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Stability between cryptocurrency prices and the term structure

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  • Castle, Jennifer L.
  • Kurita, Takamitsu

Abstract

The rapid expansion of the global cryptocurrency market raises the question of whether there are stable relationships between the prices of representative cryptocurrencies and economic indicators capturing expectations of future monetary policy. Multivariate time-series analysis reveals a single but significant cointegrating relationship between cryptocurrencies and the US term spread. This evidence allows us to explore cointegration-based control analysis of the data, which results in direct policy implications for the implementation of monetary policy allowing for the growing influence of digital assets. Structural breaks due to Tesla terminating the use of Bitcoin for car sales and the US inflation shock in 2022 must be handled, maintaining the stability of the relationship between cryptocurrencies and the term spread.

Suggested Citation

  • Castle, Jennifer L. & Kurita, Takamitsu, 2024. "Stability between cryptocurrency prices and the term structure," Journal of Economic Dynamics and Control, Elsevier, vol. 165(C).
  • Handle: RePEc:eee:dyncon:v:165:y:2024:i:c:s0165188924000824
    DOI: 10.1016/j.jedc.2024.104890
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    1. Giese, Julia V., 2008. "Level, Slope, Curvature: Characterising the Yield Curve in a Cointegrated VAR Model," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 2, pages 1-20.
    2. Soren Johansen & Katarina Juselius, 2001. "Controlling Inflation in a Cointegrated Vector Autoregressive Model with an Application to US Data," Discussion Papers 01-03, University of Copenhagen. Department of Economics.
    3. Takamitsu Kurita & Bent Nielsen, 2019. "Partial Cointegrated Vector Autoregressive Models with Structural Breaks in Deterministic Terms," Econometrics, MDPI, vol. 7(4), pages 1-35, October.
    4. John Y. Campbell, 1995. "Some Lessons from the Yield Curve," Journal of Economic Perspectives, American Economic Association, vol. 9(3), pages 129-152, Summer.
    5. Estrella, Arturo & Mishkin, Frederic S., 1997. "The predictive power of the term structure of interest rates in Europe and the United States: Implications for the European Central Bank," European Economic Review, Elsevier, vol. 41(7), pages 1375-1401, July.
    6. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Felix Pretis, 2015. "Detecting Location Shifts during Model Selection by Step-Indicator Saturation," Econometrics, MDPI, vol. 3(2), pages 1-25, April.
    7. Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco & Vigne, Samuel A., 2018. "Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation," Finance Research Letters, Elsevier, vol. 26(C), pages 145-149.
    8. Angelo Corelli, 2018. "Cryptocurrencies and Exchange Rates: A Relationship and Causality Analysis," Risks, MDPI, vol. 6(4), pages 1-11, October.
    9. Harris, David & Leybourne, Stephen J. & Taylor, A.M. Robert, 2016. "Tests of the co-integration rank in VAR models in the presence of a possible break in trend at an unknown point," Journal of Econometrics, Elsevier, vol. 192(2), pages 451-467.
    10. Jurgen A. Doornik & David F. Hendry & Bent Nielsen, 1998. "Inference in Cointegrating Models: UK M1 Revisited," Journal of Economic Surveys, Wiley Blackwell, vol. 12(5), pages 533-572, December.
    11. repec:bla:jecsur:v:12:y:1998:i:5:p:533-72 is not listed on IDEAS
    12. Bergamelli, Michele & Bianchi, Annamaria & Khalaf, Lynda & Urga, Giovanni, 2019. "Combining p-values to test for multiple structural breaks in cointegrated regressions," Journal of Econometrics, Elsevier, vol. 211(2), pages 461-482.
    13. Søren Johansen & Rocco Mosconi & Bent Nielsen, 2000. "Cointegration analysis in the presence of structural breaks in the deterministic trend," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 216-249.
    14. Hansen, Peter Reinhard, 2003. "Structural changes in the cointegrated vector autoregressive model," Journal of Econometrics, Elsevier, vol. 114(2), pages 261-295, June.
    15. Choi, Sangyup & Shin, Junhyeok, 2022. "Bitcoin: An inflation hedge but not a safe haven," Finance Research Letters, Elsevier, vol. 46(PB).
    16. Taylor, John B. & Williams, John C., 2010. "Simple and Robust Rules for Monetary Policy," Handbook of Monetary Economics, in: Benjamin M. Friedman & Michael Woodford (ed.), Handbook of Monetary Economics, edition 1, volume 3, chapter 15, pages 829-859, Elsevier.
    17. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    18. Henrik Hansen & Søren Johansen, 1992. "Recursive Estimation in Cointegrated VAR-Models," Discussion Papers 92-13, University of Copenhagen. Department of Economics.
    19. Katsiampa, Paraskevi, 2017. "Volatility estimation for Bitcoin: A comparison of GARCH models," Economics Letters, Elsevier, vol. 158(C), pages 3-6.
    20. C. Alexander & M. Dakos, 2020. "A critical investigation of cryptocurrency data and analysis," Quantitative Finance, Taylor & Francis Journals, vol. 20(2), pages 173-188, February.
    21. Conlon, Thomas & Corbet, Shaen & McGee, Richard J., 2020. "Are cryptocurrencies a safe haven for equity markets? An international perspective from the COVID-19 pandemic," Research in International Business and Finance, Elsevier, vol. 54(C).
    22. Helmut Lütkepohl & Pentti Saikkonen & Carsten Trenkler, 2004. "Testing for the Cointegrating Rank of a VAR Process with Level Shift at Unknown Time," Econometrica, Econometric Society, vol. 72(2), pages 647-662, March.
    23. Cheung, Yin-Wong & Lai, Kon S, 1993. "Finite-Sample Sizes of Johansen's Likelihood Ration Tests for Conintegration," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 55(3), pages 313-328, August.
    24. Carlos Santos & David Hendry & Soren Johansen, 2008. "Automatic selection of indicators in a fully saturated regression," Computational Statistics, Springer, vol. 23(2), pages 317-335, April.
    25. Jeffrey Chu & Stephen Chan & Saralees Nadarajah & Joerg Osterrieder, 2017. "GARCH Modelling of Cryptocurrencies," JRFM, MDPI, vol. 10(4), pages 1-15, October.
    26. Grégory Claeys & Maria Demertzis & Konstantinos Efstathiou, 2018. "Cryptocurrencies and monetary policy," Policy Contributions 26557, Bruegel.
    27. Soren Johansen, 2002. "A Small Sample Correction for the Test of Cointegrating Rank in the Vector Autoregressive Model," Econometrica, Econometric Society, vol. 70(5), pages 1929-1961, September.
    28. Søren Johansen & Rocco Mosconi & Bent Nielsen, 2000. "Cointegration analysis in the presence of structural breaks in the deterministic trend," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 216-249.
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    2. Josué Thélissaint, 2024. "Assessing Cryptomarket Risks: Macroeconomic Forces, Market Shocks and Behavioural Dynamics," Economics Working Paper Archive (University of Rennes & University of Caen) 2024-14, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.

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    More about this item

    Keywords

    Cryptocurrencies; Cointegration; Weak exogeneity; Policy simulation; Structural breaks; Term structure;
    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
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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