Multi-horizon forecast models using statistical analysis have been around for years now, channeling market variables into predictions about how a stock will move over different time periods. The machine-learning techniques introduced in this research will increase the amount of data that can be processed and the potential accuracy of the predictions over longer time periods.
But to make it work, the AI has to be able to process a huge amount of data quickly. The researchers turned to Bristol, England-based Graphcore’s Intelligence Processing Unit, a pizza box-sized chip
designed specifically to handle the demands of an AI program. In the trials, Graphcore’s chip performed about 10-times faster than GPUs.
While the research and the Graphcore chips that make the model possible are the “logical next step” in the high-speed computations that Man Group is interested in, the fund hasn’t committed to rolling it out, Ledford said.
Meanwhile, not every firm would be able to deploy this kind of strategy. “You would not try this model if you did not have access to fast computation,” said Zohren, who worked with Oxford-Man Institute research associate Zihao Zhang on the research.
Traders built some of the fastest telecommunications equipment anywhere, to get prices quickly between New York and Chicago. They pioneered colocation and the transition of exchanges into data centres. It is inevitable they will invest heavily in super computers if they believe they can gain an edge in short-term trading.Click HERE to subscribe to Fuller Treacy Money Back to top