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The Long-term Memory And Clustering Complexity Of Securities Market

Posted on:2010-05-12Degree:DoctorType:Dissertation
Country:ChinaCandidate:F X HuangFull Text:PDF
GTID:1119360302960488Subject:Economic Systems Analysis and Management
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As the Efficient Market Hypothesis (EMH) assumed that the existence of a normal distribution, skewed or fat-tailed and other issues.Fractal Market Hypothesis (FMH) is proposed, it does not require assumptions such as normal distribution. EMH by the failure to include long-term memory is one of the important characteristics of FMH. Also known as long-term memory and long-term relationship, long-term dependence, which describes the time-series with a longer lag period related to each other. If the existence of a time series of long-term memory, then a longer period of observation between the value of the interdependence between the continuing relationship between the sequence at this time but will show a clear cycle of volatile fluctuations in the characteristics of the cycle.Characteristics of long-term memory for the system to identify non-linear structure, as well as the effectiveness of market research is of great significance. The existence of long-term memory as a result of the stock market, and the elements of the system is the interaction between the complex and changeable, and therefore are non-linear complex systems. The introduction of topology subdominant ultra-metric space is proposed for clustering method of the stock market.Aimed at the problem of whether long-term memory exists in daily return time series and Volatility series about G7 and BRIC stock market. Non-parametric statistics methods of (classical R/S, modified R/S, V/S) and semi-parametric estimation (standard GPH, tapered GPH) comparatively are adopted to evaluate. The sample is to use close price of daily return time series of G7 and BRIC stock market from Jan 4, 2001 to Mar 31, 2009. It detects the long-term memory effect in daily returns and volatilities of three typical measures of G7 and BRIC stock market. The following results: The following results: Firstly, The long-term memory exists in daily returns of SSEC, HIS, NIKKEI225, FTSE100, CAC40, DAX, BOVESPA, MIBTEL, TSX, RTX, BSE30. Secondly, the long-term memory exists in their volatilities of three typical measures. There is very important meaning for the system to identify non-linear structure, as well as the effectiveness of market research. Partly, New York stock market of USA is the most effective( H of DJI on 0.4582 is the closest 0.5); Shanghai stock market of China is the most inefficient(H of SSEC is Up to 0.6882).This study's objective was to overcome the issue of the popular parameter analysis method, which would bring the diversity of results in clustering analysis of securities market. Subdominant ultra-metric space is provided with the exactly defined topology sequence. Firstly, based on the correlation coefficient between every two housing prices of two cities, Euclidean distance of ultra-metric space is calculated; Secondly, subdominant ultra-metric space of portfolio is constructed based on minimum spanning tree of Kruskal; Finally, index hierarchical structure is mapped from subdominant ultra-metric space and its visualization.(1) Via date from sample of Shanghai and Shenzhen 300 Index from Jul, 2005 to Dec,2007, results is finding: ?The style effect is prominent, especially for the industry style, and the other styles, for example, the sharing style, the event style, the capital style and the size style are distributed independently in different periods; (2) According to the MST, central node is the industry, which proves that the industry is very important in the China's macro-economic from the new perspective. (3) The finance and IT are in the highest lever of index hierarchical structure, which proves that the finance and IT are the basis of structure. This shows that the evolution of Shanghai and Shenzhen 300 industrial associated with the path-dependent. Between Shanghai and Shenzhen 300 industry in the overall dynamic stability are relatively stable on, but at the individual time (Joint-stock reform) had a dramatic fluctuations. This is Associated with severe external shocks at the time of the reform policies. In order to avoid sharp fluctuations in the stock market, stock market reform should be gradual and preference IPO about dominator of calling among the first and third industry is post advanced.(2) In order to study the evolution of linkages and the dynamic stability of the national index of Global Stock Market under the impact of Financial Crisis. Via date data from the most representative stock index, January, 2005 to June, 2009, result of demonstration is finding: There is more significant clustering effect in world stock market after the outbreak of Financial Crisis. Over time, the distance between the national indexes shows a trend of reducing, which indicates that the relevance of the national index is improving more significantly. The dynamic stability of the global stock market overall is relatively stable. However, since March 2007 it has been significantly weakened. In order to avoid sharp fluctuations in the stock market, financial supervision should be global coordination, and should not be a country or a region of isolated acts. Develop reasonable financial regulatory policies timely to guard against financial risks. Maintain the diversity of all types of financial institutions, to prevent economic and financial integration of the saying" One with all, a loss will also be ruined!"This shows that method of Subdominant Ultra-metric Space is effective in clustering analysis of securities market.
Keywords/Search Tags:long-term memory, rescaled range(R/S), tapered GPH, Subdominant Ultra-metric Space, Minimum Spanning Tree (MST), Index Hierarchical Structure, Clustering Effect
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