Quantum computational quantitative trading: high-frequency statistical arbitrage algorithm
AI Breakdown
Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.
Abstract
Quantitative trading is an integral part of financial markets with high calculation speed requirements, while no quantum algorithms have been introduced into this field yet. We propose quantum algorithms for high-frequency statistical arbitrage trading by utilizing variable time condition number estimation and quantum linear regression. The algorithm complexity has been reduced from the classical benchmark O(N 2 d) to O(dNκ02log(1/ϵ)2) , where N is the length of trading data, and d is the number of stocks, κ 0 is the condition number and ϵ is the desired precision. Moreover, two tool algorithms for condition number estimation and cointegration test are developed.