IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2301.00509.html
   My bibliography  Save this paper

Time-Varying Coefficient DAR Model and Stability Measures for Stablecoin Prices: An Application to Tether

Author

Listed:
  • Antoine Djobenou
  • Emre Inan
  • Joann Jasiak

Abstract

This paper examines the dynamics of Tether, the stablecoin with the largest market capitalization. We show that the distributional and dynamic properties of Tether/USD rates have been evolving from 2017 to 2021. We use local analysis methods to detect and describe the local patterns, such as short-lived trends, time-varying volatility and persistence. To accommodate these patterns, we consider a time varying parameter Double Autoregressive tvDAR(1) model under the assumption of local stationarity of Tether/USD rates. We estimate the tvDAR model non-parametrically and test hypotheses on the functional parameters. In the application to Tether, the model provides a good fit and reliable out-of-sample forecasts at short horizons, while being robust to time-varying persistence and volatility. In addition, the model yields a simple plug-in measure of stability for Tether and other stablecoins for assessing and comparing their stability.

Suggested Citation

  • Antoine Djobenou & Emre Inan & Joann Jasiak, 2023. "Time-Varying Coefficient DAR Model and Stability Measures for Stablecoin Prices: An Application to Tether," Papers 2301.00509, arXiv.org.
    • Handle: RePEc:arx:papers:2301.00509
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2301.00509
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Li, Qi, 1999. "Consistent model specification tests for time series econometric models," Journal of Econometrics, Elsevier, vol. 92(1), pages 101-147, September.
    2. Bullmann, Dirk & Klemm, Jonas & Pinna, Andrea, 2019. "In search for stability in crypto-assets: are stablecoins the solution?," Occasional Paper Series 230, European Central Bank.
    3. Gabe Chandler & Wolfgang Polonik, 2017. "Residual Empirical Processes and Weighted Sums for Time-Varying Processes with Applications to Testing for Homoscedasticity," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(1), pages 72-98, January.
    4. W. K. Li & T. K. Mak, 1994. "On The Squared Residual Autocorrelations In Non‐Linear Time Series With Conditional Heteroskedasticity," Journal of Time Series Analysis, Wiley Blackwell, vol. 15(6), pages 627-636, November.
    5. Chen, Meichen & Qin, Cong & Zhang, Xiaoyu, 2022. "Cryptocurrency price discrepancies under uncertainty: Evidence from COVID-19 and lockdown nexus," Journal of International Money and Finance, Elsevier, vol. 124(C).
    6. Wang, Gang-Jin & Ma, Xin-yu & Wu, Hao-yu, 2020. "Are stablecoins truly diversifiers, hedges, or safe havens against traditional cryptocurrencies as their name suggests?," Research in International Business and Finance, Elsevier, vol. 54(C).
    7. Tro Kortian, 1995. "Modern Approaches to Asset Price Formation: A Survey of Recent Theoretical Literature," RBA Research Discussion Papers rdp9501, Reserve Bank of Australia.
    8. Dong Li & Shaojun Guo & Ke Zhu, 2019. "Double AR model without intercept: An alternative to modeling nonstationarity and heteroscedasticity," Econometric Reviews, Taylor & Francis Journals, vol. 38(3), pages 319-331, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Juan Carlos Escanciano, 2006. "Joint Diagnostic Tests for Conditional Mean and Variance Specifications," Faculty Working Papers 02/06, School of Economics and Business Administration, University of Navarra.
    2. Lennart Ante & Ingo Fiedler & Jan Marius Willruth & Fred Steinmetz, 2023. "A Systematic Literature Review of Empirical Research on Stablecoins," FinTech, MDPI, vol. 2(1), pages 1-14, January.
    3. BRIK, Hatem & El OUAKDI, Jihene & FTITI, Zied, 2022. "Roles of stable versus nonstable cryptocurrencies in Bitcoin market dynamics," Research in International Business and Finance, Elsevier, vol. 62(C).
    4. Kliber, Agata, 2022. "Looking for a safe haven against American stocks during COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    5. Ladislav Kristoufek, 2022. "On the role of stablecoins in cryptoasset pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-26, December.
    6. Klaudia Jarno & Hanna Kołodziejczyk, 2021. "Does the Design of Stablecoins Impact Their Volatility?," JRFM, MDPI, vol. 14(2), pages 1-14, January.
    7. Bojaj, Martin M. & Muhadinovic, Milica & Bracanovic, Andrej & Mihailovic, Andrej & Radulovic, Mladen & Jolicic, Ivan & Milosevic, Igor & Milacic, Veselin, 2022. "Forecasting macroeconomic effects of stablecoin adoption: A Bayesian approach," Economic Modelling, Elsevier, vol. 109(C).
    8. Elena Vladimirovna Travkina & Alim Borisovich Fiapshev & Marianna Tolevna Belova, 2022. "Stablecoin-Based Digital Trading and Investment Platforms and Their Potential in Overcoming Sanctions Restrictions," Economies, MDPI, vol. 10(10), pages 1-10, October.
    9. Filip Hampl & Lucie Gyönyörová, 2021. "Can Fiat‐backed Stablecoins Be Considered Cash or Cash Equivalents Under International Financial Reporting Standards Rules?," Australian Accounting Review, CPA Australia, vol. 31(3), pages 233-255, September.
    10. Kołodziejczyk, Hanna, 2023. "Stablecoins as diversifiers, hedges and safe havens: A quantile coherency approach," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    11. Lyons, Richard K. & Viswanath-Natraj, Ganesh, 2023. "What keeps stablecoins stable?," Journal of International Money and Finance, Elsevier, vol. 131(C).
    12. Abate, Giorgio & Branzoli, Nicola & Gallo, Raffaele, 2023. "Crypto-Asset Markets: Structure, Market Developments in 2022 and Policy Considerations," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 76(3), pages 353-386.
    13. Force, ECB Crypto Assets Task, 2020. "Stablecoins: Implications for monetary policy, financial stability, market infrastructure and payments, and banking supervision in the euro area," Occasional Paper Series 247, European Central Bank.
    14. Patrick Saart & Jiti Gao & Nam Hyun Kim, 2014. "Semiparametric methods in nonlinear time series analysis: a selective review," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(1), pages 141-169, March.
    15. Duan, Kun & Zhao, Yanqi & Urquhart, Andrew & Huang, Yingying, 2023. "Do clean and dirty cryptocurrencies connect with financial assets differently? The role of economic policy uncertainty," Energy Economics, Elsevier, vol. 127(PA).
    16. Alexander Lipton & Aetienne Sardon & Fabian Schar & Christian Schupbach, 2020. "From Tether to Libra: Stablecoins, Digital Currency and the Future of Money," Papers 2005.12949, arXiv.org.
    17. Zacharias Psaradakis & Marián Vávra, 2019. "Portmanteau tests for linearity of stationary time series," Econometric Reviews, Taylor & Francis Journals, vol. 38(2), pages 248-262, February.
    18. Łęt, Blanka & Sobański, Konrad & Świder, Wojciech & Włosik, Katarzyna, 2023. "What drives the popularity of stablecoins? Measuring the frequency dynamics of connectedness between volatile and stable cryptocurrencies," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    19. Chen, Song Xi & Gao, Jiti & Tang, Chenghong, 2005. "A test for model specification of diffusion processes," MPRA Paper 11976, University Library of Munich, Germany, revised Feb 2007.
    20. repec:ebl:ecbull:v:3:y:2005:i:11:p:1-10 is not listed on IDEAS
    21. Jiang, Feiyu & Li, Dong & Zhu, Ke, 2020. "Non-standard inference for augmented double autoregressive models with null volatility coefficients," Journal of Econometrics, Elsevier, vol. 215(1), pages 165-183.

    More about this item

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2301.00509. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.