摘要
近年来,证券市场的剧烈波动给监管层和投资者都带来了极大挑战。本文从订单执行角度阐述了算法交易对减缓证券市场大幅波动的影响,并针对投资者所提交订单经常出现无法成交的情况,引入一个成交概率指标,构建考虑机会成本的算法交易模型,得到投资者的最优算法交易策略。进一步,利用数值示例对此算法交易模型进行进一步阐述,并利用参数敏感性方法分析了成交概率、风险厌恶程度、以及市场冲击等因素对投资者算法交易策略的影响。研究发现,在保持风险厌恶程度、市场冲击等因素不变的情况下,如果成交概率越大,那么在交易初期投资者所提交订单规模也越大;如果投资者风险厌恶程度越大,那么在交易初期的订单规模越大;市场冲击程度越小,投资者在交易初期的订单规模越大。研究结论表明,在面对新常态下国内证券市场所出现的新情况,本文所提出的算法交易策略可以有效减缓证券市场的大幅波动,同时还可以为投资者节省交易费用,提高投资收益。
In the securities market, the investor may not trade the orders according to the expected target. This paper introduces the vari- able of turnover probability, develops a method to estimate the opportunity cost of a trading strategy if the blocks are not completely exe- cuted, 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 proba- bility. 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.
作者
燕汝贞
李冉
高伟
吴栩
Yan Ruzhen;Li Ran;Gao Wei;Wu Xu(School of Business,Chengdu University of Technology,Chengdu 610059;School of Business,Sichuan Agricultural University,Chengdu 611830)
出处
《管理评论》
CSSCI
北大核心
2018年第7期45-51,共7页
Management Review
基金
国家自然科学基金青年基金项目(71501018)
国家自然科学基金项目(71771032)
教育部人文社会科学研究青年基金项目(17YJC790168)
四川省软科学项目(2017ZR0204
2017ZR0205)
成都理工大学哲学社会科学研究基金(YJ2017-NS007
YJ2017-NS010)
成都理工大学中青年骨干教师培养计划(KYGG201713
KYGG201714)
关键词
市场冲击
交易成本
算法交易
量化投资
market impact
transaction costs
algorithmic trading
quantitative trading
