本文關(guān)鍵詞： 上海股票市場 復(fù)雜性 有效性 排列熵　出處：《南京財(cái)經(jīng)大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：現(xiàn)代金融學(xué)是在有效市場理論的基礎(chǔ)上建立起來的，在此基礎(chǔ)上也產(chǎn)生和發(fā)展了很多重要的金融模型。但是，金融市場因?yàn)椤坝邢蘩硇浴蓖顿Y者的參與而成為一個(gè)復(fù)雜適應(yīng)性系統(tǒng)。復(fù)雜性的存在使得人們認(rèn)識(shí)和駕馭金融市場的難度增加，然而，復(fù)雜性又支撐著金融系統(tǒng)的相對(duì)穩(wěn)定性。因而，考慮金融市場的復(fù)雜性和有效性兩者之間是否存在交互的影響，以及如果存在影響時(shí)又是以何種形式存在的成為一個(gè)值得研究的課題和內(nèi)容。 熵開始是一個(gè)熱力學(xué)的概念，用于描述熱力學(xué)系統(tǒng)的混亂程度。在經(jīng)濟(jì)學(xué)領(lǐng)域中，熵表示復(fù)雜系統(tǒng)的均勻和不確定程度，因此它可以作為度量系統(tǒng)復(fù)雜性程度的指標(biāo)。另一方面，針對(duì)有效市場假說的不足而提出的分形市場假說近年來在金融市場的有效性分析層面起到了重要的作用。因而，本文以熵和有效性指數(shù)分別作為市場復(fù)雜性和有效性的度量，以上證綜合指數(shù)1991年7月15日至2012年6月29日的收盤價(jià)數(shù)據(jù)為研究對(duì)象，根據(jù)上證綜指變化的特點(diǎn)將其劃分為7個(gè)時(shí)間區(qū)間，就以下幾個(gè)方面對(duì)上述問題進(jìn)行了研究： 首先，基于赫斯特指數(shù)與0.5的絕對(duì)離差構(gòu)造有效性指數(shù)，來代表市場有效性，并利用多重分形消除趨勢波動(dòng)分析（MF-DFA）實(shí)證研究了上海股票市場的有效性，結(jié)果表明，上海股票市場目前遠(yuǎn)遠(yuǎn)沒有達(dá)到“弱式”有效狀態(tài)。 其次，應(yīng)用排列熵理論探討了上海股票市場復(fù)雜性。實(shí)證分析顯示排列熵能夠及時(shí)快速有效的提取各種股價(jià)變化時(shí)期的特征，體現(xiàn)股價(jià)變化的有序性，從而能夠正確的反應(yīng)股票市場的復(fù)雜性程度。 最后，結(jié)合“滑動(dòng)窗口”技術(shù)，分析了上海股票市場的效率和排列熵之間的相關(guān)關(guān)系。應(yīng)用BDS檢驗(yàn)發(fā)現(xiàn)，效率指數(shù)和排列熵之間存在非線性關(guān)系；使用交叉相關(guān)系數(shù)分析表明，兩者之間存在交叉影響，且長期的影響較短期更顯著；利用Diks等提出的非線性Granger檢驗(yàn)方法指出，兩者之間存在非常穩(wěn)健地雙向格蘭杰因果關(guān)系。 因此，短期市場復(fù)雜性的增加可能會(huì)降低市場效率，但是長遠(yuǎn)來看，可以通過增加市場復(fù)雜度的方法來提升股票市場的效率。本文也從實(shí)證的角度證實(shí)了劉維奇的觀點(diǎn)，即市場效率與市場本身的復(fù)雜性密切相關(guān)。
[Abstract]:Modern finance is established on the basis of efficient market theory, on which many important financial models have emerged and developed. Financial market has become a complex adaptive system because of the participation of "limited rational" investors. The existence of complexity makes it more difficult for people to understand and control financial market. Complexity, in turn, supports the relative stability of the financial system. Therefore, considering whether there is interaction between the complexity and effectiveness of financial markets, And if there is influence in what form of existence is worth studying the subject and content. Entropy began as a thermodynamic concept used to describe the degree of confusion in thermodynamic systems. In the field of economics, entropy represents the degree of uniformity and uncertainty of complex systems. Therefore, it can be used as an index to measure the complexity of the system. On the other hand, the fractal market hypothesis, which aims at the deficiency of the efficient market hypothesis, has played an important role in the efficiency analysis of financial markets in recent years. In this paper, entropy and efficiency index are taken as the measurement of market complexity and efficiency respectively, and the closing price data of Shanghai Composite Index from July 15th 1991 to June 29th 2012 are taken as the research object. According to the characteristics of the Shanghai Composite Index, it is divided into 7 time intervals, and the above problems are studied in the following aspects:. First of all, based on the absolute deviation of Hurst index and 0.5 to represent the efficiency of the market, and using multifractal to eliminate trend volatility analysis (MF-DFAA) empirical study of the effectiveness of the Shanghai stock market, the results show that, Shanghai stock market is far from reaching the "weak" effective state. Secondly, the complexity of Shanghai stock market is discussed by using permutation entropy theory. The empirical analysis shows that permutation entropy can extract the characteristics of all kinds of stock price change period in time, and reflect the order of stock price change. In order to correctly reflect the complexity of the stock market. Finally, the relationship between efficiency and permutation entropy of Shanghai stock market is analyzed by using "sliding window" technique. The BDS test shows that there is a nonlinear relationship between efficiency index and permutation entropy. The cross correlation coefficient analysis shows that there is a cross effect between the two, and the long-term effect is more significant than that in the short term, and the nonlinear Granger test method proposed by Diks et al. shows that there is a very robust bidirectional Granger causality between the two. Therefore, the increase of short-term market complexity may reduce market efficiency, but in the long run, we can improve the efficiency of stock market by increasing market complexity. That is, market efficiency and the complexity of the market itself is closely related.
【學(xué)位授予單位】：南京財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F832.51;F224

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