科研成果详情

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
ISBN9781728124858
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
DOI10.1109/SSCI44817.2019.9002781
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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
被引频次:2[WOS]   [WOS记录]     [WOS相关记录]
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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