MIT scientists led by an Indian-origin researcher have developed a machine-learning algorithm that can predict the price of the notoriously volatile cryptocurrency Bitcoin.
Researchers at Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Laboratory and the Laboratory for Information and Decision Systems used the algorithm to nearly double their investment over a period of 50 days.
For the study, principal investigator Devavrat Shah and recent graduate Kang Zhang collected price data from all major Bitcoin exchanges earlier this year, every second for five months, accumulating more than 200 million data points.
Using a technique called "Bayesian regression," they trained an algorithm to automatically identify patterns from the data, which they used to predict prices, and trade accordingly.
Specifically, every two seconds they predicted the average price movement over the following 10 seconds. If the price movement was higher than a certain threshold, they bought a Bitcoin; if it was lower than the opposite threshold, they sold one; and if it was in-between, they did nothing.
Over 50 days, the team's 2,872 trades gave them an 89 per cent return on investment with a Sharpe ratio (measure of return relative to the amount of risk) of 4.1.
Shah said he was drawn to Bitcoin because of its vast swath of free data, as well as its sizable user base of high-frequency traders.
"We needed publicly available data, in large quantities and at an extremely fine scale," said Shah, who previously used the approach to predict Twitter trending topics.
"We were also intrigued by the challenge of predicting a currency that has seen its prices see-saw regularly in the last few years," Shah added.
Launched in 2009, Bitcoin is a form of cryptography-based e-money that offers a largely anonymous payment system and can can be stored either virtually or on a user's hard drive.
