BH-Quant智能量化策略辅助设计平台的研究与实践
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摘要
量化交易已在国外高频金融交易领域的广泛应用,但国内现有量化交易平台存在数据模型单一、策略有限、辅助功能少等不足,为解决上述问题,本文设计了一种智能的量化策略辅助设计平台,该平台引入了深度学习框架,利用人工智能技术训练模型和设计策略,并将预测结果通过可视化技术呈现,为投资者提供按自己的风险偏好选择投资组合提供辅助设计平台。
Quantitative trading has been widely applied in foreign high-frequency financial transactions,but there are several deficiencies in the existing domestic quantitative trading platform,such as the single variety of data models,limited strategies and insufficient auxiliary functions.In order to solve the above problems,this paper designs an intelligent quantization strategy aided design platform.The platform introduces a deep learning framework,adopts the technology of the artificial intelligence training model and the design strategy,and presents prediction results through visualization technology,which provides an aided design platform for investors to select portfolios based on their own risk preference.
Quantitative trading has been widely applied in foreign high-frequency financial transactions,but there are several deficiencies in the existing domestic quantitative trading platform,such as the single variety of data models,limited strategies and insufficient auxiliary functions.In order to solve the above problems,this paper designs an intelligent quantization strategy aided design platform.The platform introduces a deep learning framework,adopts the technology of the artificial intelligence training model and the design strategy,and presents prediction results through visualization technology,which provides an aided design platform for investors to select portfolios based on their own risk preference.
引文
[1]谢堞江.量化交易策略综述与新策略设计[D].浙江:浙江大学,2016.
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[2]Lawrence R.Rabiner.A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition[J].Proceedings of the IEEE,1989,77(2):257-286.
[3]Y.Kawahara,T.Yairi,K.Machida.Change-point detection in time-series data based on subspace identification[J].Seventh IEEE International Conference on,IEEE,2007:559-564.
[4]Hall L O.Exploring Big Data with Scalable Soft Clustering[J].Proc of the 6th International Conference on Soft Methods in Probability and Statistics.Konstanz,Germany,2012:11-15.
[5]Song M,et al.A Comparative Study of Dimensionality Reduction Techniques to Enhance Trace Clustering Performances[J].Expert Systems with Applications,2013,40(9):3722-3737.