计算机科学 ›› 2021, Vol. 48 ›› Issue (11A): 608-615.doi: 10.11896/jsjkx.201100068
戴宏亮, 梁楚欣
DAI Hong-liang, LIANG Chu-xin
摘要: 随着我国经济的迅速发展和国民可供分配收入的不断增加,人们投资需求变得更为强烈,如何高效合理地进行投资组合俨然成为投资者关注的热点问题。针对在线投资组合策略过于单一的价格预测和难以确定精准投资比例的问题,提出了基于价格趋势驱动的元学习算法在线投资组合策略(TPPT)。首先,考虑到股票价格异象的影响,提出了根据历史窗口期的等权重斜率值的三状态价格预测方法来追踪价格变化。其次,加入基于梯度投影的快速误差反向传播(BP)算法来求解投资比例。于是TPPT策略就将资产的增加能力反馈到投资比例上,以此来最大化累积财富。最后,5个典型数据的实证分析表明了TPPT策略在平衡风险与收益上占据较大的优势,是一种稳健且行之有效的在线投资组合策略。
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