Fuzzy logic-based portfolio selection with particle filtering and anomaly detection
Fuzzy logic-based portfolio selection with particle filtering and anomaly detection
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DOI：
10.1016/j.knosys.2017.06.006
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发表时间：
2017-09-01
影响因子：
8.8
通讯作者：
Takahashi, Soichiro
中科院分区：
文献类型：
--
作者：
Nakano, Masafumi;Takahashi, Akihiko;Takahashi, Soichiro
本文提出了一种新的基于知识的系统(KBS)，该系统以模糊逻辑(FL)为特征，结合粒子滤波和异常检测，以创建高绩效的投资组合。特别是，我们的FL系统通过整合多边业绩衡量标准，从多个候选者中选择具有良好风险-回报概况的投资组合。候选者包括基于多个时间序列模型的各种投资组合，该模型由带有异常检测器的粒子过滤器估计。在一个国际金融资产数据集的样本外数值实验中，我们展示了我们的KBS成功地生成了一系列具有令人满意的投资记录的选定投资组合。(C)2017爱思唯尔B.V.保留所有权利。
This paper proposes a new knowledge-based system (KBS) featuring fuzzy logic (FL) with particle filtering and anomaly detection to create high-performance investment portfolios. In particular, our FL system selects a portfolio with fine risk-return profiles from a number of candidates by integrating multilateral performance measures. The candidates consist of various portfolios based on multiple time-series models estimated by a particle filter with anomaly detectors. In an out-of-sample numerical experiment with a dataset of international financial assets, we demonstrate our KBS successfully generates a series of selected portfolios with satisfactory investment records. (C) 2017 Elsevier B.V. All rights reserved.