DocumentCode :
533120
Title :
Notice of Retraction
Predicting crashes of Chinese Stock market based on Log-Periodic Power Law
Author :
Liu Zhe ; Zhuang Xin-tian ; Yuan Ying
Author_Institution :
Sch. of Bus. Adm., Northeastern Univ., Shenyang, China
Volume :
13
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

By log-periodic power law, this article predicts the collapse time of two stock market bubbles in China from October 2008 to August 2009 financial crisis. Shang Hai & Shen Zhen 300 index and representative shares in key industries of the economy are selected for this analysis. Relative conclusion indicates that Chinese Stock market index and these shares´ situations before crashes are similar to Log-Periodic Power Law model distribution. Fluctuation range of market index between predicted and actual value is [0,2] and about 65% of selected shares is within [0,3] days for above-mentioned two periods; which shows a good availability of logarithm periodic power law model in predicting peak time and it can serve as certain reference to investment risk management.
Keywords :
economic cycles; investment; risk management; stock markets; Chinese stock market index; collapse time prediction; financial crisis; investment risk management; logarithm periodic power law model; Analytical models; Biological system modeling; Computer crashes; Fitting; Fluctuations; Indexes; Stock markets; Complex Network; Log-periodic Power Law; Susceptibility;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Type :
conf
DOI :
10.1109/ICCASM.2010.5622838
Filename :
5622838
Link To Document :
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