Hardware Accelerator for Engle-Granger Cointegration in Pairs Trading

Pairs trading is a classic strategy in the algorithmic trading area and has achieved great success in the stock market. It consists of two stages: pairs selection and trading based on the selected stock pairs. The process of pairs selection is the key to higher returns. Among existing pairs selection methods, pairs trading based on Engle-Granger cointegration has been proven to be superior. However, the cointegration approach is computationally expensive and brings high latency which may greatly affect the returns. In this paper, the Engle-Granger cointegration algorithm is drastically simplified. Meanwhile, a low latency hardware architecture is proposed for the modified algorithm. In the experiment of selecting stocks of length 5000, our hardware design is more than 1290× faster than CPU and 190× faster than GPU. To the best of our knowledge, this is the first work on hardware accelerator for Engle-Granger cointegration in open literature.