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Futures Trend Strategy Model Based on Recurrent Neural Network
Applied Economics and Finance
View Archive Info| Field | Value | |
| Title |
Futures Trend Strategy Model Based on Recurrent Neural Network
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| Creator |
Zhang, Ru
Huang, Chenyu Chen, Shaozhen |
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| Description |
In recent years, quantitative investment has been widely used in the global futures market, and its steady investment performance has also been recognized by domestic futures investors. This paper takes the CSI-300 stock index futures as the research object and constructs a futures trend strategy model based on recurrent neural network. Furthermore, this paper back tests the strategy at different periods, different transaction costs and different parameters. The results show that the strategy model has strong profitability and robustness.
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| Publisher |
Redfame Publishing
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| Contributor |
—
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| Date |
2018-06-19
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| Type |
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion Peer-reviewed Article |
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| Format |
application/pdf
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| Identifier |
http://redfame.com/journal/index.php/aef/article/view/3306
10.11114/aef.v5i4.3306 |
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| Source |
Applied Economics and Finance; Vol 5, No 4 (2018); 95-101
2332-7308 2332-7294 |
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| Language |
eng
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| Relation |
http://redfame.com/journal/index.php/aef/article/view/3306/3538
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| Rights |
Copyright (c) 2018 Applied Economics and Finance
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