A Hybrid Intelligence Mechanism for Group Investment on Portfolio Recommendation
碩士 === 國立交通大學 === 資訊管理研究所 === 106 === More and more people want to invest financial products by themselves rather than saving in the banks. Recently, participating in an investment club becomes a good choice for investors. It is likely more profitable to follow with financial experts in investing cl...
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| Format: | Others |
| Language: | en_US |
| Published: |
2018
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| Online Access: | http://ndltd.ncl.edu.tw/handle/8x593n |
| Summary: | 碩士 === 國立交通大學 === 資訊管理研究所 === 106 === More and more people want to invest financial products by themselves rather than saving in the banks. Recently, participating in an investment club becomes a good choice for investors. It is likely more profitable to follow with financial experts in investing club as they can learn how to select stock and get greater positive ROI. But many of investment clubs have low return of rate from financial crisis in 2007-2008. In this study, we want to propose a recommendation mechanism that combine collective intelligence and a special type of recurrent neural network called LSTM to recommend portfolio to accord with investment club demand. According to club's risk tolerance and investment style, our system can recommend appropriate stock portfolio for investors in the club. Utilizing StockTwits and stock historical data, we verify that the proposed portfolio recommendation mechanism performs better than other benchmarks in market.
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