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Research Of Stock Markets In China Based On Sandpile Model

Posted on:2021-03-01Degree:MasterType:Thesis
Country:ChinaCandidate:H C JiFull Text:PDF
GTID:2439330611999268Subject:Financial
Abstract/Summary:PDF Full Text Request
With the continuous development of China’s economy,the stock market is also expanding.Stock market trends and fluctuations have a huge impact on the economy.Since the establishment of Chinese stock market,many experts and scholars have studied the effectiveness of Chinese stock market.In recent years,a large number of literatures show that China’s stock market has reached a weak efficient market.This also shows that the Chinese stock market has already belonged to the category of the efficient market hypothesis.However,other literature studies have found many anomalies in the market that contradict the efficient market hypothesis,such as herd behavior and calendar effect.The occurrence of these phenomena shows that the structure of the stock market is not the case assumed by the efficient market.Therefore,this paper attempts to explore the fractal structure of China’s stock market through the theory of fractal market hypothesis,and to make an empirical analysis of China’s stock market through the theory of self-organizing criticality and sand heap model in fractal theory.The first chapter,the paper summarizes and analyzes relevant research literature at home and abroad.The second chapter,the paper starts with the fractal market hypothesis,summarizes and discusses the differences between the fractal market hypothesis and the efficient market hypothesis.The third chapter,the R/S analysis method is used to make an empirical study on the fractal characteristics of Chinese stock market,and to explore whether Chinese stock market is in the state of fractal market.The fourth chapter,this paper introduces and discusses the famous theory of self-organizing criticality in fractal theory and dynamics theory.The theory of self-organizing criticality is the foundation to reveal the sand heap model,so the study of the theory of self-organizing criticality is helpful to better understand the sand heap model.The fifth chapter,By using the sandpile model to study and explore the internal dynamics mechanism of Chinese stocks,and using the data of the Shanghai and Shen Zhen stock markets in recent 20 years for empirical research,the internal dynamics mechanism of Chinese stock market and the fractal structure of Chinese stock market are explored.The empirical study on the fractal structure and dynamics mechanism of Chinese stock market shows that: China’s stock market is not an efficient market,but a fractal market structure.China’s stock market has a long-term correlation,and both the Shang Hai and Shen Zhen stock markets have a positive long-term memory of about 150 days.The Chinese stock market satisfies the relevant characteristics of the sandpile model and it is an open dissipative system,which will develop towards the self-organized critical state.In the self-organized critical state,any disturbance will lead to the fluctuation of stock price distance.China’s stock market presents scale invariance in space and time.The probability of large-scale decline in Shang Hai stock market is higher than that of large-scale rise,and the duration of decline is higher than that of rise.Shen Zhen stock market in the occurrence of a large decline in the probability is higher than the probability of a large rise in the fall of the duration of time is lower than the duration of the rise.In a relatively stable external environment,the fluctuation of the stock market price in China is mainly determined by various factors within the system.This paper explores the fractal structure of China’s stock market,and the research results are more in line with the situation of the real market,so as to further explore the internal mechanism of China’s stock market and study the stock price volatility of China’s stock market.
Keywords/Search Tags:China stock markets, fractal market, self-organized criticality, R/S analysis, sandpile model
PDF Full Text Request
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