题名 | Hybrid Chaotic Radial Basis Function Neural Oscillatory Network (HCRBFNON) for Financial Forecast and Trading System |
作者 | |
发表日期 | 2019-12-01 |
会议名称 | 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019 |
会议录名称 | 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019
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ISBN | 9781728124858 |
页码 | 2799-2806 |
会议日期 | December 6-9, 2019 |
会议地点 | Xiamen |
摘要 | Nowadays, financial prediction and trading are two major topics in financial engineering and the application of artificial intelligence. In this paper, we proposed a hybrid chaotic radial basis function neural oscillatory network (HCRBFNON) based foreign exchange (Forex) product price series prediction and quantum price levels based hedging trading system. In our forecasting system, the HCRBFNON consists of three components: 1) Quantum Finance Theory to model the secondary financial market and extract the financial dynamic energy level feature, 2) Long short-term memory mechanism to extract the temporal financial feature, 3) Chaotic type-2 transient-fuzzy membership function based transient chaotic radial basis layer to model the highly chaotic financial time series. In the quantum finance hedging trading system (QFHTS), we employ the forecasting prices from the HCRBFNON and the respective nearest quantum price levels to construct the trading timing capture. In the model evaluation, we measure the performance CRBFNON with 5 popular models used in financial time series prediction; we also compared the trading performance of QFHTS with 2 classical technical analysis-based trading strategies. By using 12 most popular forex product datasets from 2011 to 2019 for the system testing, the experimental results revealed that both the HCRBFNON and QFHTS achieve promising results in terms of forecast and trading performances respectively. |
关键词 | chaotic neural networks financial Investment financial prediction financial trading quantum finance |
DOI | 10.1109/SSCI44817.2019.9002781 |
URL | 查看来源 |
收录类别 | CPCI-S |
语种 | 英语English |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000555467202126 |
Scopus入藏号 | 2-s2.0-85080882537 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | https://repository.uic.edu.cn/handle/39GCC9TT/6220 |
专题 | 理工科技学院 |
通讯作者 | Lee, Raymond S.T. |
作者单位 | Beijing Normal University-Hong Kong Baptist,University United International College,Division of Computer Science and Technology,Zhuhai,China |
第一作者单位 | 北师香港浸会大学 |
通讯作者单位 | 北师香港浸会大学 |
推荐引用方式 GB/T 7714 | Qiu, Turing Y.F.,Yuan, Alex Y.C.,Chen, Peter Z.et al. Hybrid Chaotic Radial Basis Function Neural Oscillatory Network (HCRBFNON) for Financial Forecast and Trading System[C], 2019: 2799-2806. |
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