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Title: Double autoregressive time-varying coefficient model for stablecoin prices: An application to Tether Authors:  Emre Inan - York University (Canada) [presenting]
Antoine Djogbenou - York University (Canada)
Joann Jasiak - York University (Canada)
Abstract: The dynamics of the largest seven stablecoins are examined in terms of market capitalization as of July 2021, including Tether, USD Coin, Binance USD, Dai, Terra USD, True USD, and Pax Dollar. We show that the distributional and dynamic properties of Tether and other stablecoins have been evolving from 2017 to 2021. We use local analysis methods to detect and describe local explosive patterns, such as short-lived trends and bubbles, time-varying volatility, and persistence. We introduce a time-varying parameter Double Autoregressive DAR(1) model accommodating the local explosive patterns. We estimate the model non-parametrically and test hypotheses on the functional parameters. The application to Tether, the stablecoin with the largest market capitalization, provides a good fit and reliable inference while being robust to persistent price dynamics and time-varying volatility.