【摘要】：股票市場(chǎng)的波動(dòng)性問(wèn)題一直以來(lái)都是國(guó)內(nèi)外學(xué)者研究的熱點(diǎn)，波動(dòng)性理論研究比較成熟。近年來(lái)，復(fù)雜網(wǎng)絡(luò)理論的應(yīng)用越來(lái)越廣泛，理論及實(shí)證研究豐富，發(fā)展迅速。在證券市場(chǎng)被證明是一個(gè)復(fù)雜系統(tǒng)以后，復(fù)雜網(wǎng)絡(luò)在金融市場(chǎng)方面的應(yīng)用研究也發(fā)展起來(lái)，開(kāi)始在微觀層面的基礎(chǔ)上討論股市的整體特征和性質(zhì)。 本文首先考察了目前不同學(xué)科領(lǐng)域中有關(guān)相似問(wèn)題，并對(duì)其進(jìn)行了深入地探討及分析，歸納出描述兩個(gè)對(duì)象相似的本質(zhì)特征。針對(duì)復(fù)雜網(wǎng)絡(luò)的特點(diǎn)，給出了復(fù)雜網(wǎng)絡(luò)相似元的定義，利用向量的相關(guān)性和隨機(jī)變量的相關(guān)系數(shù)等計(jì)量方法來(lái)計(jì)算相似元數(shù)值。在此基礎(chǔ)上，重新給出復(fù)雜網(wǎng)絡(luò)相似的定義并從微觀層面和中觀層面闡述和對(duì)比分析了幾支股票指數(shù)之間及個(gè)股的相似性和自相似性，為研究復(fù)雜網(wǎng)絡(luò)的自相似性研究提供一個(gè)新的視角。本文主要內(nèi)容分三個(gè)部分，具體如下： 第一部分主要是介紹股市波動(dòng)性網(wǎng)絡(luò)研究所需的背景和理論知識(shí)，包括股市波動(dòng)性網(wǎng)絡(luò)的研究現(xiàn)狀，復(fù)雜網(wǎng)絡(luò)的基本理論、股票市場(chǎng)的相關(guān)知識(shí)。 第二部分重點(diǎn)介紹了目前各學(xué)科關(guān)于相似性、自相似性的描述，總結(jié)歸納相似的共同特征，給出復(fù)雜網(wǎng)絡(luò)相似元、相似和自相似的定義及復(fù)雜網(wǎng)絡(luò)相似元數(shù)值和相似度的計(jì)算方法，這為更好地理解復(fù)雜網(wǎng)絡(luò)和復(fù)雜網(wǎng)絡(luò)自相似性實(shí)際運(yùn)用提供一個(gè)有力的分析工具。 第三部分運(yùn)用粗粒化方法建立復(fù)雜網(wǎng)絡(luò)模型，基于點(diǎn)頻率、點(diǎn)平均周期等概念，分析網(wǎng)絡(luò)的重要拓?fù)涮匦院徒y(tǒng)計(jì)特性。然后對(duì)股指不同時(shí)間段的波動(dòng)性網(wǎng)絡(luò)的相似性和自相似性以及個(gè)股之間和股指之間同一時(shí)間段的波動(dòng)性網(wǎng)絡(luò)的相似性進(jìn)行比較分析，說(shuō)明不同地區(qū)和不同時(shí)間段的股市波動(dòng)性網(wǎng)絡(luò)之間的聯(lián)系。在此基礎(chǔ)上考慮個(gè)股波動(dòng)性網(wǎng)絡(luò)的性質(zhì)。
[Abstract]:Volatility in stock market has always been a hot topic for scholars at home and abroad, and the theory of volatility is relatively mature. In recent years, the application of complex network theory is more and more extensive. After the securities market has been proved to be a complex system, the application of complex network in the financial market has also developed, and the overall characteristics and properties of the stock market have been discussed on the basis of the microscopic level. In this paper, we first investigate the similarity problems in different disciplines, and analyze them deeply, and conclude the essential characteristics of describing the similarity between the two objects. According to the characteristics of complex network, the definition of similarity element of complex network is given, and the similarity element value is calculated by using the methods of vector correlation and correlation coefficient of random variables. On this basis, the definition of similarity of complex network is redefined, and the similarity and self-similarity of several stock indices and individual stocks are analyzed and compared from the micro level and the middle level. It provides a new perspective for the study of self-similarity of complex networks. The main contents of this paper are as follows: the first part mainly introduces the background and theoretical knowledge needed for the research of volatility network in stock market, including the current research situation of volatility network in stock market, the basic theory of complex network, Knowledge of the stock market. The second part focuses on the description of similarity and self-similarity in various disciplines, summarizes the common characteristics of similarity, and gives the similarity element of complex network. The definition of similarity and self-similarity and the calculation method of similarity element and similarity degree of complex network provide a powerful tool for understanding the practical application of complex network and complex network self-similarity. In the third part, the rough granulation method is used to establish the complex network model. Based on the concepts of point frequency and point average period, the important topological and statistical characteristics of the network are analyzed. Then the similarity and self-similarity of volatility networks in different time periods of stock index and the similarity of volatility networks between individual stocks and stock indexes in the same time period are compared and analyzed. It shows the relationship between the stock market volatility network in different regions and different time periods. On this basis, consider the nature of the volatility network of individual stocks.
【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類(lèi)號(hào)】：F224;F830.91

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