一种面向高频交易的算法交易策略  

A new algorithmic trading strategy for high-frequency trading

作　　者：燕汝贞[1] 李平[1] 曾勇[1] 

机构地区：[1]电子科技大学经济与管理学院,成都610054

出　　处：《管理科学学报》2014年第3期88-96,共9页Journal of Management Sciences in China

基　　金：国家自然科学基金资助项目(71171034);中央高校基本科研业务费专项资金资助项目

摘　　要：在高频交易中,投资者为了减少交易成本、提高投资收益或减少损失,一般会将大额订单分拆为若干个中小规模订单,并根据不同市场环境择机逐次提交,但同时也会存在订单未全部成交以及证券价格变动所带来的风险.针对现有文献大都考虑订单全部执行以及未考虑时间风险因素的不足,在最小化总隐性交易成本的目标下,构建了具有最低成交量限制的最优交易策略模型,并针对风险中性且可预期未来成交量的投资者,给出了最优交易策略.研究结论表明,当投资者同时考虑市场冲击成本、机会成本、择时风险、价格冲击等4种不同隐性交易成本,不同交易时期的订单成交概率无论是单调增加、单调减少还是U型时,其最优交易策略的总隐性交易成本均小于常用的VWAP交易策略以及投资者同时考虑市场冲击成本和机会成本时的最优交易策略(MIOC),表明本文提出的最优交易策略可以为投资者有效节省交易成本.Over the past decade, financial markets have witnessed an explosion of algorithmic trading strategy which can help investors efficiently reduce transaction cost. In order to reduce the trading cost, investors usu- ally break block orders into small pieces in high-frequency trading. However, the behavior of such order split ting may result in inevitable opportunity cost as well as timing risk. This paper establishes a new algorithmic trading strategy to minimize implicit trading costs, including the market impact, opportunity cost, timing risk and the price appreciation. We find the performance of our optimal algorithmic trading that of MIOC or VWAP strategies in all the cases of increased, decreased and U-shaped strategy is better than execution probability. The new algorithmic trading strategy established in this paper can effectively reduce the trading cost.

关 键 词：高频交易 算法交易 隐性交易成本 择时风险 

分 类 号：F830.9[经济管理—金融学]