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用图搜索与模拟分岔加速股票配对交易

文章 arXiv papers · 作者: Kosuke Tatsumura et al.
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总结

本文介绍一种股票配对交易系统，可在包含 N 只股票的范围内搜索，而非只监控预先选定的一对股票。系统将股票表示为有向图中的节点，并根据即时价格差异和统计相关因子设定边权重。采用量子启发式模拟分岔算法的组合优化加速器用于搜索潜在路径；禁忌搜索则有助于避免重复发现同一机会。

该系统使用基于 FPGA 的实现，在东京证券交易所进行了演示。对于包含 15 只股票的范围，报告的延迟为 33 微秒，对应 210 种可能的配对。这展示了一种低延迟机会搜索实现，但摘要未报告交易收益、交易成本、风险控制措施，也未与更简单的配对选择方法进行比较。因此，所称的执行速度证明的是计算能力和系统延迟，本身不能证明策略盈利能力。

核心观点

  • 该系统使用有向图，在股票范围内搜索配对交易机会。
  • 边权重结合即时价格差异与统计相关因子。
  • 模拟分岔算法加速图路径优化搜索。
  • 系统使用禁忌搜索，以减少重复发现机会。
  • 东京证券交易所演示报告称，延迟为 33 微秒，涉及 15 只股票，但未能证明其盈利能力。

标签

股票配对交易套利交易执行高频交易
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# 2307.05923


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









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 $μ$s for $N$=15 or 210 pairs) to execute the pairs-trading strategy based on optimal path search in market graphs.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。