IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v57y2021i2d10.1007_s10614-020-09970-8.html
   My bibliography  Save this article

An Intelligent System for Insider Trading Identification in Chinese Security Market

Author

Listed:
  • Shangkun Deng

    (China Three Gorges University
    China Three Gorges University)

  • Chenguang Wang

    (China Three Gorges University)

  • Zhe Fu

    (Beijing Normal University)

  • Mingyue Wang

    (China Three Gorges University)

Abstract

Insider trading is one kind of criminal behaviors in security markets. It has existed since the birth of the security market. Until 2018, the history of the Chinese security market is less than 30 years, nonetheless, insider trading behavior frequently occurred. In this study, we mainly explore the features of insider trading behavior by studying relevant indicators during the sensitive period (time window length before the release of insider information). For this purpose, an intelligent system with an integration method of Principal Component Analysis (PCA) and Random Forest (RF) is proposed to identify insider tradings in Chinese security market. In the proposed method, we first collect twenty-six relevant indicators for insider trading samples that occurred from 2007 to 2017 and corresponding non-insider trading samples in Chinese security market. Next, by using the PCA, indicator dimension is reduced and principal components are extracted. Then, relations between insider trading samples and principal components are learnt by the RF algorithm. In the identification phase, the trained PCA-RF model is applied to classify the insider trading and non-insider trading samples, as well as analyzing the relative importance of indicators for insider trading identification. Experimental results showed us that under the 30-, 60-, and 90-days time window lengths, recall results of the proposed method for the out-of-samples identification were 73.53%, 83.87%, and 79.41%, respectively. We further investigate the voting threshold of RF for the proposed method, and we found when the voting threshold of RF was increased to more than 70%, the proposed method produced identification accuracy up to more than 90%. In addition, the relative importance result of RF indicated that three indicators were crucial for insider trading identification. Moreover, identification accuracy and efficiency of the proposed method were substantially superior to benchmark methods. In summary, experimental results indicated that the proposed method could be efficiently applied to Chinese security market. Thus, the proposed method can provide useful suggestions to market regulators for insider trading investigations.

Suggested Citation

  • Shangkun Deng & Chenguang Wang & Zhe Fu & Mingyue Wang, 2021. "An Intelligent System for Insider Trading Identification in Chinese Security Market," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 593-616, February.
    • Handle: RePEc:kap:compec:v:57:y:2021:i:2:d:10.1007_s10614-020-09970-8
    DOI: 10.1007/s10614-020-09970-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-020-09970-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10614-020-09970-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Utpal Bhattacharya & Hazem Daouk, 2002. "The World Price of Insider Trading," Journal of Finance, American Finance Association, vol. 57(1), pages 75-108, February.
    2. Chao Lu & Xuetong Zhao & Jingwen Dai, 2018. "Corporate Social Responsibility and Insider Trading: Evidence from China," Sustainability, MDPI, vol. 10(9), pages 1-17, September.
    3. Peters, Jan & Baets, Bernard De & Verhoest, Niko E.C. & Samson, Roeland & Degroeve, Sven & Becker, Piet De & Huybrechts, Willy, 2007. "Random forests as a tool for ecohydrological distribution modelling," Ecological Modelling, Elsevier, vol. 207(2), pages 304-318.
    4. Pierre Collin‐Dufresne & Vyacheslav Fos, 2016. "Insider Trading, Stochastic Liquidity, and Equilibrium Prices," Econometrica, Econometric Society, vol. 84, pages 1441-1475, July.
    5. Guillermo Llorente & Roni Michaely & Gideon Saar & Jiang Wang, 2002. "Dynamic Volume-Return Relation of Individual Stocks," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1005-1047.
    6. Pierre Collin‐Dufresne & Vyacheslav Fos, 2016. "Insider Trading, Stochastic Liquidity, and Equilibrium Prices," Econometrica, Econometric Society, vol. 84(4), pages 1441-1475, July.
    7. Agrawal, Anup & Nasser, Tareque, 2012. "Insider trading in takeover targets," Journal of Corporate Finance, Elsevier, vol. 18(3), pages 598-625.
    8. Qi, Min & Zhang, Guoqiang Peter, 2001. "An investigation of model selection criteria for neural network time series forecasting," European Journal of Operational Research, Elsevier, vol. 132(3), pages 666-680, August.
    9. Julan Du & Shang-Jin Wei, 2004. "Does Insider Trading Raise Market Volatility?," Economic Journal, Royal Economic Society, vol. 114(498), pages 916-942, October.
    10. Maug, Ernst, 2002. "Insider trading legislation and corporate governance," European Economic Review, Elsevier, vol. 46(9), pages 1569-1597, October.
    11. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    12. Minenna, Marcello, 2003. "Insider trading, abnormal return and preferential information: Supervising through a probabilistic model," Journal of Banking & Finance, Elsevier, vol. 27(1), pages 59-86, January.
    13. David Aboody & Baruch Lev, 2000. "Information Asymmetry, R&D, and Insider Gains," Journal of Finance, American Finance Association, vol. 55(6), pages 2747-2766, December.
    14. Ali, Usman & Hirshleifer, David, 2017. "Opportunism as a firm and managerial trait: Predicting insider trading profits and misconduct," Journal of Financial Economics, Elsevier, vol. 126(3), pages 490-515.
    15. Jarrell, Gregg A & Poulsen, Annette B, 1989. "Stock Trading before the Announcement of Tender Offers: Insider Trading or Market Anticipation?," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 5(2), pages 225-248, Fall.
    16. Ferreira, Eurico J, 1995. "Insider Trading Activity, Different Market Regimens, and Abnormal Returns," The Financial Review, Eastern Finance Association, vol. 30(2), pages 193-210, May.
    17. Finnerty, Joseph E, 1976. "Insiders and Market Efficiency," Journal of Finance, American Finance Association, vol. 31(4), pages 1141-1148, September.
    18. Lauren Cohen & Christopher Malloy & Lukasz Pomorski, 2012. "Decoding Inside Information," Journal of Finance, American Finance Association, vol. 67(3), pages 1009-1043, June.
    19. Ahern, Kenneth R., 2017. "Information networks: Evidence from illegal insider trading tips," Journal of Financial Economics, Elsevier, vol. 125(1), pages 26-47.
    20. Christophe, Stephen E. & Ferri, Michael G. & Hsieh, Jim, 2010. "Informed trading before analyst downgrades: Evidence from short sellers," Journal of Financial Economics, Elsevier, vol. 95(1), pages 85-106, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Deng, Shangkun & Huang, Xiaoru & Zhu, Yingke & Su, Zhihao & Fu, Zhe & Shimada, Tatsuro, 2023. "Stock index direction forecasting using an explainable eXtreme Gradient Boosting and investor sentiments," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    2. Shangkun Deng & Yingke Zhu & Xiaoru Huang & Shuangyang Duan & Zhe Fu, 2022. "High-Frequency Direction Forecasting of the Futures Market Using a Machine-Learning-Based Method," Future Internet, MDPI, vol. 14(6), pages 1-21, June.
    3. Prashant Priyadarshi & Prabhat Kumar, 2024. "A comprehensive review on insider trading detection using artificial intelligence," Journal of Computational Social Science, Springer, vol. 7(2), pages 1645-1664, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Luke M. Bennett & Wei Hu, 2023. "Filtration enlargement‐based time series forecast in view of insider trading," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 112-140, February.
    2. Ryu, Doojin & Yang, Heejin & Yu, Jinyoung, 2022. "Insider trading and information asymmetry: Evidence from the Korea Exchange," Emerging Markets Review, Elsevier, vol. 51(PA).
    3. Aziz Simsir, Serif & Simsek, Koray D., 2022. "The market impact of private information before corporate Announcements: Evidence from Turkey," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    4. Michael R. King, 2009. "Prebid Run‐Ups Ahead of Canadian Takeovers: How Big Is the Problem?," Financial Management, Financial Management Association International, vol. 38(4), pages 699-726, December.
    5. Denis, David J. & Xu, Jin, 2013. "Insider trading restrictions and top executive compensation," Journal of Accounting and Economics, Elsevier, vol. 56(1), pages 91-112.
    6. Contreras, Harold & Marcet, Francisco, 2021. "Sell-side analyst heterogeneity and insider trading," Journal of Corporate Finance, Elsevier, vol. 66(C).
    7. Sadok El Ghoul & Omrane Guedhami & Robert Nash & He (Helen) Wang, 2022. "Economic policy uncertainty and insider trading," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 45(4), pages 817-854, December.
    8. Agrawal, Anup & Nasser, Tareque, 2012. "Insider trading in takeover targets," Journal of Corporate Finance, Elsevier, vol. 18(3), pages 598-625.
    9. Cheng, Lin & Jin, Qinglu & Ma, Hui, 2023. "Tone emphasis and insider trading," Journal of Corporate Finance, Elsevier, vol. 80(C).
    10. Fich, Eliezer M. & Parrino, Robert & Tran, Anh L., 2023. "When and how are rule 10b5-1 plans used for insider stock sales?," Journal of Financial Economics, Elsevier, vol. 149(1), pages 1-26.
    11. Styliani Panetsidou & Angelos Synapis & Ioannis Tsalavoutas, 2022. "Price run-ups and insider trading laws under different regulatory environments," Review of Quantitative Finance and Accounting, Springer, vol. 59(2), pages 601-639, August.
    12. Aleksanyan, Mark & Danbolt, Jo & Siganos, Antonios & Wu, Betty (H.T.), 2022. "I only fear when I hear: How media affects insider trading in takeover targets," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 318-342.
    13. Pierce, Andrew T., 2024. "Capital-market effects of tipper-tippee insider trading law: Evidence from the Newman ruling," Journal of Accounting and Economics, Elsevier, vol. 77(2).
    14. Contreras, Harold & Korczak, Adriana & Korczak, Piotr, 2023. "Religion and insider trading profits," Journal of Banking & Finance, Elsevier, vol. 149(C).
    15. Tong, Wilson H.S. & Zhang, Shaojun & Zhu, Yanjian, 2013. "Trading on inside information: Evidence from the share-structure reform in China," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1422-1436.
    16. Arturo Bris, 2005. "Do Insider Trading Laws Work?," European Financial Management, European Financial Management Association, vol. 11(3), pages 267-312, June.
    17. Semih Tartaroglu & Michael Imhof, 2017. "Insider trading and response to earnings announcements: the impact of accelerated disclosure requirements," Review of Quantitative Finance and Accounting, Springer, vol. 49(2), pages 315-336, August.
    18. Rahman, Dewan & Malik, Ihtisham & Ali, Searat & Iqbal, Jamshed, 2021. "Do co-opted boards increase insider profitability?," Journal of Contemporary Accounting and Economics, Elsevier, vol. 17(3).
    19. Michael Firth & T. Y. Leung & Oliver M. Rui, 2011. "Insider Trading in Hong Kong: Tests of Stock Returns and Trading Frequency," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 505-533.
    20. Chen, Shenglan & Ma, Hui & Wu, Qiang & Zhang, Hao, 2023. "Does common ownership constrain managerial rent extraction? Evidence from insider trading profitability," Journal of Corporate Finance, Elsevier, vol. 80(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:57:y:2021:i:2:d:10.1007_s10614-020-09970-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.