[1] |
刘逖 . 市场微观结构与交易机制设计高级指南[M]. 上海: 上海人民出版社, 2012 569-583.
|
|
LIU T . Market microstructure and trading mechanism advanced guideline[M]. Shanghai: Shanghai People’s PressPress, 2012: 569-583.
|
[2] |
ALDRIDGE I . High frequency trading[M]. New Jersey: John Wiley & Sons,Inc.Press, 2010: 7-35.
|
[3] |
SEYFERT R . Bugs,predations or manipulations? Incompatible epistemic regimes of high-frequency trading[J]. Economy and Society, 2016,45(2): 251-277.
|
[4] |
叶伟 . 我国资本市场程序化交易的风险控制策略[J]. 证券市场导报, 2014(8): 46-52.
|
|
YE W . The risk control strategies of program trading of Chinese capital market[J]. Securities Market Herald, 2014(8): 46-52.
|
[5] |
熊熊, 袁海亮, 张维 ,等. 程序化交易及其风险分析[J]. 电子科技大学学报(社科版), 2011,13(3): 32-39.
|
|
XIONG X , YUAN H L , ZHANG W ,et al. Program Trading overview and risk analysis[J]. Journal of University Electronics Science and Technology of China, 2011,13(3): 32-39.
|
[6] |
彭蕾 . 中国证券市场程序化交易研究[D]. 成都:西南财经大学, 2005: 4-17.
|
|
PENG L . The research on pr ogram trading of the Chinese securities market[D]. Chengdu:Southwest University of Finance and Economics Press, 2005: 4-17.
|
[7] |
陈梦根 . 算法交易的兴起及最新研究进展[J]. 证券市场导报, 2013(9): 11-17.
|
|
CHEN M G . Algorithmic trading's rising and advances[J]. Securities Market Herald , 2013(9): 11-17.
|
[8] |
蓝海平 . 高频交易的技术特征、发展趋势及挑战[J]. 证券市场导报, 2014(4): 59-64.
|
|
LAN H P . HFT:the technique feature,developments and challenges[J]. Securities Market Herald, 2014(4): 59-64.
|
[9] |
郭朋 . 国外高频交易的发展现状及启示[J]. 证券市场导报, 2012(7): 56-61.
|
|
GUO P . Development of high frequency trading and its implication[J]. Securities Market Herald, 2012(7): 56-61.
|
[10] |
YANG S Y , QIAO Q F , BELING P A ,et al. Gaussian process-based algorithmic trading strategy identification[J]. Quantitative Finance, 2015,15(10): 1683-1702.
|
[11] |
QIAO Q F , BELING P A . Decision analytics and machine learning in economic and financial systems[J]. Environment Systems and Decisions, 2016,36(2): 109-113.
|
[12] |
YANG S Y , QIAO Q F , BELING P A . Algorithmic trading behavior identification using reward learning method[C]// The 2014 International Joint Conference on Neural Networks,July 6-11,2014,Beijing,China. Red Hook:Curran Associates, 2014: 3807-3414.
|
[13] |
张鸿萍 . 基于时间序列交易数据的服装电商客户分类研究[J]. 现代管理, 2017,7(6): 481-492.
|
|
ZHANG H P . Research for customer classification of clothing E-business based on time series transaction data[J]. Modern Management, 2017,7(6): 481-492.
|
[14] |
毛瑞, 费宇 . 基于交易数据的客户分类研究[J]. 中国证券期货, 2012(1): 22-23.
|
|
MAO R , FEI Y . The study of customer classification based on trading data[J]. Securities & Futures of China, 2012(1): 22-23.
|
[15] |
WANG G , ZHANG X , TANG S ,et al. Clickstream user behavior models[J]. ACM Transactions on the Web, 2017,11(4): 1-37.
|
[16] |
BENSON A R , KUMAR R , TOMKINS A . Modeling user consumption sequences[C]// The 25th International Conference on World Wide Web.International World Wide Web Conferences,April 11-15,2016,Montréal,Canada. New York:ACM Press, 2016: 519-529.
|
[17] |
HINTON G E , OSINDERO S , TEH Y W . A fast learning algorithm for deep belief nets[J]. Neural Computation, 2006,18(7): 1527-1554.
|
[18] |
马世龙, 乌尼日其其格, 李小平 ,等. 大数据与深度学习综述[J]. 智能系统学报, 2016,11(6): 728-742.
|
|
MA S L , WUNIRI Q Q G , LI X P ,et al. Deep learning with big data:state of the art and development[J]. CAAI Transactions on Intelligent Systems, 2016,11(6): 728-742.
|
[19] |
SCHMIDHUBER J . Deep learning in neural networks:an overview[J]. Neural Networks, 2015,61(1): 85-117.
|
[20] |
SUTSKEVER I , VINYALS O , LE Q V . Sequence to sequence learning with neural networks[J]. Computer Science, 2014,arXiv:1409.3215.
|
[21] |
孙志远, 鲁成祥, 史忠植 ,等. 深度学习研究与进展[J]. 计算机科学, 2016,43(2): 1-8.
|
|
SUN Z Y , LU C X , SHI Z Z ,et al. Research and ad vances on deep learning[J]. Computer Science, 2016,43(2): 1-8.
|
[22] |
KARNOWSKI T P , AREL I , ROSE D C . Deep spatiotemporal feature learning with application to image classification[C]// The 9th International Conference on Machine Learning and Applications,December 12,2010,Washington,DC,USA. Piscataway:IEEE Computer Society, 2010: 883-888.
|