Management Review

›› 2018, Vol. 30 ›› Issue (7): 45-51.

Previous Articles     Next Articles

Study on the Securities Market Algorithmic Trading Strategy Based on the Opportunity Cost

Yan Ruzhen1, Li Ran1, Gao Wei2, Wu Xu1   

  1. 1. School of Business, Chengdu University of Technology, Chengdu 610059;
    2. School of Business, Sichuan Agricultural University, Chengdu 611830
  • Received:2017-07-29 Online:2018-07-28 Published:2018-07-21

PDF (PC)

703

Abstract:

In the securities market, the investor may not trade the orders according to the expected target. This paper introduces the variable of turnover probability, develops a method to estimate the opportunity cost of a trading strategy if the blocks are not completely executed, and studies an optimal trading strategy that the investor considers both market impact and opportunity cost. Using the optimization theory and methods, this paper gets the analytical solutions and the optimal algorithmic trading strategy. Furthermore, this paper makes numerical experiments for the optimal algorithmic trading strategy problem, and compares the strategy with the different turnover probability. The result shows that the order size in the first trading period is bigger than other strategies, compared with the small turnover probability. The order size in the first trading period is bigger than other strategies, compared with the less risk aversion, and the order size in the first trading period is bigger than other strategies, compared with the large market impact. The algorithmic trading strategy can effectively reduce the trading costs, and improve the investment return for the institutional investors.

Key words: market impact, transaction costs, algorithmic trading, quantitative trading