Real-time Trading System based on Selections of Potentially Profitable, Uncorrelated, and Balanced Stocks by NP-hard Combinatorial Optimization

ArXiv ID: 2307.06339 “View on arXiv”

Authors: Unknown

Abstract

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 $μ$s.

Keywords: Ising machine, Quantum-inspired algorithm, NP-hard portfolio optimization, Simulated bifurcation, FPGA, Stocks

Complexity vs Empirical Score

  • Math Complexity: 7.5/10
  • Empirical Rigor: 6.0/10
  • Quadrant: Holy Grail
  • Why: The paper employs advanced mathematical concepts such as NP-hard combinatorial optimization, quadratic unconstrained binary optimization (QUBO), and Ising models, demonstrating high mathematical density. Empirically, it is anchored by a real-time trading system tested on the Tokyo Stock Exchange with specific latency measurements (164 µs), but the excerpt lacks detailed backtesting metrics or comprehensive data analysis, suggesting moderate implementation depth.
  flowchart TD
    A["Research Goal: High-speed stock trading<br>via NP-hard optimization"] --> B["Key Methodology: Ising Machine<br>using Simulated Bifurcation"]
    B --> C["Data Inputs: 128 Tokyo Stock Exchange stocks"]
    C --> D["Computational Process:<br>NP-hard Portfolio Optimization<br>Max returns & Min correlation"]
    D --> E{"Outcome: FPGA Trading System<br>Response Latency: 164 μs"}
    E --> F["Result: Real-time Long/Short<br>Trading Execution"]