Title :
Predicting drastic drop in Chinese stock market with local Hurst exponent
Author :
Xu Shao-jun ; Jin Xue-jun
Author_Institution :
Coll. of Econ., Zhejiang Univ., Hangzhou, China
Abstract :
In this paper we employ detrended fluctuation analysis (DFA) technique to estimate the local Hurst exponent of Shanghai stock exchange composite (SSEC) index, which is used to predict the crash or other drastic decreases in Chinese stock market. We assume the local Hurst exponent can be used to as a measurement of actual excitation or nervous state of the market before the displaying of market index. The empirical result shows that a very clear decreasing trend from greater than 0.5 to less than 0.5 in local Hurst exponent is visible, preceding the market drastic drop point. In-sample vs. out-of-sample tests confirm above viewpoint, showing that local Hurst exponent below 0.5 can be used as an important signal of stock return when stock index is going to face drastic drop, and it has more significant predict power than historical average return forecasting method. So we find efficient market hypothesis (EMH) doesn´t receive support in Chinese stock market, and explore a new method for investment beyond the traditional technical analysis.
Keywords :
economic forecasting; fluctuations; investment; sampling methods; statistical testing; stock markets; Chinese stock market; DFA technique; EMH; SSEC index; Shanghai stock exchange composite; detrended fluctuation analysis; efficient market hypothesis; historical average return forecasting method; in-sample test; investment method; local Hurst exponent; market drastic drop prediction; market index; out-of-sample test; technical analysis; Autocorrelation; Computer crashes; Conference management; Doped fiber amplifiers; Economic forecasting; Educational institutions; Engineering management; Fluctuations; Power generation economics; Stock markets; Chinese stock market; DFA method; drastic drop; local Hurst exponent; out-of-sample test;
Conference_Titel :
Management Science and Engineering, 2009. ICMSE 2009. International Conference on
Conference_Location :
Moscow
Print_ISBN :
978-1-4244-3970-6
Electronic_ISBN :
978-1-4244-3971-3
DOI :
10.1109/ICMSE.2009.5318022