Quantum computational quantitative trading: high-frequency statistical arbitrage algorithm

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 for high-frequency statistical arbitrage in work by utilizing variable time condition number estimation and linear regression.The algorithm complexity has reduced from the classical benchmark O(N^2d) to O(sqrt(d)(kappa)^2(log(1/epsilon))^2 )). It shows advantage, where N length data, d stocks, kappa epsilon desired precision. Moreover, two tool cointegration test are developed.