Computer Science ›› 2025, Vol. 52 ›› Issue (6A): 240700108-8.doi: 10.11896/jsjkx.240700108
• Big Data & Data Science • Previous Articles Next Articles
LIU Chengming, LI Haixia, LI Shaochuan, LI Yinghao
CLC Number:
| [1]WU C L,LIU J,HUANG X M.Market Manipulation and Firm Innovation－A Detection Model of Closing Price Manipulation Based on High Frequency Data[J].Review of Investment Stu-dies,2021,40(9):46-66. [2]SHAH Q,GHAFOOR A,QURESHI F,et al.Market manipulation in East-Asian markets:A regulatory overview [J].Studies of Applied Economics,2021,39(2):146-158. [3]LIU Z Q,WANG X,YAO Y.Research on Stock Price Manipulation Identification Model Based on Novel Indicators [J].Jianghuai Tribune,2020(4):119-125. [4]HART O D.On the profitability of speculation[J].The Quarterly Journal of Economics,1977,91(4):579-597. [5]PUTNIŠ T J.Market manipulation:A survey[J].Journal of economic surveys,2012,26(5):952-967. [6]XU L B,YAN H M,ZHANG X F.The Progress of Research on Information-based Market Manipulation Behavior[J].Economic Perspectives,2018(7):130-140. [7]FISCHEL D R,ROSS D J.Should the law prohibit manipulation in financial markets [J].Harv L Rev,1991,105:503. [8]ALLEN F,GALE D.Stock-price manipulation [J].The Review of Financial Studies,1992,5(3):503-529. [9]ZHOU C S,YANG Y H,WANG Y P.Trading-based Market Manipulation in China’s Stock Market[J].Economic Research Journal,2005(10):70-78. [10]AGGARWAL R K,WU G.Stock market manipulations [J].The Journal of Business,2006,79(4):1915-1953. [11]VLAD A.Financial Market Manipulation:How to identify the Mechanisms [J].International Journal of Economic Practices and Theories,2014,4(1):77-88. [12]BERNARDINO W,OSPINA R,DE SOUZA F C,et al.Riskcurves:A methodology to evaluate the risk of fraud by stock price manipulation based on game theory and detection software [J].Journal of Economics and Business,2021,113:105953. [13]WU CL,LIN F Y,LIU J.Can Analyst Focus Curb Market Manipulation? --A closing price manipulation identification model based on high-frequency data [J].South China Finance,2022(5):47-58. [14]KAKDE Y,CHAVAN G,SAH B,et al.Solution Approach for Detection of Stock Price Manipulation by Market Operators [M].Smart Technologies in Data Science and Communication:Proceedings of SMART-DSC 2022.Springer,2023:281-288. [15]ÖČÜT H,DOČANAY M M,AKTAŞ R.Detecting stock-price manipulation in an emerging market:The case of Turkey [J].Expert Systems with Applications,2009,36(9):11944-11949. [16]AKTAS R,DOGANAY M.Stock-price manipulation in the Istanbul stock exchange [J].Eurasian Review of Economics and Finance,2006,2(1):21-28. [17]ZHANGT,ZHAO B X.An Application of Logistic Regression-Based Stock Manipulation Identification Models [J].Digital Technology and Application,2022,40(7):130-133. [18]DIAZ D,THEODOULIDIS B,SAMPAIO P.Analysis of stock market manipulations using knowledge discovery techniques applied to intraday trade prices [J].Expert Systems with Applications,2011,38(10):12757-12771. [19]GOLMOHAMMADI K,ZAIANE O R,DíAZ D.Detecting stock market manipulation using supervised learning algorithms[C]//Proceedings of the 2014 International Conference on Data Science and Advanced Analytics(DSAA).IEEE,2014. [20]ZHANG J,WANG S,XU S,et al.Stock price manipulation detection based on machine learning technology:Evidence in China[C]//4th International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem.2017. [21]NTI I K,ADEKOYA A F,WEYORI B A.A comprehensive evaluation of ensemble learning forstock-market prediction [J].Journal of Big Data,2020,7(1):20. [22]ZHAI J,CAO Y,YAO Y,et al.Computational intelligent hybrid model for detecting disruptive trading activity [J].Decision Support Systems,2017,93:26-41. [23]LIU Q,WANG C,ZHANG P,et al.Detecting stock market manipulation via machine learning:Evidence from China Securities Regulatory Commission punishment cases [J].International Review of Financial Analysis,2021,78:101887. [24]LEANGARUN T,TANGAMCHIT P,THAJCHAYAPONGS.Stock price manipulation detection using a computational neural network model[C]//Proceedings of the 2016 Eighth International Conference on Advanced Computational Intelligence(ICACI).IEEE,2016. [25]WANG Q,XU W,HUANG X,et al.Enhancing intraday stock price manipulation detection by leveraging recurrent neural networks with ensemble learning [J].Neurocomputing,2019,347:46-58. [26]SRIDHAR S,MOOTHA S,SUBRAMANIAN S.Detection of market manipulation using ensemble neural networks[C]//Proceedings of the 2020 International Conference on Intelligent Systems and Computer Vision(ISCV).IEEE,2020. [27]LEANGARUN T,TANGAMCHIT P,THAJCHAYAPONGS.Stock price manipulation detection using generative adversarialnetworks[C]//Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence(SSCI).IEEE,2018. [28]CHULLAMONTHON P,TANGAMCHIT P.A transformermodel for stock price manipulation detection in the stock exchange of Thailand [C]//Proceedings of the 2022 19th International Conference on Electrical Engineering/Electronics,Computer,Telecommunications and Information Technology(ECTI-CON).IEEE,2022. [29]TALLBOYS J,ZHU Y,RAJASEGARAR S.Identification ofstock market manipulation with deep learning[C]//Proceedings of the International Conference on Advanced Data Mining and Applications.Springer,2022. [30]KANG L,MU T J,ZHAO G.Hierarchical Transformer-based Siamese Network for Related Trading Detection in Financial Market[C]//2023 International Joint Conference on Neural Networks(IJCNN).IEEE,2023:1-8. [31]RIZVI B A.Anomaly detection approaches for stock price manipulation detection [M].University of Northumbria at Newcastle(United Kingdom),2021. [32]CAO Y,LI Y,COLEMAN S,et al.Adaptive hidden Markovmodel with anomaly states for price manipulation detection [J].IEEE Transactions on Neural Networks and Learning Systems,2014,26(2):318-30. [33]GOLMOHAMMADI K,ZAIANE O R.Time series contextual anomaly detection for detecting market manipulation in stock market[C]//Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics(DSAA).IEEE,2015. [34]AL-THANI H,HASSEN H,AL-MAADCED S,et al.Unsupervised technique for anomaly detection in Qatar stock market [C]//Proceedings of the 2018 International Conference on Computer and Applications(ICCA).IEEE,2018. [35]NAIDOO V,DU S.A Deep Learning Method for the Detection and Compensation of Outlier Events in Stock Data [J].Electronics,2022,11(21):3465. [36]LEANGARUN T,TANGAMCHIT P,THAJCHAYAPONGS.Using generative adversarial networks for detecting stock price manipulation:the stock exchange of Thailand case study[C]//Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence(SSCI).IEEE,2020. [37]LEANGARUN T,TANGAMCHIT P,THAJCHAYAPONGS.Stock price manipulation detectionusing deep unsupervised learning:The case of Thailand [J].IEEE Access,2021,9:106824-106838. [38]RIZVI B,BELATRECHE A,BOURIDANE A,et al.Detection of stock price manipulation using kernel based principal component analysis and multivariate density estimation [J].IEEE Access,2020,8:135989-136003. [39]CHULLAMONTHON P,TANGAMCHIT P.Ensemble of supervised and unsupervised deep neural networks for stock price manipulation detection [J].Expert Systems with Applications,2023,220:119698. [40]NÚÑEZ DELAFUENTE H,ASTUDILLO C A,DÍAZ D.En-semble Approach Using k-Partitioned Isolation Forests for the Detection of Stock Market Manipulation[J].Mathematics,2024,12:1336. [41]SAFA K,BELATRECHE A,OUADFEL S,et al.WALDATA:Wavelet transform based adversarial learning for the detection of anomalous trading activities[J].Expert Systems with Applications,2024,255(C):124729. |
| [1] | WANG Baohui, GAO Zhan, XU Lin, TAN Yingjie. Research and Implementation of Mine Gas Concentration Prediction Algorithm Based on Deep Learning [J]. Computer Science, 2025, 52(6A): 240400188-7. |
| [2] | ZHANG Yongyu, GUO Chenjuan, WEI Hanyue. Deep Learning Stock Price Probability Prediction Based on Multi-modal Feature Wavelet Decomposition [J]. Computer Science, 2025, 52(6A): 240600140-11. |
| [3] | WANG Chanfei, YANG Jing, XU Yamei, HE Jiai. OFDM Index Modulation Signal Detection Based on Deep Learning [J]. Computer Science, 2025, 52(6A): 240900122-6. |
| [4] | BAO Shenghong, YAO Youjian, LI Xiaoya, CHEN Wen. Integrated PU Learning Method PUEVD and Its Application in Software Source CodeVulnerability Detection [J]. Computer Science, 2025, 52(6A): 241100144-9. |
| [5] | ZOU Ling, ZHU Lei, DENG Yangjun, ZHANG Hongyan. Source Recording Device Verification Forensics of Digital Speech Based on End-to-End DeepLearning [J]. Computer Science, 2025, 52(6A): 240800028-7. |
| [6] | ZHOU Lei, SHI Huaifeng, YANG Kai, WANG Rui, LIU Chaofan. Intelligent Prediction of Network Traffic Based on Large Language Model [J]. Computer Science, 2025, 52(6A): 241100058-7. |
| [7] | GUAN Xin, YANG Xueyong, YANG Xiaolin, MENG Xiangfu. Tumor Mutation Prediction Model of Lung Adenocarcinoma Based on Pathological [J]. Computer Science, 2025, 52(6A): 240700010-8. |
| [8] | TAN Jiahui, WEN Chenyan, HUANG Wei, HU Kai. CT Image Segmentation of Intracranial Hemorrhage Based on ESC-TransUNet Network [J]. Computer Science, 2025, 52(6A): 240700030-9. |
| [9] | RAN Qin, RUAN Xiaoli, XU Jing, LI Shaobo, HU Bingqi. Function Prediction of Therapeutic Peptides with Multi-coded Neural Networks Based on Projected Gradient Descent [J]. Computer Science, 2025, 52(6A): 240800024-6. |
| [10] | FAN Xing, ZHOU Xiaohang, ZHANG Ning. Review on Methods and Applications of Short Text Similarity Measurement in Social Media Platforms [J]. Computer Science, 2025, 52(6A): 240400206-8. |
| [11] | YANG Jixiang, JIANG Huiping, WANG Sen, MA Xuan. Research Progress and Challenges in Forest Fire Risk Prediction [J]. Computer Science, 2025, 52(6A): 240400177-8. |
| [12] | WANG Jiamin, WU Wenhong, NIU Hengmao, SHI Bao, WU Nier, HAO Xu, ZHANG Chao, FU Rongsheng. Review of Concrete Defect Detection Methods Based on Deep Learning [J]. Computer Science, 2025, 52(6A): 240900137-12. |
| [13] | HAO Xu, WU Wenhong, NIU Hengmao, SHI Bao, WU Nier, WANG Jiamin, CHU Hongkun. Survey of Man-Machine Distance Detection Method in Construction Site [J]. Computer Science, 2025, 52(6A): 240700098-10. |
| [14] | CHEN Shijia, YE Jianyuan, GONG Xuan, ZENG Kang, NI Pengcheng. Aircraft Landing Gear Safety Pin Detection Algorithm Based on Improved YOlOv5s [J]. Computer Science, 2025, 52(6A): 240400189-7. |
| [15] | GAO Junyi, ZHANG Wei, LI Zelin. YOLO-BFEPS:Efficient Attention-enhanced Cross-scale YOLOv10 Fire Detection Model [J]. Computer Science, 2025, 52(6A): 240800134-9. |
|
||
Home