Real-Time Trading System Based on Selections of Potentially Profitable, Uncorrelated, and Balanced Stocks by NP-Hard Combinatorial Optimization
- Resource Type
- article
- Authors
- Kosuke Tatsumura; Ryo Hidaka; Jun Nakayama; Tomoya Kashimata; Masaya Yamasaki
- Source
- IEEE Access, Vol 11, Pp 120023-120033 (2023)
- Subject
- Portfolio construction
trading system
real-time system
custom circuit
FPGA
combinatorial optimization
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
- Language
- English
- ISSN
- 2169-3536
Financial portfolio construction problems are often formulated as quadratic and discrete (combinatorial) optimization that belong to the nondeterministic polynomial time (NP)-hard class in computational complexity theory. Ising machines are hardware devices that work in quantum-mechanical/quantum-inspired principles for quickly solving NP-hard optimization problems, which potentially enable making trading decisions based on NP-hard optimization in the time constraints for high-speed trading strategies. Here we report a real-time stock trading system that determines long(buying)/short(selling) positions through NP-hard portfolio optimization for improving the Sharpe ratio using an embedded Ising machine based on a quantum-inspired algorithm called simulated bifurcation. The Ising machine selects a balanced (delta-neutral) group of stocks from an $N$ -stock universe according to an objective function involving maximizing instantaneous expected returns defined as deviations from volume-weighted average prices and minimizing the summation of statistical correlation factors (for diversification). It has been demonstrated in the Tokyo Stock Exchange that the trading strategy based on NP-hard portfolio optimization for $N=128$ is executable with the FPGA (field-programmable gate array)-based trading system with a response latency of $164 \mu \text{s}$ .