Skip to main content
Top
Published in: Review of Quantitative Finance and Accounting 3/2018

03-07-2017 | Original Research

Data analytic approach for manipulation detection in stock market

Authors: Jia Zhai, Yi Cao, Xuemei Ding

Published in: Review of Quantitative Finance and Accounting | Issue 3/2018

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

The term “price manipulation” is used to describe the actions of “rogue” traders who employ carefully designed trading tactics to incur equity prices up or down to make profit. Such activities damage the proper functioning, integrity, and stability of the financial markets. In response to that, the regulators proposed new regulatory guidance to prohibit such activities on the financial markets. However, due to the lack of existing research and the implementation complexity, the application of those regulatory guidance, i.e. MiFID II in EU, is postponed to 2018. The existing studies exploring this issue either focus on empirical analysis of such cases, or propose detection models based on certain assumptions. The effective methods, based on analysing trading behaviour data, are not yet studied. This paper seeks to address that gap, and provides two data analytics based models. The first one, static model, detects manipulative behaviours through identifying abnormal patterns of trading activities. The activities are represented by transformed limit orders, in which the transformation method is proposed for partially reducing the non-stationarity nature of the financial data. The second one is hidden Markov model based dynamic model, which identifies the sequential and contextual changes in trading behaviours. Both models are evaluated using real stock tick data, which demonstrate their effectiveness on identifying a range of price manipulation scenarios, and outperforming the selected benchmarks. Thus, both models are shown to make a substantial contribution to the literature, and to offer a practical and effective approach to the identification of market manipulation.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
go back to reference Aggarwal RK, Wu G (2006) Stock market manipulations. J Bus 79(4):1915–1953CrossRef Aggarwal RK, Wu G (2006) Stock market manipulations. J Bus 79(4):1915–1953CrossRef
go back to reference Ahrabian A, Took CC, Mandic DP (2012) Algorithmic trading using phase synchronization. IEEE J Sel Top Signal Process 6(4):399–404CrossRef Ahrabian A, Took CC, Mandic DP (2012) Algorithmic trading using phase synchronization. IEEE J Sel Top Signal Process 6(4):399–404CrossRef
go back to reference Aitken M, Harris F, Ji S (2009) Trade-based manipulation and market efficiency: a cross-market comparison. In: 22nd Australasian finance and banking conference. Sydney, p 18 Aitken M, Harris F, Ji S (2009) Trade-based manipulation and market efficiency: a cross-market comparison. In: 22nd Australasian finance and banking conference. Sydney, p 18
go back to reference Allen F, Gale D (1992) Stock price manipulation. Rev Financ Stud 5(3):503–529CrossRef Allen F, Gale D (1992) Stock price manipulation. Rev Financ Stud 5(3):503–529CrossRef
go back to reference Bishop CM (2006) Pattern recognition and machine learning. Springer, New York Bishop CM (2006) Pattern recognition and machine learning. Springer, New York
go back to reference Bollerslev T (1986) Generalized autoregressive conditional heteroskedasticity. J Econ 31(3):307–327CrossRef Bollerslev T (1986) Generalized autoregressive conditional heteroskedasticity. J Econ 31(3):307–327CrossRef
go back to reference Caetano MA, Yoneyama T (2009) A new indicator of imminent occurrence of drawdown in the stock market. Phys A 388(17):3563–3571CrossRef Caetano MA, Yoneyama T (2009) A new indicator of imminent occurrence of drawdown in the stock market. Phys A 388(17):3563–3571CrossRef
go back to reference Cao L, Ou Y, Yu P (2012) Coupled behavior analysis with applications. IEEE Trans Knowl Data Eng 24(8):1378–1392CrossRef Cao L, Ou Y, Yu P (2012) Coupled behavior analysis with applications. IEEE Trans Knowl Data Eng 24(8):1378–1392CrossRef
go back to reference Cao Y, Li Y, Coleman S, Belatreche A, McGinnity M (2015) Adaptive hidden Markov model with anomaly states for price manipulation detection. IEEE Trans Neural Netw Learn Syst 26:318–330CrossRef Cao Y, Li Y, Coleman S, Belatreche A, McGinnity M (2015) Adaptive hidden Markov model with anomaly states for price manipulation detection. IEEE Trans Neural Netw Learn Syst 26:318–330CrossRef
go back to reference CFTC (2013) Antidisruptive practices authority no. 3038-AD96. US Commodity Future Trading Commission CFTC (2013) Antidisruptive practices authority no. 3038-AD96. US Commodity Future Trading Commission
go back to reference Chang CC, Lin CJ (2011) LIBSVM: a library for support vector machines. ACM Trans Intell Syst Technol 2:27:1–27:27CrossRef Chang CC, Lin CJ (2011) LIBSVM: a library for support vector machines. ACM Trans Intell Syst Technol 2:27:1–27:27CrossRef
go back to reference Chow EH-Y, Hung C-W, Liu CS, Shiu C-Y (2013) Expiration day effects and market manipulation: evidence from Taiwan. Rev Quant Financ Account 41:441–462CrossRef Chow EH-Y, Hung C-W, Liu CS, Shiu C-Y (2013) Expiration day effects and market manipulation: evidence from Taiwan. Rev Quant Financ Account 41:441–462CrossRef
go back to reference Cumming D, Johan S, Li D (2011) Exchange trading rules and stock market liquidity. J Financ Econ 99(3):651–671CrossRef Cumming D, Johan S, Li D (2011) Exchange trading rules and stock market liquidity. J Financ Econ 99(3):651–671CrossRef
go back to reference Cumming DJ, Zhan F, Aitken MJ (2013) High frequency trading and end-of-day manipulation. Technical Report, York University, Toronto Cumming DJ, Zhan F, Aitken MJ (2013) High frequency trading and end-of-day manipulation. Technical Report, York University, Toronto
go back to reference Daubechies I, Lu J, Wu HT (2011) Synchrosqueezed wavelet transforms: an empirical mode decomposition-like tool. Appl Comput Harm Anal 30(2):243–261CrossRef Daubechies I, Lu J, Wu HT (2011) Synchrosqueezed wavelet transforms: an empirical mode decomposition-like tool. Appl Comput Harm Anal 30(2):243–261CrossRef
go back to reference Diaz D, Theodoulidis B, Sampaio P (2011) Analysis of stock market manipulations using knowledge discovery techniques applied to intraday trade prices. Expert Syst Appl 38(15):12757–12771CrossRef Diaz D, Theodoulidis B, Sampaio P (2011) Analysis of stock market manipulations using knowledge discovery techniques applied to intraday trade prices. Expert Syst Appl 38(15):12757–12771CrossRef
go back to reference Ding X, Li Y, Belatreche A, Maguire LP (2014) An experimental evaluation of novelty detection methods. Neurocomputing 135:313–327CrossRef Ding X, Li Y, Belatreche A, Maguire LP (2014) An experimental evaluation of novelty detection methods. Neurocomputing 135:313–327CrossRef
go back to reference Engle RF (1982) Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50(4):987–1008CrossRef Engle RF (1982) Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50(4):987–1008CrossRef
go back to reference EU (2012) Market abuse, amended proposal for a directive. European Commission, Brussels EU (2012) Market abuse, amended proposal for a directive. European Commission, Brussels
go back to reference Feldman M (2009) Analytical basics of the EMD: two harmonics decomposition. Mech Syst Signal Process 23(7):2059–2071CrossRef Feldman M (2009) Analytical basics of the EMD: two harmonics decomposition. Mech Syst Signal Process 23(7):2059–2071CrossRef
go back to reference Ferraris A (2008) Equity market impact models: mathematics at the interface between business and research. Technical Report, Stifterverband fur die Deutsche Wissenschaft, Berlin, Germany Ferraris A (2008) Equity market impact models: mathematics at the interface between business and research. Technical Report, Stifterverband fur die Deutsche Wissenschaft, Berlin, Germany
go back to reference Ghazali R, Hussain AJ, Nawi NM, Mohamad B (2009) Non-stationary and stationary prediction of financial time series using dynamic ridge polynomial neural network. Neurocomputing 72(10–12):2359–2367CrossRef Ghazali R, Hussain AJ, Nawi NM, Mohamad B (2009) Non-stationary and stationary prediction of financial time series using dynamic ridge polynomial neural network. Neurocomputing 72(10–12):2359–2367CrossRef
go back to reference Grimmett G, Stirzaker D (2001) Probability and random processes. Oxford University Press, New York Grimmett G, Stirzaker D (2001) Probability and random processes. Oxford University Press, New York
go back to reference Guo P, Miao Z, Zhang X-P, Shen Y, Wang S (2012) Coupled observation decomposed hidden Markov model for multiperson activity recognition. IEEE Trans Circuits Syst Video Technol 22(9):1306–1320CrossRef Guo P, Miao Z, Zhang X-P, Shen Y, Wang S (2012) Coupled observation decomposed hidden Markov model for multiperson activity recognition. IEEE Trans Circuits Syst Video Technol 22(9):1306–1320CrossRef
go back to reference Hautsch N, Huang R (2012) The market impact of a limit order. J Econ Dyn Control 36(4):501–522CrossRef Hautsch N, Huang R (2012) The market impact of a limit order. J Econ Dyn Control 36(4):501–522CrossRef
go back to reference Haven E, Liu X, Shen L (2012) De-noising option prices with the wavelet method. Eur J Oper Res 222(1):104–112CrossRef Haven E, Liu X, Shen L (2012) De-noising option prices with the wavelet method. Eur J Oper Res 222(1):104–112CrossRef
go back to reference Hayton P, Utete S, King D, King S, Anuzis P, Tarassenko L (2007) Static and dynamic novelty detection methods for jet engine health monitoring. Philos Trans R Soc A Math Phys Eng Sci 365(1851):493–514CrossRef Hayton P, Utete S, King D, King S, Anuzis P, Tarassenko L (2007) Static and dynamic novelty detection methods for jet engine health monitoring. Philos Trans R Soc A Math Phys Eng Sci 365(1851):493–514CrossRef
go back to reference Huang YC, Cheng YJ (2014) The trading behavior of attention securities with different closing mechanisms: evidence from Taiwan. Rev Pacific Basin Financ Markets Policies 17:1450026CrossRef Huang YC, Cheng YJ (2014) The trading behavior of attention securities with different closing mechanisms: evidence from Taiwan. Rev Pacific Basin Financ Markets Policies 17:1450026CrossRef
go back to reference Huang YC, Cheng YJ (2015) Stock manipulation and its effects: pump and dump versus stabilization. Rev Quant Financ Account 44:791–815CrossRef Huang YC, Cheng YJ (2015) Stock manipulation and its effects: pump and dump versus stabilization. Rev Quant Financ Account 44:791–815CrossRef
go back to reference Hull J (2011) Options, futures and other derivatives, 8th edn. Pearson Education, Upper Saddle River Hull J (2011) Options, futures and other derivatives, 8th edn. Pearson Education, Upper Saddle River
go back to reference Ian D (2012) Market abuse and surveillance, economic impact assessment on market abuse and surveillance legislation. Government Office for Science, London Ian D (2012) Market abuse and surveillance, economic impact assessment on market abuse and surveillance legislation. Government Office for Science, London
go back to reference Jawadi F, Louhichi W, Cheffou AI, Randrianarivony R (2016) Intraday jumps and trading volume: a nonlinear Tobit specification. Rev Quant Financ Account 47:1167–1186CrossRef Jawadi F, Louhichi W, Cheffou AI, Randrianarivony R (2016) Intraday jumps and trading volume: a nonlinear Tobit specification. Rev Quant Financ Account 47:1167–1186CrossRef
go back to reference Lee C-C, Lee J-D, Lee C-C (2010) Stock prices and the efficient market hypothesis: evidence from a panel stationary test with structural breaks. Jpn World Econ 22(1):49–58CrossRef Lee C-C, Lee J-D, Lee C-C (2010) Stock prices and the efficient market hypothesis: evidence from a panel stationary test with structural breaks. Jpn World Econ 22(1):49–58CrossRef
go back to reference Lee EJ, Eom KS, Park KS (2013) Microstructure-based manipulation: strategic behavior and performance of spoofing traders. J Financ Mark 16(2):227–252CrossRef Lee EJ, Eom KS, Park KS (2013) Microstructure-based manipulation: strategic behavior and performance of spoofing traders. J Financ Mark 16(2):227–252CrossRef
go back to reference Mendes R, Paiva A, Peruchi R, Balestrassi P (2016) Multiobjective portfolio optimization of ARMA-GARCH time series based on experimental designs. Comput Oper Res 70:434–444CrossRef Mendes R, Paiva A, Peruchi R, Balestrassi P (2016) Multiobjective portfolio optimization of ARMA-GARCH time series based on experimental designs. Comput Oper Res 70:434–444CrossRef
go back to reference Mongkolnavin J, Tirapat S (2009) Marking the close analysis in Thai bond market surveillance using association rules. Expert Syst Appl 36(4):8523–8527CrossRef Mongkolnavin J, Tirapat S (2009) Marking the close analysis in Thai bond market surveillance using association rules. Expert Syst Appl 36(4):8523–8527CrossRef
go back to reference Neal RM (2000) Markov chain sampling methods for Dirichlet process mixture models. J Comput Graph Stat 9(2):249–265 Neal RM (2000) Markov chain sampling methods for Dirichlet process mixture models. J Comput Graph Stat 9(2):249–265
go back to reference Ngai E, Hu Y, Wong Y, Chen Y, Sun X (2011) The application of data mining techniques in financial fraud detection: a classification framework and an academic review of literature. Decision Support Syst 50:559–569CrossRef Ngai E, Hu Y, Wong Y, Chen Y, Sun X (2011) The application of data mining techniques in financial fraud detection: a classification framework and an academic review of literature. Decision Support Syst 50:559–569CrossRef
go back to reference Öğüt H, Doğana MM, Aktaş R (2009) Detecting stock-price manipulation in an emerging market: the case of Turkey. Exp Syst Appl 36(9):11944–11949CrossRef Öğüt H, Doğana MM, Aktaş R (2009) Detecting stock-price manipulation in an emerging market: the case of Turkey. Exp Syst Appl 36(9):11944–11949CrossRef
go back to reference Ong M, Condon N (2012). FINRA joins exchanges and the SEC in fining hold brothers more than $5.9 million for manipulative trading, anti-money laundering, and other violations. SEC, New York. Retrieved from SEC Ong M, Condon N (2012). FINRA joins exchanges and the SEC in fining hold brothers more than $5.9 million for manipulative trading, anti-money laundering, and other violations. SEC, New York. Retrieved from SEC
go back to reference Oztekin A, Kizilaslan R, Freund S, Iseri A (2016) A data analytic approach to forecasting daily stock returns in an emerging market. Eur J Oper Res 253:697–710CrossRef Oztekin A, Kizilaslan R, Freund S, Iseri A (2016) A data analytic approach to forecasting daily stock returns in an emerging market. Eur J Oper Res 253:697–710CrossRef
go back to reference Palshikar GK, Apte MM (2008) Collusion set detection using graph clustering. Data Min Knowl Disc 16(2):135–164CrossRef Palshikar GK, Apte MM (2008) Collusion set detection using graph clustering. Data Min Knowl Disc 16(2):135–164CrossRef
go back to reference Priestley MB (1982) Spectral analysis and time series. Academic Press, Cambridge Priestley MB (1982) Spectral analysis and time series. Academic Press, Cambridge
go back to reference Ron K (1995) A study of cross-validation and bootstrap for accuracy estimation and model selection. In: Proceedings of the fourteenth international joint conference on artificial intelligence. Morgan Kaufmann, San Mateo, pp 1137–1143 Ron K (1995) A study of cross-validation and bootstrap for accuracy estimation and model selection. In: Proceedings of the fourteenth international joint conference on artificial intelligence. Morgan Kaufmann, San Mateo, pp 1137–1143
go back to reference Schölkopf B, Platt JC, Shawe-Taylor J, Smola AJ, Williamson RC (2001) Estimating the support of a high-dimensional distribution. Neural Comput 13(7):1443–1471CrossRef Schölkopf B, Platt JC, Shawe-Taylor J, Smola AJ, Williamson RC (2001) Estimating the support of a high-dimensional distribution. Neural Comput 13(7):1443–1471CrossRef
go back to reference SEC (2013) Securities and exchange commission release. Securities and Exchange Commission, Atlanta SEC (2013) Securities and exchange commission release. Securities and Exchange Commission, Atlanta
go back to reference Stephen B (2009) The use of hidden Markov models for anomaly detection in nuclear core condition monitoring. IEEE Trans Nucl Sci 56(2):453–461CrossRef Stephen B (2009) The use of hidden Markov models for anomaly detection in nuclear core condition monitoring. IEEE Trans Nucl Sci 56(2):453–461CrossRef
go back to reference Tax D (2013) DDtools, the data description toolbox for Matlab version 2.0.1 Tax D (2013) DDtools, the data description toolbox for Matlab version 2.0.1
go back to reference Tse J, Lin X, Vincent D (2012) High frequency trading—measurement, detection and response. Technical Report, Credit Suisse, Zürich, Switzerland Tse J, Lin X, Vincent D (2012) High frequency trading—measurement, detection and response. Technical Report, Credit Suisse, Zürich, Switzerland
go back to reference Van Bellegem S (2003) Adaptive methods for modelling, estimating and forecasting locally stationary processes. Université catholique de Louvain, Louvain Van Bellegem S (2003) Adaptive methods for modelling, estimating and forecasting locally stationary processes. Université catholique de Louvain, Louvain
go back to reference Wang L, Mehrabi MG, Kannatey-Asibu E (2002) Hidden Markov model-based tool wear monitoring in turning. J Manuf Sci Eng 124(3):651–658CrossRef Wang L, Mehrabi MG, Kannatey-Asibu E (2002) Hidden Markov model-based tool wear monitoring in turning. J Manuf Sci Eng 124(3):651–658CrossRef
go back to reference Wu Z, Huang NE (2004) A study of the characteristics of white noise using the empirical mode decomposition method. Proc R Soc Lond Ser A Math Phys Eng Sci 460(2046):1597–1611CrossRef Wu Z, Huang NE (2004) A study of the characteristics of white noise using the empirical mode decomposition method. Proc R Soc Lond Ser A Math Phys Eng Sci 460(2046):1597–1611CrossRef
go back to reference Yeung D-Y, Ding Y (2003) Host-based intrusion detection using dynamic and static behavioral models. Pattern Recognit 36:229–243CrossRef Yeung D-Y, Ding Y (2003) Host-based intrusion detection using dynamic and static behavioral models. Pattern Recognit 36:229–243CrossRef
Metadata
Title
Data analytic approach for manipulation detection in stock market
Authors
Jia Zhai
Yi Cao
Xuemei Ding
Publication date
03-07-2017
Publisher
Springer US
Published in
Review of Quantitative Finance and Accounting / Issue 3/2018
Print ISSN: 0924-865X
Electronic ISSN: 1573-7179
DOI
https://doi.org/10.1007/s11156-017-0650-0

Other articles of this Issue 3/2018

Review of Quantitative Finance and Accounting 3/2018 Go to the issue