Investment Process in China's Mutual Funds and Application of Artificial Intelligence
This paper explored the process of investment management in both theory and practice in China's mutual fund industry and reviewed the applications of artificial intelligence including Rule-based Expert Systems, Genetic Algorithms, Artificial Neural Network, and Support Vector Machines in financ...
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| Format: | Dissertation (University of Nottingham only) |
| Language: | English |
| Published: |
2008
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| Online Access: | https://eprints.nottingham.ac.uk/22200/ |
| _version_ | 1848792373460467712 |
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| author | Xie, Ningjia |
| author_facet | Xie, Ningjia |
| author_sort | Xie, Ningjia |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | This paper explored the process of investment management in both theory and practice in China's mutual fund industry and reviewed the applications of artificial intelligence including Rule-based Expert Systems, Genetic Algorithms, Artificial Neural Network, and Support Vector Machines in financial forecasting, asset allocation and stocks selection.
This study proposed the use of artificial neural network for stock selection which classifies stocks into undervalued stocks (+1), neutral stocks (0) and overvalued stocks(-1) in China's market. The neural network used in this study is a multiple-layer feedforward neural network which uses a Levenberg-Marquardt accelerated training algorithm. There were three groups of input variables in this study. One unprecedented input was proposed in this study name analysts recommendations.
This study found that the traditionally managed equity fund average performance did not beat the market. It is also conclude that the artificial neural network in stock selection can be used to improve the current investment management process. This study also found that the use of analysts recommendations as input variable to the neural network was proved as ineffective to improve the stock selection performance; and, a misclassification problem due to too many input variables. |
| first_indexed | 2025-11-14T18:43:22Z |
| format | Dissertation (University of Nottingham only) |
| id | nottingham-22200 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T18:43:22Z |
| publishDate | 2008 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-222002017-12-28T11:09:51Z https://eprints.nottingham.ac.uk/22200/ Investment Process in China's Mutual Funds and Application of Artificial Intelligence Xie, Ningjia This paper explored the process of investment management in both theory and practice in China's mutual fund industry and reviewed the applications of artificial intelligence including Rule-based Expert Systems, Genetic Algorithms, Artificial Neural Network, and Support Vector Machines in financial forecasting, asset allocation and stocks selection. This study proposed the use of artificial neural network for stock selection which classifies stocks into undervalued stocks (+1), neutral stocks (0) and overvalued stocks(-1) in China's market. The neural network used in this study is a multiple-layer feedforward neural network which uses a Levenberg-Marquardt accelerated training algorithm. There were three groups of input variables in this study. One unprecedented input was proposed in this study name analysts recommendations. This study found that the traditionally managed equity fund average performance did not beat the market. It is also conclude that the artificial neural network in stock selection can be used to improve the current investment management process. This study also found that the use of analysts recommendations as input variable to the neural network was proved as ineffective to improve the stock selection performance; and, a misclassification problem due to too many input variables. 2008 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/22200/1/08MSclixnx1.pdf Xie, Ningjia (2008) Investment Process in China's Mutual Funds and Application of Artificial Intelligence. [Dissertation (University of Nottingham only)] (Unpublished) Artificial Intelligence Artificial Neural Network Investment Process Stock Selection |
| spellingShingle | Artificial Intelligence Artificial Neural Network Investment Process Stock Selection Xie, Ningjia Investment Process in China's Mutual Funds and Application of Artificial Intelligence |
| title | Investment Process in China's Mutual Funds and Application of Artificial Intelligence |
| title_full | Investment Process in China's Mutual Funds and Application of Artificial Intelligence |
| title_fullStr | Investment Process in China's Mutual Funds and Application of Artificial Intelligence |
| title_full_unstemmed | Investment Process in China's Mutual Funds and Application of Artificial Intelligence |
| title_short | Investment Process in China's Mutual Funds and Application of Artificial Intelligence |
| title_sort | investment process in china's mutual funds and application of artificial intelligence |
| topic | Artificial Intelligence Artificial Neural Network Investment Process Stock Selection |
| url | https://eprints.nottingham.ac.uk/22200/ |