Stablecoins and Cryptoasset Returns

The increasing price and public awareness of cryptoassets has meant that they have become a popular choice for investors. Although much of the focus has been on their meteoric price appreciation, for example recently within Decentralised Finance (DeFi) tokens, another interesting aspect of them has been gaining promience in the background.

For the vast majority of exchanges, maintaining a typical banking relationship can be somewhat difficult. As a result, deposits in fiat currencies can often get stuck, and Bitcoin, Ethereum and other liquid cryptoassets are therefore used for trading due to their better compatibility. A solution to this issue has been the creation of the so-called stablecoins. These are cryptoassets that are pegged to the value of a fiat currency, thus acting as compatible proxies.

For cryptoasset investors, the key purpose of a stablecoin is to allow for conversion and trading cryptoassets on exchanges which do not accept fiat currencies, usually those that cannot establish stable banking relationships with traditional institutions. In this respect, the only obvious reason for an investor to hold a stablecoin is for transaction and exchange against cryptoassets.

The stabilisation role of stablecoins is an active area of discussion among academics and policy makers. Some prominent research show that stablecoins can be instrumental for market manipulation (e.g. Griffin and Shams, 2019). The legitimate role of stablecoins within the cryptoasset ecosystem can be fully understood by looking at the relationship between the market activity of stablecoins and the rest of the cryptoasset market.

A paper by Bianchi, Iacopini and Rossini titled “Stablecoins and Cryptocurrency Returns: Evidence from large Bayesian VARs” looks carefully this relationship. They do this through the lens of a complex large dimensional multi-variate time series model, i.e., a Vector Autoregressive (VAR) model, and they focus on the most prominent stablecoin to date, namely Tether (USDT).

The role of USDT is of particular interest as it has been previously linked with market manipulation. Unlike most cryptocurrencies, with Tether there is no protocol underlying the issuance of the coins and there is no open, diffuse network controlling the validity of transactions. This gives the private issuer control on both the size and the timing of the USDT emissions. Griffin and Shams (2019) show that such lack of legitimacy and transparency could lead to fraudulent behaviours such as market manipulation.

Launched in 2014 and originally built on top of the BTC blockchain, USDT now underpins the majority of cryptoasset trading around the world. Similar to a typical Eurodollar, USDT is a dollar-like liability – which is claimed to be backed by real dollar assets on a 1:1 parity basis – issued by a non-US entity outside the reach of regulations that usually govern dollar-issuing institutions. Practically no minimum reserve requirements, no access to lender of last resort and no registration applies. They are like dollars, but they are not dollars.

Bianchi et al. (2020) show that, contrary to the conventional wisdom, stablecoins are not as stable as their name suggests. USDT has a substantial daily volatility which highly correlates with BTC, most notably during the burst of the “Bitcoin bubble'' at the end of 2017. This result highlights that, although nominally pegged to the US dollar, the USDT still reacts significantly to extreme negative market events.

Perhaps more importantly, the authors show robust evidence that the lag daily return on USDT positively correlates with future returns across the vast majority of cryptocassets in their analysis – which is the top 28 cryptoassets by average market capitalization - controlling for past returns and the lagged de-trended average daily trading volume. This result suggests that the dynamics of USDT leads crypto market activity for a large fraction of major cryptoasset trading pairs. This result is worth discussing as it is novel to the academic literature.

The complete paper can be found here.


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