Pairs-trading System using Quantum-inspired Combinatorial Optimization Accelerator for Optimal Path Search in Market Graphs

TL;DR

This paper introduces a quantum-inspired combinatorial optimization accelerator for pairs-trading that efficiently finds multiple trading opportunities in large stock universes using an FPGA-based system with low latency.

Contribution

The paper presents a novel FPGA-based accelerator utilizing simulated bifurcation for optimal path search in market graphs, enhancing pairs-trading strategies with high-speed processing.

Findings

Successfully demonstrated in Tokyo Stock Exchange

Achieves low latency of 33 microseconds for 15 stocks

Enables real-time detection of multiple trading opportunities

Abstract

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.