Research on Fuzzy Portfolio Selection method based on Hierarchical Boltzmann Machine

基于层次玻尔兹曼机的模糊投资组合选择方法研究

• 批准号: 11680459
• 负责人: WATADA Junzo
• 金额: $ 2.24万
• 依托单位: Osaka Institute of Technology
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 1999
• 资助国家: 日本
• 起止时间: 1999 至 2002
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-11680459/
• 关键词: Hierarchical Boltzmann machine; Meta-controlled Boltzmann machine; Fuzzy portfolio selection problem; Selection a limited number of stocks; Mean-variance analysis; Fuzzy quadratic programming; ファジィ数理計画法; ボルツマンマシーン; メタ制御; ポートフォリオ選択; リバランス; プロジェク

The research on methods of investment of stocks starts from portfolio selection model proposed by H. Markowits. But it is difficult to realize sufficiently efficient selection of a certain number of stocks out of all stocks in the market. The objective of this research is to build the improved model using the neural network which we have been studied for years.The research results obtained in this granted research can be summarized as follows:1) We successed to organically drive a neural network by connecting between a Boltzmann machine and a Hopfield machine. This result was presented at international Journals and international conferences.2) In order to solve a portfolio selection problem under the consideration of the previous investing pattern, we developed the method to employ the hierarchical neural network in solving. The meta-controlled layer consisting of a Hopfield network is built in to select the appropriate number of stocks and the lower layer of a Boltzmann machine is emp … More loyed to effectively minimize the difference between the present investment pattern and the previous investment pattern. This model successfully obtained the solution. This result was presented at international conferences.3) It enables us to forecast the price of a stock at the next term using Fuzzy Chaotic Short-Term Forecasting Model which the head investigator have studied. The portfolio of stocks can be solved using the forecasted price under the consideration of dealing unit at the market. This result was presented at international conferences.4) It enables us to solve the portfolio selection problem considering a dealing unit by combining between the chaotic method and the meta-controlled Boltzmann machine. This result was presented at international conferences.5) The above-mentioned methods are applied to solve agricultural to management, production management and project management as well as to portfolio selection problems. This result was presented at international Journals and international conferences. Less

对股票投资方法的研究始于马科维茨提出的投资组合模型。但要实现从市场上的所有股票中充分有效地选择一定数量的股票是很困难的。本研究的目的是利用我们研究多年的神经网络来建立改进的模型。在这项授权研究中取得的研究成果可以概括如下：1)通过连接Boltzmann机器和Hopfield机器，成功地实现了神经网络的有机驱动。这一结果发表在国际期刊和国际会议上。2)为了解决在考虑以往投资模式的情况下的投资组合选择问题，我们提出了一种利用递阶神经网络进行求解的方法。元控制层由Hopfield网络组成，用于选择合适的库存数量，而Boltzmann机的下层是emp…更希望有效地缩小当前投资模式与以往投资模式之间的差异。该模型成功地得到了该模型的解。这一结果发表在国际会议上。3)它使我们能够使用首席研究员研究的模糊混沌短期预测模型来预测下一个时期的股票价格。在考虑市场上交易单位的情况下，可以用预测价格来求解股票组合。4)将混沌方法与元控制的Boltzmann机器相结合，解决了考虑交易单元的投资组合选择问题。5)将上述方法应用于农业转产管理、生产管理、项目管理以及投资组合的选择问题。这一结果发表在国际期刊和国际会议上。较少

项目成果

T.Watanabe, J.Watada: "Portfolio Selection Problem with Minimum Fluctuations of Portfolio Pattern"The 4^<th> Asian Fuzzy Systems Symposium(AFSS2000). Vol.2. 1021-1026 (2000)

T.Watanabe，J.Watada：“投资组合选择问题与投资组合模式的最小波动”第四届亚洲模糊系统研讨会（AFSS2000）。

Teruyuki Watanabe, Junzo Watada: "Formulation of Fuzzy Rebalance Model"Proceeding, 2th ISIS2001. (2001)

Teruyuki Watanabe、Junzo Watada：“模糊再平衡模型的制定”论文集，第 2 届 ISIS2001。

T. Kawaura & J. Watada: "Formulation of a Two-Layered Boltzmann Machine for Portfolio Selection"Proceedings, IEEE Int. Conference on Fuzzy Systems, Taipei, August 17-25, 1999. II. 1196-1201 (1999)

T·河浦

T.Kawaura, J.Watada: "Mean-Variance Analysis of Medical Investment and Medical Products"Journal of Biomedical Soft Computing and Human Science. Vol.5, No.2. 91-96 (2000)

T.Kawaura、J.Watada：“医疗投资和医疗产品的均值方差分析”生物医学软计算和人类科学杂志。

Y. Matsumoto & J. Watada: "Chaotic Short-term Forecasting based on Wavelet Transformation"Proceedings, Soft Computing and Intelligent Systems and 3rd Int. Symposium on Advanced Intelligent Systems, Tsukuba, Oct. 2002. (2002)

Y·松本