动量策略:编程语言性能的比较

Francesco Ceccon, Lovjit Thukral, Pedro Vergel Eleuterio
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引用次数: 2

摘要

由于市场参与者的增加,算法交易越来越受欢迎,现在需要更多的考虑来制定一个有利可图的交易策略。交易策略需要基于线性或非线性关系对参数进行优化,这会增加复杂性,从而增加计算运行时间。我们发现,C为量化交易策略的原型设计提供了最好的性能;然而,它的实现是最耗时的。在允许更快开发时间的语言中,Cython和Julia之间的差异相对较小,因此在它们之间的选择取决于用户偏好和其他因素。我们发现Julia是一门出色的编程语言,因为它的简单性和高性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Momentum Strategies: Comparison of Programming Language Performance
Given the increase in the popularity of algorithmic trading resulting from an increase in market participants, more considerations are now required to prototype a profitable trading strategy. Trading strategies, which require optimization of parameters based on linear or nonlinear relationships, cause an increase in complexity, which in turn increases computational run time. We find that C provides the best performance for prototyping quantitative trading strategies; however, it is the most time-consuming to implement. Among the languages that allow for faster development times, the difference between Cython and Julia is relatively small, so choice between them comes down to user preference and other factors. We find Julia to be the standout programming language due to its simplicity and high performance.
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