1 LI Q , CHEN Y , WANG J . Web media and stock markets: a survey and future directions from a big data perspective[J]. IEEE Transactions on Knowledge and Data Engineering, 2018, 30(2): 381-399.
2 陈浪南,杨科 . 中国股市高频波动率的特征、预测模型以及预测精度比较[J]. 系统工程理论与实践, 2013, 33(2): 296-307. (CHEN L N, YANG K. High-frequency volatility features, forecast model and performance evaluation[J]. Systems Engineering-Theory and Practice, 2013, 33(2): 296-307.)
3 CHAN J , LIN S , YU Y , et al . Analysts’ stock ownership and stock recommendations[J]. Journal of Accounting and Economics, 2018, 66(2/3): 479-498.
4 ZHANG X , QU S , HUANG J , et al . Stock market prediction via multi-source multiple instance learning[J]. IEEE Access, 2018, 6: 50720-50728.
5 RENAULT T . Intraday online investor sentiment and return patterns in the U.S. stock market[J]. Journal of Banking and Finance, 2017, 84: 25-40.
6 BOLLEN J , MAO H , ZENG X . Twitter mood predicts the stock market[J]. Journal of Computational Science, 2011, 2(1): 1-8.
7 KAO L J, CHIU C C , LU C J , et al . A hybrid approach by integrating wavelet-based feature extraction with MARS and SVR for stock index forecasting[J]. Decision Support Systems, 2013, 54(3):1228-1244.
8 李振平,桂预风 . 基于灰关联神经网络和马尔可夫模型的股票价格预测[J]. 内蒙古师范大学学报(自然科学汉文版), 2016, 45(3): 310-314. (LI Z P, GUI Y F. Prediction of stock price based on grey correlation neural network and Markov model[J]. Journal of Inner Mongolia Normal University (Natural Science Edition), 2016, 45(3): 310-314.)
9 YU Y , WANG S , ZHANG L . Stock price forecasting based on BP neural network model of network public opinion[C]// Proceedings of the 2nd International Conference on Image, Vision and Computing. Piscataway: IEEE, 2017: 1058-1062.
10 刘健,何林,袁建华,等 . 基于新式组合算法的上证综合指数预测[J]. 计算机仿真, 2013, 30(12): 203-207. LIU J , HE L , YUAN J H , et al . Shanghai composite index forecast based on new combinational algorithm[J]. Computer Simulation, 2013, 30(12): 203-207.
11 HU H , TANG L , ZHANG S , et al . Predicting the direction of stock markets using optimized neural networks with Google trends[J]. Neurocomputing, 2018, 285: 188-195.
12 BOZORGI S M , YAZDANI S . IWOA: an improved whale optimization algorithm for optimization problems[J]. Journal of Computational Design and Engineering, 2019, 6(3): 243-259.
13 XU M , SHANG P , LIN A . Cross-correlation analysis of stock markets using EMD and EEMD[J]. Physica A: Statistical Mechanics and its Applications, 2016, 442: 82-90.
14 ZHONG X , ENKE D . A comprehensive cluster and classification mining procedure for daily stock market return forecasting[J]. Neurocomputing, 2017, 267: 152-168.
15 WANG L . Modeling Stock price dynamics with fuzzy opinion networks[J]. IEEE Transactions on Fuzzy Systems, 2017, 25(2): 277-301.
16 LUO B , ZENG J , DUAN J . Emotion space model for classifying opinions in stock message board[J]. Expert Systems with Applications, 2016, 44: 138-146.
17 石善冲,朱颖楠,赵志刚,等 . 基于微信文本挖掘的投资者情绪与股票市场表现[J]. 系统工程理论与实践, 2018, 38(6): 1404-1412. SHI S C , ZHU Y N , ZHAO Z G , et al . The investor sentiment mined from WeChat text and stock market performance[J]. Systems Engineering-Theory and Practice, 2018, 38(6): 1404-1412.
18 FENG X , CHAN K C , YANG D . Short sale constraints, dispersion of opinion, and stock overvaluation: evidence from earnings announcements in China[J]. The North American Journal of Economics and Finance, 2017, 41: 217-230.
19 CAO J , LI Z , LI J . Financial time series forecasting model based on CEEMDAN and LSTM[J]. Physica A: Statistical Mechanics and its Applications, 2019, 519: 127-139.
20 LUO J , SHI B . A hybrid whale optimization algorithm based on modified differential evolution for global optimization problems[J]. Applied Intelligence, 2019, 49(5): 1982-2000.
21 褚鼎立,陈红,王旭光 . 基于自适应权重和模拟退火的鲸鱼优化算法[J]. 电子学报, 2019, 47(5): 992-999. (CHU D L, CHEN H, WANG X G. Whale optimization algorithm based on adaptive weight and simulated annealing[J]. Acta Electronica Sinica, 2019, 47(5): 992-999.)
22 BOZORGI S M , YAZDANI S . IWOA: an improved whale optimization algorithm for optimization problems[J]. Journal of Computational Design and Engineering, 2019, 6(3): 243-259.
23 张润梅,胡学钢,王浩,等 . 基于能量计算模型的贝叶斯网络股市态势预测算法[J]. 模式识别与人工智能, 2015, 28(12): 1137-1146. ZHANG R M , HU X G , WANG H , et al . Stock market trend forecast algorithm based on energy computational model of Bayesian networks[J]. Pattern Recognition and Artificial Intelligence, 2015, 28(12): 1137-1146. |