The duo found that digital currencies don't behave like stocks or other currencies when it comes to price movements.
On August 6, Yale economist Yukun Liu[1] and PhD candidate Aleh Tsyvinski[2] published a working paper[3] titled Risks and Returns of Cryptocurrency. In it, they argue that there are several factors that predict price trends of some of the most popular digital currencies. The study is said[4] to be "the first-ever comprehensive economic analysis of cryptocurrency and the blockchain technology upon which it is based."
The researchers start with the claim that many factors that are predictive of the prices of stocks, currencies, and precious metals do not apply to cryptocurrencies, and so calculating the risk-return tradeoff requires different methods. They then go on to discuss factors specific to the cryptocurrency markets, focusing on two that they find to be predictive of digital currency price trends: the "time-series momentum effect," and the "investor attention effect."
Time-series Momentum Effect
The authors first focus on a factor called the "time-series momentum effect." This means that when asset or cryptocurrency prices are rising they tend to rise even higher. This method can be useful to predict the best time for investors to buy and sell their crypto. Tsyvunski described their findings to Yale News:
"We have designed a simple strategy that says an investor should buy Bitcoin if its value increases more than 20% in the previous week."
Although the time-series momentum effect can be useful, investors should know that it is not always the best method to use. The argument is essentially, "if the price goes up, it will continue to go up," which has some obvious flaws. For example, according to coinmarketcap.com[5]
