Doesn’t Tether have a clean slate? A study relieves the publishers of the alleged US dollar-covered stable coin of the accusation of Bitcoin market manipulation. Does the report manage to refute the allegations of manipulation?
The anonymous Bitcoin formula critic
The Stable Coin Tether has been confronted with allegations of manipulation of the Bitcoin formula course since the publication of an anonymously published Bitcoin formula report in January of this year. The report, entitled “Quantifying the Effect of Tether”, suspects that the stable coin was responsible for almost half of Bitcoin’s price gains in the period under review. The report concluded that new units were “printed” depending on the cryptographic market situation and that their growth was not the result of “organic” demand.
Doubts about the cover of the stable coin
The author also doubts that the stable coin is really 100 percent covered by US dollar deposits. Tether Limited, the publisher of the stable coin, insists on this – but has so far failed to provide any watertight evidence. A report published on 20 June by the law firm Freeh Sporkin & Sullivan confirmed on the basis of random checks that the stable coin was covered by US dollars. However, the expert opinion lacks credibility, as Sullivan is also part of the advisory board of one of the two (anonymous) tether banks.
Persistent suspicion of manipulation
In addition, the report highlights some unusual features in the relationship between the stable coin and Bitcoin. For example, 48.8 percent of Bitcoin’s share price growth in 2017 occurred within the first two hours after the release of new USDT tokens on the Bitfinex crypto exchange. In addition, the author described the deposit/payment movements at Bitfinex as “unusual” and in need of further investigation. The report from the beginning of the year also assumes a price slump of 30 to 80 percent if the manipulation rumours about the stable coin are confirmed.
Who had written the report for the private think tank “1000x Group” was not known. However, the group revealed that the author was an ex-Google employee specializing in machine learning and statistics.