[1] |
HOCHREITER S, SCHMIDHUBER J. Long short-term memory[J]. Neural Computation, 1997, 9(8): 1735-1780.
|
[2] |
GERS F A, SCHMIDHUBER J, CUMMINS F. Learning to forget: Continual prediction with LSTM[J]. Neural Computation, 2000, 12(10): 2451-2471.
|
[3] |
WEN T H, GASIC M, MRKSIC N, et al. Semantically conditioned LSTM-based natural language generation for spoken dialogue systems[C]// Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA: Association for Computational Linguistics, 2015: 1711-1721.
|
[4] |
DONAHUE J, HENDRICKS A L, GUADARRAMA S, et al. Long-term recurrent convolutional networks for visual recognition and description[C]// Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2015: 2625-2634.
|
[5] |
VENUGOPALAN S, XU H, DONAHUE J, et al. Translating videos to natural language using deep recurrent neural networks[J]. Human Language Technologies: The 2015 Annual Conference of the North American Chapter of the ACL. Stroudsburg, PA: Association for Computational Linguistics, 2015: 1494-1504.
|
[6] |
MAKNICKIEN N, MAKNICKAS A. Application of neural network for forecasting of exchange rates and forex trading[C]// The 7th International Scientific Conference “Business and Management 2012”. Vilnius, Lithuania: Vilnius Gediminas Technical University, 2012: 10-11.
|
[7] |
DI PERSIO L, HONCHAR O. Artificial neural networks architectures for stock price prediction: Comparisons and applications[J]. International Journal of Circuits, Systems and Signal Processing, 2016, 10: 403-413.
|
[8] |
SIMON D P. The soybean crush spread: Empirical evidence and trading strategies[J]. Journal of Futures Markets, 1999, 19(3): 271-289.
|
[9] |
仇中群, 程希骏. 基于协整的股指期货跨期套利策略模型[J]. 系统工程, 2008, 26(12): 26-29. QIU Zhongqun, CHENG Xijun. Calendar spread arbitrage strategy model for index futures based on co-integration rule[J]. Systems Engineering, 2008, 26(12):26-29.
|
[10] |
葛翔宇, 吴洋, 周艳丽. 门限协整套利: 理论与实证研究[J]. 统计研究, 2012,29(3): 79-87.GE Xiangyu, WU Yang, ZHOU Yanli. Threshold cointegration arbitrage: Theory and application[J]. Statistical Research, 2012, 29(3): 79-87.
|
[11] |
KANAMURA T, RACHEV S T, FABOZZI F J. A profit model for spread trading with an application to energy futures[J]. The Journal of Trading, 2010, 5(1): 48-62.
|
[12] |
DUNIS C L, LAWS J, EVANS B. Modelling and trading the soybean-oil crush spread with recurrent and higher order networks: A comparative analysis[J]. Neural Network World, 2006, 16(3): 193.
|
[13] |
DUNIS C L, LAWS J, MIDDLETON P W, et al. Trading and hedging the corn/ethanol crush spread using time-varying leverage and nonlinear models[J]. The European Journal of Finance, 2015, 21(4): 352-375.
|
[14] |
曾濂, 马丹頔, 刘宗鑫. 基于BP神经网络改进的黄金价格预测[J]. 计算机仿真, 2010 (9): 200-203.ZENG Lian, MA Dandi, LIU Zongxin. Gold price forecast based on improved BP neural network[J]. Computer Simulation, 2010, 27(9):200-203.
|
[15] |
张金仙, 闫二乐, 杨拴强. 基于自适应 BP 神经网络的上证指数预测模型的研究[J]. 长春大学学报, 2016, 26(6):26-30.ZHANG Jinxian, YAN Erle, YANG Shuanqiang. Research on prediction model of shanghai stock exchange index based on self-adaptive BP neural network[J]. Journal of Changchun University, 2016, 26(6): 26-30.
|
[16] |
林杰, 龚正. 基于人工神经网络的沪锌期货价格预测研究[J]. 财经理论与实践, 2017, 38(2): 54-57.LING Jie, GONG Zheng. A research on forecasting of Shanghai zinc futures price based on artificial neural network[J]. The Theory and Practice of Finance and Economics, 2017, 38(2): 54-57.
|
[17] |
张贵勇. 改进的卷积神经网络在金融预测中的应用研究[D]. 郑州:郑州大学, 2016. ZHANG Guiyong. Research on the application of improved convolutional neural network in financial forecasting[D]. Zhengzhou: Zhengzhou University, 2016.
|
[18] |
TSANTEKIDIS A, PASSALIS N, TEFAS A, et al. Forecasting stock prices from the limit order book using convolutional neural networks[C]// 2017 IEEE 19th Conference on Business Informatics. IEEE, 2017:7-12.
|
[19] |
GRAVES A. Supervised Sequence Labelling with Recurrent Neural Networks[M]. Berlin: Springer, 2012: 15-35.
|
[20] |
ENGLE R F, GRANGER C W J. Co-integration and error correction: Representation, estimation, and testing[J]. Econometrica: Journal of the Econometric Society, 1987,55(2): 251-276.
|
[1] |
HOCHREITER S, SCHMIDHUBER J. Long short-term memory[J]. Neural Computation, 1997, 9(8): 1735-1780.
|
[2] |
GERS F A, SCHMIDHUBER J, CUMMINS F. Learning to forget: Continual prediction with LSTM[J]. Neural Computation, 2000, 12(10): 2451-2471.
|
[3] |
WEN T H, GASIC M, MRKSIC N, et al. Semantically conditioned LSTM-based natural language generation for spoken dialogue systems[C]// Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA: Association for Computational Linguistics, 2015: 1711-1721.
|
[4] |
DONAHUE J, HENDRICKS A L, GUADARRAMA S, et al. Long-term recurrent convolutional networks for visual recognition and description[C]// Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2015: 2625-2634.
|
[5] |
VENUGOPALAN S, XU H, DONAHUE J, et al. Translating videos to natural language using deep recurrent neural networks[J]. Human Language Technologies: The 2015 Annual Conference of the North American Chapter of the ACL. Stroudsburg, PA: Association for Computational Linguistics, 2015: 1494-1504.
|
[6] |
MAKNICKIEN N, MAKNICKAS A. Application of neural network for forecasting of exchange rates and forex trading[C]// The 7th International Scientific Conference “Business and Management 2012”. Vilnius, Lithuania: Vilnius Gediminas Technical University, 2012: 10-11.
|
[7] |
DI PERSIO L, HONCHAR O. Artificial neural networks architectures for stock price prediction: Comparisons and applications[J]. International Journal of Circuits, Systems and Signal Processing, 2016, 10: 403-413.
|
[8] |
SIMON D P. The soybean crush spread: Empirical evidence and trading strategies[J]. Journal of Futures Markets, 1999, 19(3): 271-289.
|
[9] |
仇中群, 程希骏. 基于协整的股指期货跨期套利策略模型[J]. 系统工程, 2008, 26(12): 26-29. QIU Zhongqun, CHENG Xijun. Calendar spread arbitrage strategy model for index futures based on co-integration rule[J]. Systems Engineering, 2008, 26(12):26-29.
|
[10] |
葛翔宇, 吴洋, 周艳丽. 门限协整套利: 理论与实证研究[J]. 统计研究, 2012,29(3): 79-87.GE Xiangyu, WU Yang, ZHOU Yanli. Threshold cointegration arbitrage: Theory and application[J]. Statistical Research, 2012, 29(3): 79-87.
|
[11] |
KANAMURA T, RACHEV S T, FABOZZI F J. A profit model for spread trading with an application to energy futures[J]. The Journal of Trading, 2010, 5(1): 48-62.
|
[12] |
DUNIS C L, LAWS J, EVANS B. Modelling and trading the soybean-oil crush spread with recurrent and higher order networks: A comparative analysis[J]. Neural Network World, 2006, 16(3): 193.
|
[13] |
DUNIS C L, LAWS J, MIDDLETON P W, et al. Trading and hedging the corn/ethanol crush spread using time-varying leverage and nonlinear models[J]. The European Journal of Finance, 2015, 21(4): 352-375.
|
[14] |
曾濂, 马丹頔, 刘宗鑫. 基于BP神经网络改进的黄金价格预测[J]. 计算机仿真, 2010 (9): 200-203.ZENG Lian, MA Dandi, LIU Zongxin. Gold price forecast based on improved BP neural network[J]. Computer Simulation, 2010, 27(9):200-203.
|
[15] |
张金仙, 闫二乐, 杨拴强. 基于自适应 BP 神经网络的上证指数预测模型的研究[J]. 长春大学学报, 2016, 26(6):26-30.ZHANG Jinxian, YAN Erle, YANG Shuanqiang. Research on prediction model of shanghai stock exchange index based on self-adaptive BP neural network[J]. Journal of Changchun University, 2016, 26(6): 26-30.
|
[16] |
林杰, 龚正. 基于人工神经网络的沪锌期货价格预测研究[J]. 财经理论与实践, 2017, 38(2): 54-57.LING Jie, GONG Zheng. A research on forecasting of Shanghai zinc futures price based on artificial neural network[J]. The Theory and Practice of Finance and Economics, 2017, 38(2): 54-57.
|
[17] |
张贵勇. 改进的卷积神经网络在金融预测中的应用研究[D]. 郑州:郑州大学, 2016. ZHANG Guiyong. Research on the application of improved convolutional neural network in financial forecasting[D]. Zhengzhou: Zhengzhou University, 2016.
|
[18] |
TSANTEKIDIS A, PASSALIS N, TEFAS A, et al. Forecasting stock prices from the limit order book using convolutional neural networks[C]// 2017 IEEE 19th Conference on Business Informatics. IEEE, 2017:7-12.
|
[19] |
GRAVES A. Supervised Sequence Labelling with Recurrent Neural Networks[M]. Berlin: Springer, 2012: 15-35.
|
[20] |
ENGLE R F, GRANGER C W J. Co-integration and error correction: Representation, estimation, and testing[J]. Econometrica: Journal of the Econometric Society, 1987,55(2): 251-276.
|