Distinguishing manipulated stocks via trading network analysis
Manipulation is an important issue for both developed and emerging stock markets. For the study of manipulation, it is critical to analyze investor behavior in the stock market. In this paper, an analysis of the full transaction records of over a hundred stocks in a one-year period is conducted. For each stock, a trading network is constructed to characterize the relations among its investors. In trading networks, nodes represent investors and a directed link connects a stock seller to a buyer with the total trade size as the weight of the link, and the node strength is the sum of all edge weights of a node. For all these trading networks, we find that the node degree and node strength both have tails following a power-law distribution. Compared with non-manipulated stocks, manipulated stocks have a high lower bound of the power-law tail, a high average degree of the trading network and a low correlation between the price return and the seller-buyer ratio. These findings may help us to detect manipulated stocks.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Gao-Feng Gu & Wei Chen & Wei-Xing Zhou, 2007. "Empirical distributions of Chinese stock returns at different microscopic timescales," Papers 0708.3472, arXiv.org.
- Shen, Huawei & Cheng, Xueqi & Cai, Kai & Hu, Mao-Bin, 2009. "Detect overlapping and hierarchical community structure in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1706-1712.
- Parameswaran Gopikrishnan & Vasiliki Plerou & Xavier Gabaix & H. Eugene Stanley, 2000. "Statistical Properties of Share Volume Traded in Financial Markets," Papers cond-mat/0008113, arXiv.org.
- Mookerjee, Rajen & Yu, Qiao, 1999. "An empirical analysis of the equity markets in China," Review of Financial Economics, Elsevier, vol. 8(1), pages 41-60, June.
- Zhang, J.W. & Zhang, Y. & Kleinert, H., 2007. "Power tails of index distributions in chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 166-172.
- Wang, Junjie & Zhou, Shuigeng & Guan, Jihong, 2011. "Characteristics of real futures trading networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 398-409.
- Jie-Jun Tseng & Sai-Ping Li & Sun-Chong Wang, 2010. "Experimental evidence for the interplay between individual wealth and transaction network," Papers 1001.3731, arXiv.org.
- Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2010. "Complex stock trading network among investors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4929-4941.
- F. Kyriakopoulos & S. Thurner & C. Puhr & S. W. Schmitz, 2009. "Network and eigenvalue analysis of financial transaction networks," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, vol. 71(4), pages 523-531, October.
- Qiu, T. & Zhong, L.X. & Chen, G. & Wu, X.R., 2009. "Statistical properties of trading volume of Chinese stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(12), pages 2427-2434.
- Jarrow, Robert A., 1992. "Market Manipulation, Bubbles, Corners, and Short Squeezes," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 27(03), pages 311-336, September.
- Lee, Kyoung Eun & Lee, Jae Woo, 2007. "Probability distribution function and multiscaling properties in the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 65-70.
- J.-J. Tseng & S.-P. Li & S.-C. Wang, 2010. "Experimental evidence for the interplay between individual wealth and transaction network," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, vol. 73(1), pages 69-74, January.
- Gu, Gao-Feng & Zhou, Wei-Xing, 2007. "Statistical properties of daily ensemble variables in the Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(2), pages 497-506.
- Wei-Xing Zhou, 2008. "Multifractal detrended cross-correlation analysis for two nonstationary signals," Papers 0803.2773, arXiv.org.
- G.-H. Mu & W. Chen & J. Kertész & W.-X. Zhou, 2009. "Preferred numbers and the distributions of trade sizes and trading volumes in the Chinese stock market," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, vol. 68(1), pages 145-152, March.
- V. Plerou & P. Gopikrishnan & X. Gabaix & L. A. N. Amaral & H. E. Stanley, 2001. "Price fluctuations, market activity and trading volume," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 262-269.
- Zhi-Qiang Jiang & Wei-Xing Zhou, 2010. "Complex stock trading network among investors," Papers 1003.2459, arXiv.org, revised May 2010.
- Plamen Ch. Ivanov & Ainslie Yuen & Boris Podobnik & Youngki Lee, 2004. "Common Scaling Patterns in Intertrade Times of U. S. Stocks," Papers cond-mat/0403662, arXiv.org.
- Piccardi, Carlo & Calatroni, Lisa & Bertoni, Fabio, 2010. "Communities in Italian corporate networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5247-5258.
- Tian Qiu & Bo Zheng & Guang Chen, 2010. "Adaptive financial networks with static and dynamic thresholds," Papers 1002.3432, arXiv.org.
- Junjie Wang & Shuigeng Zhou & Jihong Guan, 2010. "Characteristics of Real Futures Trading Networks," Papers 1004.4402, arXiv.org, revised Feb 2011.
When requesting a correction, please mention this item's handle: RePEc:arx:papers:1110.2260. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (arXiv administrators)
If references are entirely missing, you can add them using this form.