LONG Wen

Name: LONG  Wen

Title: Professor

Research Areas: Financial market, Financial data analysis, Fictitious economy

E-mail: longwen@ucas.ac.cn

Administrative Title: Assistant Director of Fictitious Economy Research Lab

 

Highest Degree&Year Earned: Ph.D, 2007

Discipline:Finance and Statistics

 

Publication in the Past 5 Years:

 

1)English Journals&Journal Citations (SSCI/SCI/EI/CSSCI) 

1. Long W , Song L , Tian Y , et al. Analysis of slump and surge phenomenon in Chinese stock market based on sequence alignment method[J]. Soft Computing, 2020, 24(23).       SCI 

2. “Deep Learning-Based Feature Engineering for Stock Price Movement Prediction” Knowledge-Based Systems, 164 (2019): 163-173, with Zhichen Lu, et al.    SCI 

3. “A new graphic kernel method of stock price trend prediction based on financial news semantic and structural similarity” Expert Systems with Applications, 118 (2019): 411-424, with Linqiu Song, et al.       SCI 

4. “Pyramid scheme model for consumption rebate frauds” Chinese Physics B, 2019, 28(7): 078901, with Yong Shi, et al.      SCI 

5. “Sentiment contagion analysis of interacting investors: Evidence from China’s stock forum” Physica A: Statistical Mechanics and its Applications, 523(2019): 246-259, with Yong Shi, et al.     SCI/SSCI 

6. “A Text Mining Based Study of Investor Sentiment and Its Influence on Stock Returns” Economic Computation and Economic Cybernetics Studies and Research, 2018, 52(1): 183-199, with Yong Shi, et al.    SCI/SSCI 

7. “Investor Sentiment Identification based on the Universum SVM” Neural Computing & Applications, 2018, 30(2): 661–670, with Yeran Tang, et al.      SCI 

8. “A complex network for studying the transmission mechanisms in stock market” Physica A: Statistical Mechanics and its Applications, 484 (2017): 345-357, with Jiangjian Shen, et al.     SCI/SSCI 

9. “Correlation Analysis of Industry Sectors in China's Stock Markets Based on Interval Data” Filomat. 2016, 30(15): 3999-4013, with Yeran Tang, et al.  SCI 

10. “Trading strategy based on dynamic mode decomposition: tested in Chinese stock market” Physica A: Statistical Mechanics and its Applications, 461 (2016): 498–508, with Lingxiao Cui.     SCI/SSCI 

11. “Investor Attention, Market Liquidity and Stock Return: A New Perspective” Asian Economic & Financial Review, 2018, 8(3): 341-352, with Bin Wang.    ABI 

12. Zhichen Lu, Wen Long*, Jiashuai Zhang, Yingjie Tian. Factor Integration Based on Neural Networks for Factor Investing, Lecture Notes in Computer Science, 2019, vol 11538, pp. 286-292      EI 

13. Z. Lu, W. Long*, Y. Guo, Extreme Market Prediction for Trading Signal with Deep Recurrent Neural Network, Lecture Notes in Computer Science, 2018, vol 10861, pp. 410–418   EI 

14. Yong Shi, Ye-ran Tang, Wen Long*. Finding Patterns of Stock Returns Based on Sequence Alignment, Procedia Computer Science 2018, 139: 256–262       EI 

15. Wen Long, Linqiu Song, Lingxiao Cui. Relationship between Capital Operation and Market Value Management of Listed Companies Based on Random Forest Algorithm. Procedia Computer Science, 2017, 108: 1271-1280    EI 

16. Fan, Xiuqi, Mengdi Du, and Wen Long*. Risk Spillover Effect of Chinese Commercial Banks: Based on Indicator Method and CoVaR Approach. Procedia Computer Science, (122) 2017: 932-940  EI 

17. Lai, Lin, Chang Li, and Wen Long*. A New Method for Stock Price Prediction Based on MRFs and SSVM, The IEEE International Conference on Data Mining (ICDM), 2017.    EI 

18. Shen, Jiangjian, and Wen Long*. The Regime Characteristics of Chinese Stock Market Industry Sectors. Procedia Computer Science. (91) 2016:512~518       EI 

19. Long, Wen, Lijing Guan, and Lingxiao Cui. Investors’ Attention and the Effects on Stock market: An Empirical Study Based on Stock forum. The IEEE International Conference on Data Mining series (ICDM). 2016.    EI 

20.Long, Wen, Bin Wang, and Lingxiao Cui. The influence of investor attention on Return and Volatility of Stock market. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent. 2016       EI 

21. Long, Wen, and Huiwen Wang. Prediction of sequential static input-output table. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2015   EI

 

2) Chinese Journals&Journal Citations (SSCI/SCI/EI/CSSCI) 

1. Yeran Tang, Wen Long, Yong Shi. Is the irrational behavior of investors the cause of momentum effect—— Evidence from internet financial forum [J]. Securities market guide, 2020 (04): 62-70 CSSCI 

2. Wen Long, Ying Guo, Zhen Wang, Haihong Feng. Will media reports affect the yield of listed companies after M & A? [J]. investment research, 2019,38 (11): 65-80 CSSCI 

3. Long Wen, Mao Yuanfeng, Guan Lijing, Cui Lingxiao, "will the topic of financial news affect the stock return? -- Research Based on the industry sector", management review, 2019, CSSCI 

4. Wen Long, Manyi Zhao, "comparative study on the correlation between China US volatility index and return based on star model", investment research, 2019,CSSCI 

5. Zhenqi Wang, Wen Long *, currency crisis early warning model and empirical research based on equilibrium stability, Journal of systems engineering, 2018, CSSCI 

6. Wenning Yang, Wen Long, "Analysis on the sharp rise and fall of Shanghai and Shenzhen index based on sequence alignment", management review, 2017,CSSCI 

7. Wen Long, Bin Wang, Wenzhi Zhao, "empirical analysis of the impact of the listing of new commodity futures contracts on the volatility of existing contracts", statistics and decision making, 2017 

8. Jiangjian Shen, Wen Long, "Research on volatility and correlation of industry sectors in China's stock market based on Markov state transition", practice and understanding of mathematics, 2016 

9. Zhiping Wei, Wen Long, Kai Wang, Minjun Shi, "study on multi-dimensional method of regional leading industry selection -- Taking Turpan City, Xinjiang as an example", science and technology for development, 2016.

 

Projects Statistics:

1) Number of Research Projects in the Past 5 Years: 5

2) Number of Industrial Projects in the Past 5 Years: 1