  Pairs-trading is a trading strategy that involves matching a long position
with a short position in two stocks aiming at market-neutral profits. While a
typical pairs-trading system monitors the prices of two statistically
correlated stocks for detecting a temporary divergence, monitoring and
analyzing the prices of more stocks would potentially lead to finding more
trading opportunities. Here we report a stock pairs-trading system that finds
trading opportunities for any two stocks in an $N$-stock universe using a
combinatorial optimization accelerator based on a quantum-inspired algorithm
called simulated bifurcation. The trading opportunities are detected through
solving an optimal path search problem in an $N$-node directed graph with edge
weights corresponding to the products of instantaneous price differences and
statistical correlation factors between two stocks. The accelerator is one of
Ising machines and operates consecutively to find multiple opportunities in a
market situation with avoiding duplicate detections by a tabu search technique.
It has been demonstrated in the Tokyo Stock Exchange that the FPGA
(field-programmable gate array)-based trading system has a sufficiently low
latency (33 $\mu$s for $N$=15 or 210 pairs) to execute the pairs-trading
strategy based on optimal path search in market graphs.
