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Journal paper
Entry Year98
Journal levelSCI
Paper title (chapter)Resource Allocation Neural Network in Portfolio Selection
Name of journalExpert Systems With Applications
Date of publication2008-07-00
number of chapters35
Issue No.1-2
Name of author (Chinese)Ping-Chen Lin
Name of author (English)Ping-Chen Lin
NoteAbstract
Portfolio selection is a resource allocation problem in a finance market. The investor's asset optimization requires the distribution of a set of capital (resources) among a set of entities (assets) with the trade-off between risk and return. The ANN with nonlinear capability is proven to solve a large-scale complex problem effectively. It is suitable to solve NP-hard resource allocation problem. However, the traditional ANN model cannot guarantee the summation of produced investment weight always preserves 100% in output layer. This article introduces a resource allocation neural network model to optimize investment weight of portfolio. This model will dynamically adjust the investment weight as a basis of 100% of summing all of asset weights in the portfolio. The experimental results demonstrate the feasibility of optimal investment weights and superiority of ROI of buy-and-hold trading strategy compared with benchmark Taiwan Stock Exchange (TSE).
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