Evidence on Nonlinear Causal Relationships between the Cryptocurrency and the Foreign Exchange Markets," Computational Economics, Springer;Society for Computational Economics, vol. 68(2), pages 1311-1336, August.
    • Handle: RePEc:kap:compec:v:68:y:2026:i:2:d:10.1007_s10614-025-11097-7
    DOI: 10.1007/s10614-025-11097-7
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    1. Peter C. B. Phillips & Shuping Shi & Jun Yu, 2015. "Testing For Multiple Bubbles: Limit Theory Of Real‐Time Detectors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56, pages 1079-1134, November.
    2. Goodell, John W. & Goutte, Stephane, 2021. "Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis," Finance Research Letters, Elsevier, vol. 38(C).
    3. Andrada-Félix, Julián & Fernandez-Perez, Adrian & Sosvilla-Rivero, Simón, 2020. "Distant or close cousins: Connectedness between cryptocurrencies and traditional currencies volatilities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    4. Yahya, Muhammad & Oglend, Atle & Dahl, Roy Endré, 2019. "Temporal and spectral dependence between crude oil and agricultural commodities: A wavelet-based copula approach," Energy Economics, Elsevier, vol. 80(C), pages 277-296.
    5. Morten O. Ravn & Zacharias Psaradakis & Martin Sola, 2005. "Markov switching causality and the money-output relationship," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(5), pages 665-683.
    6. Xunfa Lu & Zhitao Ye & Kin Keung Lai & Hairong Cui & Xiao Lin, 2022. "Time-Varying Causalities in Prices and Volatilities between the Cross-Listed Stocks in Chinese Mainland and Hong Kong Stock Markets," Mathematics, MDPI, vol. 10(4), pages 1-19, February.
    7. Avik Sinha & Arshian Sharif & Arnab Adhikari & Ankit Sharma, 2022. "Dependence structure between Indian financial market and energy commodities: a cross-quantilogram based evidence," Annals of Operations Research, Springer, vol. 313(1), pages 257-287, June.
    8. Szczygielski, Jan Jakub & Charteris, Ailie & Obojska, Lidia, 2023. "Do commodity markets catch a cold from stock markets? Modelling uncertainty spillovers using Google search trends and wavelet coherence," International Review of Financial Analysis, Elsevier, vol. 87(C).
    9. Khalfaoui, Rabeh & Tiwari, Aviral Kumar & Kablan, Sandrine & Hammoudeh, Shawkat, 2021. "Interdependence and lead-lag relationships between the oil price and metal markets: Fresh insights from the wavelet and quantile coherency approaches," Energy Economics, Elsevier, vol. 101(C).
    10. Younis, Ijaz & Shah, Waheed Ullah & Yousaf, Imran, 2023. "Static and dynamic linkages between oil, gold and global equity markets in various crisis episodes: Evidence from the Wavelet TVP-VAR," Resources Policy, Elsevier, vol. 80(C).
    11. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    12. Gandal, Neil & Hamrick, JT & Moore, Tyler & Oberman, Tali, 2018. "Price manipulation in the Bitcoin ecosystem," Journal of Monetary Economics, Elsevier, vol. 95(C), pages 86-96.
    13. Lu, Xunfa & Huang, Nan & Mo, Jianlei, 2024. "Time-varying causalities from the COVID-19 media coverage to the dynamic spillovers among the cryptocurrency, the clean energy, and the crude oil," Energy Economics, Elsevier, vol. 132(C).
    14. Madaleno, Mara & Dogan, Eyup & Taskin, Dilvin, 2022. "A step forward on sustainability: The nexus of environmental responsibility, green technology, clean energy and green finance," Energy Economics, Elsevier, vol. 109(C).
    15. Robert G. Chambers & Richard E. Just, 1981. "Effects of Exchange Rate Changes on U.S. Agriculture: A Dynamic Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 63(1), pages 32-46.
    16. Hsu, Shu-Han & Sheu, Chwen & Yoon, Jiho, 2021. "Risk spillovers between cryptocurrencies and traditional currencies and gold under different global economic conditions," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    17. Umar, Zaghum & Gubareva, Mariya & Teplova, Tamara & Tran, Dang K., 2022. "Covid-19 impact on NFTs and major asset classes interrelations: Insights from the wavelet coherence analysis," Finance Research Letters, Elsevier, vol. 47(PB).
    18. Vincent Fromentin & Turki Alshammari, 2022. "Time-varying causality between stock prices and macroeconomic fundamentals: Connection or disconnection?," Post-Print hal-03721792, HAL.
    19. Mokni, Khaled & Ajmi, Ahdi Noomen, 2021. "Cryptocurrencies vs. US dollar: Evidence from causality in quantiles analysis," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 238-252.
    20. Liu, Heping & Shi, Jing, 2013. "Applying ARMA–GARCH approaches to forecasting short-term electricity prices," Energy Economics, Elsevier, vol. 37(C), pages 152-166.
    21. Jiang, Zhuhua & Yoon, Seong-Min, 2020. "Dynamic co-movement between oil and stock markets in oil-importing and oil-exporting countries: Two types of wavelet analysis," Energy Economics, Elsevier, vol. 90(C).
    22. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    23. Shuping Shi & Peter C. B. Phillips & Stan Hurn, 2018. "Change Detection and the Causal Impact of the Yield Curve," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 966-987, November.
    24. Urom, Christian & Ndubuisi, Gideon & Guesmi, Khaled, 2022. "How do financial and commodity markets volatility react to real economic activity?," Finance Research Letters, Elsevier, vol. 47(PB).
    25. Dai, Xingyu & Wang, Qunwei & Zha, Donglan & Zhou, Dequn, 2020. "Multi-scale dependence structure and risk contagion between oil, gold, and US exchange rate: A wavelet-based vine-copula approach," Energy Economics, Elsevier, vol. 88(C).
    26. Qiao, Xingzhi & Zhu, Huiming & Zhang, Zhongqingyang & Mao, Weifang, 2022. "Time-frequency transmission mechanism of EPU, investor sentiment and financial assets: A multiscale TVP-VAR connectedness analysis," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    27. Vincent Fromentin, 2022. "Time-varying causality between stock prices and macroeconomic fundamentals: Connection or disconnection?," Post-Print hal-04206765, HAL.
    28. Bhuvaneskumar Annamalaisamy & Sivakumar Vepur Jayaraman, 2024. "Do cryptocurrencies integrate with the indices of equity, sustainability, clean energy, and crude oil? A wavelet coherency approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 3372-3392, July.
    29. Walid Mensi & Mobeen Ur Rehman & Muhammad Shafiullah & Khamis Hamed Al-Yahyaee & Ahmet Sensoy, 2021. "High frequency multiscale relationships among major cryptocurrencies: portfolio management implications," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-21, December.
    30. Luís Aguiar-Conraria & Maria Joana Soares, 2014. "The Continuous Wavelet Transform: Moving Beyond Uni- And Bivariate Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 344-375, April.
    31. Li, Yue & W. Goodell, John & Shen, Dehua, 2021. "Does happiness forecast implied volatility? Evidence from nonparametric wave-based Granger causality testing," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 113-122.
    32. Rabeh Khalfaoui & Sakiru Adebola Solarin & Adel Al-Qadasi & Sami Ben Jabeur, 2022. "Dynamic causality interplay from COVID-19 pandemic to oil price, stock market, and economic policy uncertainty: evidence from oil-importing and oil-exporting countries," Annals of Operations Research, Springer, vol. 313(1), pages 105-143, June.
    33. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Larkin, Charles & Lucey, Brian & Oxley, Les, 2022. "Cryptocurrency liquidity and volatility interrelationships during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 45(C).
    34. Trimborn, Simon & Härdle, Wolfgang Karl, 2018. "CRIX an Index for cryptocurrencies," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 107-122.
    35. Fromentin, Vincent, 2022. "Time-varying causality between stock prices and macroeconomic fundamentals: Connection or disconnection?," Finance Research Letters, Elsevier, vol. 49(C).
    36. Foued Hamouda & Imran Yousaf & Muhammad Abubakr Naeem, 2024. "Exploring the Dynamics of Equity and Cryptocurrency Markets: Fresh Evidence from the Russia–Ukraine War," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3555-3576, December.
    37. Ender Demir & Mehmet Huseyin Bilgin & Gokhan Karabulut & Asli Cansin Doker, 2020. "The relationship between cryptocurrencies and COVID-19 pandemic," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 10(3), pages 349-360, September.
    38. Lu, Xunfa & He, Pengchao & Zhang, Zhengjun & Apergis, Nicholas, 2024. "Extreme co-movements between CO2 emission allowances and commodity markets and their response to economic policy uncertainty," Energy Economics, Elsevier, vol. 138(C).
    39. Fahad Mostafa & Pritam Saha & Mohammad Rafiqul Islam & Nguyet Nguyen, 2021. "GJR-GARCH Volatility Modeling under NIG and ANN for Predicting Top Cryptocurrencies," JRFM, MDPI, vol. 14(9), pages 1-22, September.
    40. Rubaiyat Ahsan Bhuiyan & Afzol Husain & Changyong Zhang, 2023. "Diversification evidence of bitcoin and gold from wavelet analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-36, December.
    41. Umar, Zaghum & Gubareva, Mariya, 2020. "A time–frequency analysis of the impact of the Covid-19 induced panic on the volatility of currency and cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    42. Xi, Yue & Huynh, Anh Ngoc Quang & Jiang, Yushi & Hong, Yanran, 2023. "Energy transition concern: Time-varying effect of climate policy uncertainty on renewables consumption," Technological Forecasting and Social Change, Elsevier, vol. 192(C).
    43. Peter C. B. Phillips & Shuping Shi & Jun Yu, 2015. "Testing For Multiple Bubbles: Limit Theory Of Real‐Time Detectors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(4), pages 1079-1134, November.
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