The relationship between stablecoin supply and the price of Bitcoin is subject of much debate. A new study by BDC Consulting adds a new spin to the matter, showing that it can be possible to maximize the profits from BTC swing trading using data on USDT supply.
Back in 2019, a class suit claimed that Tether and Bitfinex together manipulated the crypto market by printing large amounts of USDT when the price of BTC was low. The idea was that institutions related to Bitfinex could inject USDT into the system to inflate the price – then convert Bitcoin back into USDT to boost the reserves.
A later study, published in 2020 by researchers at U.C. Berkeley and the Warwick Business School, didn’t find evidence of such manipulations. However, it doesn’t mean that there is no correlation between the supply of stablecoins and the prices: indeed, one can hypothesize that large market players mint fresh USDT when they prepare to buy crypto.
Finding the on-chain metrics most correlated with Bitcoin price
Can the supply of stablecoins and other kinds of on-chain data be used to improve one's trading and investment strategy? To find this out, the researchers at BDC Consulting ran 3 types of correlation tests (Pearson, Kendall, and Spearman) on almost 20 on-chain indicators to see which of them showed a clear correlation with the daily closing price of Bitcoin.
In the heatmap below, the indicators with the strongest correlation are marked in green. These include the total and circulating USDT supply, as well as the USDT transfer volume (total and mean).
The analysts proceeded to run the Dicky-Fuller test on the time series for the supply of USDT and the BTC price. This test, widely used in statistics, shows if a time series is stationary, meaning that its statistical properties like mean and variance remain consistent regardless of seasonality and trends.
Determining the stationarity was important because it allowed the researchers to make sure that a model built based on the data would hold true for different points in time. In this case, the model of the correlation between the total USDT supply and the closing price of Bitcoin passed the Dicky-Fuller test with flying colors.
Once the analysts saw that the correlation was statistically significant and stationary, they proceeded to plot the potential market entry and exit point on the 2020-2022 BTC price chart based on the USDT supply data.
As the chart shows, the resulting entry points (in green) did indeed correspond to the very beginning of most major price spikes and reversals after a local or a mid-term downtrend. Conversely, the exit points generated by the model fit nicely with the local peaks followed by a bearish reversal.
Finally, the team calculated the mean return on investment and the Sharpe coefficient for the theoretical investor who bought and sold Bitcoin based on the model. The mean ROI turned out to be 229%, which is three times higher than the returns on the best-performing blockchain ETFs.
At the same time, the Sharpe coefficient value was 1.4577, which is considered good. Sharpe coefficient is used to adjust the returns on a portfolio by risk, where a higher value means better returns compared to investing in lower-risk assets. A ratio of above 1 is considered reasonably good, while anything above 2 is viewed as excellent. Thus, investing in Bitcoin based on the USDT supply correlation model yielded a good risk-return ratio.
An increase in the total supply of stablecoins indicates that large investors are ready to buy BTC, expecting a reversal – and, as the model shows, they are usually proven right. Individual investors and traders can use on-chain data on the supply of Tether to time their market entries and exits.
In particular, the researchers at BDC Consulting stress that modifying the exit strategy based on the model can make one’s risk management system more efficient , with a potential to reach an ROI above 200% in the long term.
*None of the information in this article should be construed as financial advice. The results are valid for the period between the end of 2020 and March 2022.