摘要
考虑到股票市场的表现往往是非平稳的,过去较长时间的股票价格对当前的投资决策影响较小,因此基于近期股票价格数据设计在线投资组合策略.首先,将上一期的策略与固定长度的股票价格近期数据对应的最优定常再调整策略加权平均,设计了一个在线投资组合策略.其次,进一步采用在线学习的方法选择加权平均的权重,设计了一个适应性的在线投资组合策略.利用实际股票价格数据对构造的策略进行数值分析,结果表明与基准策略和已有的在线投资组合策略相比,设计的策略具有较好的性能.
Considering the behavior of the stock market is nonstationary and thus earlier observations are less relevant to the current investment decision-making,we design online portfolio strategies only based on recent stock price data.Firstly,we design an online portfolio strategy which is the weighted average of the previous portfolio and the best constant rebalanced portfolio corresponding to recent stock price data of fixed length.Secondly,we design an adaptive online portfolio strategy by choosing the weights via online learning.We present numerical analysis by using real stock data,and the results illustrate that our strategies perform well,compared with benchmark strategies and existing online portfolio strategies.
作者
杨兴雨
何锦安
赖明聪
YANG Xingyu;HE Jin’an;LAI Mingcong(School of Management,Guangdong University of Technology,Guangzhou 510520,China)
出处
《运筹学学报》
CSCD
北大核心
2018年第3期89-98,共10页
Operations Research Transactions
基金
国家自然科学基金(Nos.71301029
71501049)
教育部人文社会科学研究基金(No.18YJA630132)
关键词
在线投资组合
非平稳市场
适应性
敏感性分析
online portfolio
nonstationary market
adaptivity
sensitivity analysis
