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  本文選題：復(fù)雜網(wǎng)絡(luò)　切入點(diǎn)：粗�；�　出處：《華中科技大學(xué)》2012年碩士論文

【摘要】：研究股票市場規(guī)律是一門熱門的課題，一方面是因?yàn)橥顿Y者期望能夠找到一定的規(guī)律便于投資，另外一方面是因?yàn)閷W(xué)者們利用股票市場豐富的數(shù)據(jù)資源進(jìn)行理論上的驗(yàn)證，但是一直以來大多數(shù)研究都是基于股票之間的關(guān)系，而本文從復(fù)雜網(wǎng)絡(luò)的觀點(diǎn)出發(fā)對上證指數(shù)波動進(jìn)行探索。 本文利用粗�；椒�，將上證指數(shù)2005年9月—2012年3月逐日收盤價序列轉(zhuǎn)化為由5個字符{R,r,e,D,d}構(gòu)成的上證指數(shù)符號序列。把連續(xù)的兩個符號組合成一種波動模態(tài)，作為網(wǎng)絡(luò)的節(jié)點(diǎn)（也就是連續(xù)三天的上證指數(shù)波動組合），然后按照時間順序連邊，構(gòu)成一個有向加權(quán)上證指數(shù)波動網(wǎng)絡(luò)。進(jìn)而計算網(wǎng)絡(luò)的度與度的分布，，最短路徑長度，聚類系數(shù)，中介中心度等動力學(xué)統(tǒng)計量，研究蘊(yùn)含在網(wǎng)絡(luò)中的拓?fù)浣Y(jié)構(gòu)。另外結(jié)合數(shù)據(jù)挖掘中的聚類分析，將節(jié)點(diǎn)進(jìn)行聚類，合并節(jié)點(diǎn)重建網(wǎng)絡(luò)，深入挖掘上證指數(shù)波動過程中的有用信息。 結(jié)果表明，上證指數(shù)變化具有復(fù)雜性，并且具有類混沌特征，不是完全隨機(jī)的；并且在網(wǎng)絡(luò)中，小幅波動模態(tài)節(jié)點(diǎn)中介中心度高，具有很重要的位置，這是與市場規(guī)律相符的，在實(shí)際的股票市場中，無論是牛市，熊市還是橫盤，都離不開小幅漲或跌的調(diào)整。另外其他含有大幅變化的組合模態(tài)之間的轉(zhuǎn)換可以為投資者提供有用的信息。
[Abstract]:It is a hot topic to study the law of stock market, on the one hand, because investors expect to find some rules to facilitate investment, and on the other hand, because scholars make use of the abundant data resources of stock market for theoretical verification. However, most studies have been based on the relationship between stocks, and this paper explores the volatility of Shanghai stock index from the point of view of complex network. In this paper, by using coarse granulation method, the daily closing price sequence of Shanghai Stock Exchange Index from September 2005 to March 2012 is transformed into a symbol sequence of Shanghai Stock Exchange Index composed of five characters {rrrrrrre / DU _ d}. The two consecutive symbols are combined into a fluctuating mode. As the node of the network (that is, the Shanghai Stock Exchange Index volatility combination for three consecutive days, and then connecting the edges in time order to form a directed weighted Shanghai Stock Exchange Index volatility Network, the distribution of the degree and degree of the network and the shortest path length are calculated. The topological structure contained in the network is studied by using the dynamic statistics such as clustering coefficient and intermediary centrality. In addition, the nodes are clustered and the nodes are merged to reconstruct the network by combining the clustering analysis in data mining. Deeply excavate the useful information in the fluctuation process of Shanghai stock index. The results show that the variation of Shanghai stock index is complex and chaotic, which is not completely random, and in the network, the intermediate center of the small fluctuation mode node is high and has a very important position. This is consistent with the laws of the market, in the actual stock market, whether it's a bull market, a bear market or a horizontal market, It's all about adjusting up or down slightly, and other conversions that contain significant variations in combination modes can provide useful information for investors.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：F830.91;O157.5;F224

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