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Causal relationship among cryptocurrencies: A conditional quantile approach

Author

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  • Kim, Myeong Jun
  • Canh, Nguyen Phuc
  • Park, Sung Y.

Abstract

This study uses a Granger non-causality test in quantiles to extend the investigation of the causality among cryptocurrencies. The empirical results reveal that (i) no quantile uncorrelated cryptocurrency is found by the Granger non-causality test in quantiles. (ii) Statistically strong bi-directional causal relationships exist only between Ripple and other cryptocurrencies over the quantile level [0.05, 0.95]. (iii) There are strong causal relationships between cryptocurrencies’ returns over high quantile levels, such as, [0.6, 0.8] and [0.8, 0.95]. (iv) The largest cryptocurrencies, that is, Bitcoin (BTC) and Ethereum (ETH), have stronger causality to smaller ones in high quantiles. The results of the non-causality test suggest a significant causal relationship in the tail quantile, which makes it hard for investors to hedge the risk in the cryptocurrency market.

Suggested Citation

  • Kim, Myeong Jun & Canh, Nguyen Phuc & Park, Sung Y., 2021. "Causal relationship among cryptocurrencies: A conditional quantile approach," Finance Research Letters, Elsevier, vol. 42(C).
    • Handle: RePEc:eee:finlet:v:42:y:2021:i:c:s1544612320316937
    DOI: 10.1016/j.frl.2020.101879
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    as
    1. Toda, Hiro Y & Phillips, Peter C B, 1993. "Vector Autoregressions and Causality," Econometrica, Econometric Society, vol. 61(6), pages 1367-1393, November.
    2. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.
    3. Cheng, Hui-Pei & Yen, Kuang-Chieh, 2020. "The relationship between the economic policy uncertainty and the cryptocurrency market," Finance Research Letters, Elsevier, vol. 35(C).
    4. Nguyen, Linh Hoang & Chevapatrakul, Thanaset & Yao, Kai, 2020. "Investigating tail-risk dependence in the cryptocurrency markets: A LASSO quantile regression approach," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 333-355.
    5. Baumöhl, Eduard, 2019. "Are cryptocurrencies connected to forex? A quantile cross-spectral approach," Finance Research Letters, Elsevier, vol. 29(C), pages 363-372.
    6. Katsiampa, Paraskevi & Moutsianas, Konstantinos & Urquhart, Andrew, 2019. "Information demand and cryptocurrency market activity," Economics Letters, Elsevier, vol. 185(C).
    7. Chuang, Chia-Chang & Kuan, Chung-Ming & Lin, Hsin-Yi, 2009. "Causality in quantiles and dynamic stock return-volume relations," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1351-1360, July.
    8. Bouri, Elie & Hussain Shahzad, Syed Jawad & Roubaud, David, 2020. "Cryptocurrencies as hedges and safe-havens for US equity sectors," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 294-307.
    9. 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.
    10. Ballis, Antonis & Drakos, Konstantinos, 2020. "Testing for herding in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 33(C).
    11. Aslanidis, Nektarios & Bariviera, Aurelio F. & Martínez-Ibañez, Oscar, 2019. "An analysis of cryptocurrencies conditional cross correlations," Finance Research Letters, Elsevier, vol. 31(C), pages 130-137.
    12. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    13. Dyhrberg, Anne Haubo, 2016. "Bitcoin, gold and the dollar – A GARCH volatility analysis," Finance Research Letters, Elsevier, vol. 16(C), pages 85-92.
    14. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    15. Canh, Nguyen Phuc & Wongchoti, Udomsak & Thanh, Su Dinh & Thong, Nguyen Trung, 2019. "Systematic risk in cryptocurrency market: Evidence from DCC-MGARCH model," Finance Research Letters, Elsevier, vol. 29(C), pages 90-100.
    16. Kurka, Josef, 2019. "Do cryptocurrencies and traditional asset classes influence each other?," Finance Research Letters, Elsevier, vol. 31(C), pages 38-46.
    17. Baur, Dirk G. & Hong, KiHoon & Lee, Adrian D., 2018. "Bitcoin: Medium of exchange or speculative assets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 54(C), pages 177-189.
    18. Tu, Zhiyong & Xue, Changyong, 2019. "Effect of bifurcation on the interaction between Bitcoin and Litecoin," Finance Research Letters, Elsevier, vol. 31(C).
    19. Corbet, Shaen & Cumming, Douglas J. & Lucey, Brian M. & Peat, Maurice & Vigne, Samuel A., 2020. "The destabilising effects of cryptocurrency cybercriminality," Economics Letters, Elsevier, vol. 191(C).
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    3. Fang, Sheng & Cao, Guangxi & Egan, Paul, 2023. "Forecasting and backtesting systemic risk in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 54(C).

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    More about this item

    Keywords

    Cryptocurrency; Quantile regression; Quantile non-causality test; Robust non-causality;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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