本文關(guān)鍵詞：基于復(fù)雜系統(tǒng)理論的金融市場(chǎng)動(dòng)力學(xué)研究　出處：《中國(guó)科學(xué)技術(shù)大學(xué)》2013年博士論文　論文類(lèi)型：學(xué)位論文

  更多相關(guān)文章： 復(fù)雜系統(tǒng) 金融物理 標(biāo)度律 多分形 層次性 復(fù)雜網(wǎng)絡(luò) 金融市場(chǎng) 動(dòng)力學(xué)行為 市場(chǎng)生態(tài)學(xué)

【摘要】：隨著世界經(jīng)濟(jì)貿(mào)易的日益頻繁,金融市場(chǎng)正發(fā)揮著越來(lái)越重要的作用,對(duì)金融市場(chǎng)的研究也引起了各領(lǐng)域的關(guān)注。另一方面,復(fù)雜系統(tǒng)理論研究了當(dāng)相互之間存在復(fù)雜非線性相互作用的個(gè)體自組織形成一個(gè)整體時(shí)所涌現(xiàn)出的宏觀規(guī)律,特別地,當(dāng)個(gè)體具有智能體的特性時(shí),該復(fù)雜系統(tǒng)將呈現(xiàn)各種有趣的性質(zhì),這樣的系統(tǒng)有金融市場(chǎng)、生物學(xué)系統(tǒng)等。利用復(fù)雜系統(tǒng)理論、統(tǒng)計(jì)物理、應(yīng)用數(shù)學(xué)、非線性科學(xué)以及理論物理等手段來(lái)研究金融市場(chǎng)中的物理規(guī)律正發(fā)展成為一門(mén)新興研究熱點(diǎn),被稱(chēng)為金融物理學(xué)。 本研究采用復(fù)雜系統(tǒng)以及統(tǒng)計(jì)物理等理論,根據(jù)研究方法從以下三個(gè)方面研究了金融市場(chǎng)的動(dòng)力學(xué)演化特性： 1.采用湍流理論中的SL層次結(jié)構(gòu)模型研究股票價(jià)格序列的層次結(jié)構(gòu)和多重分形特性。 SL層次結(jié)構(gòu)理論最初用于解釋湍流中發(fā)現(xiàn)的非線性標(biāo)度律,其優(yōu)點(diǎn)在于僅用間歇參數(shù)β、最奇異標(biāo)度指數(shù)h0、余維數(shù)C三個(gè)參數(shù)就能夠較好地描述和解釋多重分形非線性標(biāo)度行為。由于湍流和金融時(shí)間序列的描述存在相似之處,我們用SL層次結(jié)構(gòu)理論對(duì)股票價(jià)格序列進(jìn)行分析后發(fā)現(xiàn),金融時(shí)間序列不僅具有多重分形性,而且存在SL層次結(jié)構(gòu)。用三個(gè)參數(shù)分別對(duì)發(fā)達(dá)和新興的金融市場(chǎng)中的非線性標(biāo)度行為進(jìn)行量化后比較得出,證券市場(chǎng)的多重分形程度與經(jīng)濟(jì)發(fā)展水平和地理位置等因素有關(guān),且層次結(jié)構(gòu)會(huì)隨著市場(chǎng)的演化而變化。本文的研究成果能夠幫助我們更好地理解金融市場(chǎng)的多重分形性質(zhì),且可以利用湍流中與SL層次結(jié)構(gòu)相關(guān)聯(lián)的多變量級(jí)聯(lián)過(guò)程來(lái)解釋金融市場(chǎng)中的動(dòng)態(tài)演化。 2.將金融市場(chǎng)看作一個(gè)由多個(gè)交易者和投資產(chǎn)品所組成的復(fù)雜網(wǎng)絡(luò),利用復(fù)雜網(wǎng)絡(luò)的理論對(duì)證券市場(chǎng)的資產(chǎn)回報(bào)序列進(jìn)行建模,研究網(wǎng)絡(luò)的靜態(tài)拓?fù)浣Y(jié)構(gòu)和動(dòng)態(tài)演化。 采用閾值和滑動(dòng)窗技術(shù),我們分別構(gòu)造了基于動(dòng)態(tài)閾值和靜態(tài)閾值的動(dòng)態(tài)全局金融網(wǎng)絡(luò),并進(jìn)一步計(jì)算了網(wǎng)絡(luò)的三個(gè)全局特征參數(shù)平均度、最短路徑長(zhǎng)度和平均聚類(lèi)系數(shù)分別隨時(shí)間演化的曲線,從而研究網(wǎng)絡(luò)拓?fù)浣Y(jié)構(gòu)的動(dòng)態(tài)變化規(guī)律及其與歷史上所發(fā)生的金融事件之間的聯(lián)系。我們發(fā)現(xiàn),三個(gè)參數(shù)都在金融風(fēng)暴發(fā)生期間出現(xiàn)了異常的波動(dòng)。該研究結(jié)果表明,金融危機(jī)與證券市場(chǎng)價(jià)格走勢(shì)的統(tǒng)計(jì)性質(zhì)之間存在著因果關(guān)系,因而研究動(dòng)態(tài)的金融網(wǎng)絡(luò)有助于我們更深入地理解經(jīng)濟(jì)危機(jī)的發(fā)生和傳播機(jī)制。 3.構(gòu)建一個(gè)包含投資者和投資產(chǎn)品的人工金融市場(chǎng),考察市場(chǎng)的動(dòng)態(tài)演化過(guò)程。我們提出的市場(chǎng)生態(tài)學(xué)模型不僅考慮投資者的動(dòng)力學(xué)演化,而且考慮投資產(chǎn)品的動(dòng)力學(xué)行為,在該模型中,投資者根據(jù)投資策略的不同分為兩種類(lèi)型：主動(dòng)投資者掌握較多的市場(chǎng)信息,投資策略更為優(yōu)化,因而選擇優(yōu)良資產(chǎn)的能力較強(qiáng)；被動(dòng)投資者由于只能獲取少量信息因而投資能力弱于主動(dòng)投資者。這與實(shí)際市場(chǎng)的情況相符合,因?yàn)楝F(xiàn)實(shí)中每個(gè)投資者都只能掌握市場(chǎng)的部分信息。另一方面,投資產(chǎn)品根據(jù)它們的品質(zhì)可以分為優(yōu)良資產(chǎn)和劣質(zhì)資產(chǎn),優(yōu)良資產(chǎn)的品質(zhì)高于劣質(zhì)資產(chǎn),更能吸引投資者進(jìn)行投資,但是優(yōu)質(zhì)產(chǎn)品的成本要高于劣質(zhì)產(chǎn)品。模擬結(jié)果發(fā)現(xiàn),在沒(méi)有任何外界調(diào)控的情況下,系統(tǒng)依靠投資者的投資策略和與投資產(chǎn)品的相互作用,運(yùn)行到足夠長(zhǎng)時(shí)間能夠自組織地到達(dá)一個(gè)準(zhǔn)靜態(tài),在準(zhǔn)靜態(tài)系統(tǒng)的交易者和投資產(chǎn)品的數(shù)量都維持著一個(gè)動(dòng)態(tài)的平衡,且不同的影響因素能夠帶來(lái)不同的準(zhǔn)靜態(tài)性質(zhì),這與生態(tài)系統(tǒng)有著類(lèi)似的性質(zhì),對(duì)實(shí)際金融市場(chǎng)的動(dòng)態(tài)演化和金融危機(jī)的發(fā)生和恢復(fù)有一定的指導(dǎo)意義。
[Abstract]:With the world economy and trade have become increasingly frequent, financial markets are playing an increasingly important role in the study of financial market has also attracted attention in various fields. On the other hand, the theory of complex system is studied when there are complex nonlinear interactions between individual self organization form a macroscopic law, whole emergence each other in particular, when the individual has agent, the complex system will present a variety of interesting properties, such a system of financial markets, biological systems. The use of complex system theory, statistical physics, applied mathematics and theoretical physics, nonlinear science and other means to study the laws of physics in the financial market is becoming a new research hotspot, known as econophysics.
In this study, the dynamic evolution characteristics of the financial market are studied from the following three aspects: complex systems and statistical physics.
1. the hierarchical structure and multifractal characteristics of the stock price sequence are studied by the SL hierarchy model in the turbulence theory.
The SL hierarchy theory originally used to explain the nonlinear turbulence found in the scaling law, the utility model has the advantages of using only intermittent parameter, the singularity exponent H0, codimension three C parameters can be used to describe and explain the nonlinear multifractal scaling behavior. Due to turbulence and financial time series describing the similarities SL, we use hierarchical structure theory of stock price series analysis found that financial time series not only has the multifractal, and SL hierarchy. By three parameters are nonlinear in developed and emerging markets in the scaling behavior was quantified after comparison, the multi fractal degree and economic development the level and geographic location and other factors of the stock market, and the structure will change with the market's evolution. The results of this research can help us better understand the financial market more heavy The fractal properties can be used to explain the dynamic evolution in the financial market by the multivariable cascade process associated with the SL hierarchy in turbulence.
2., we regard the financial market as a complex network composed of multiple traders and investment products. We use the complex network theory to model the asset return sequence in the stock market, and study the static topology and dynamic evolution of the network.
The threshold and sliding window technique, we constructed the dynamic global financial network dynamic and static threshold based on threshold, and further calculate the network characteristic parameters of the three global average degree, shortest path length and the average clustering coefficient respectively with time evolution curve between dynamic changes of network topology and what happened in the history of financial events. We found that the three parameters during the financial turmoil has abnormal fluctuations. The results show that there exists a causal relationship between the statistical properties of the financial crisis and the stock market price movements, so the research of dynamic financial network have occurred and communication mechanism to help us more understanding of the economic crisis.
3. build a contains investors and investment products, artificial financial market, the dynamic evolution of the market. The market ecology model we proposed not only consider the dynamics and evolution of investors, consider the dynamical behavior of investment products, in this model, investors according to different investment strategies into two types: active investors have more the market information and investment strategies to optimize, and excellent asset selection ability is strong; passive investors can only get a small amount of information and weak investment in active investors. This with the actual market situation is consistent, because part of the information of each investor can only grasp the reality of the market. On the other hand, according to their investment products the quality can be divided into good assets and bad assets, excellent asset quality than inferior assets, can attract more investors for investment The capital, but the quality of the product cost is higher than that of inferior products. The simulation results show that in the absence of any external control, interaction systems rely on the investment strategy for investors and investment products, enough to run long time can automatically reach a quasi static, had maintained a dynamic equilibrium in quantity quasi static system products traders and investment, and the influence of different factors can bring different quasi static properties, which have similar properties and ecological system, the actual financial market dynamic evolution and the occurrence of financial crisis and has certain guiding significance to recover.

【學(xué)位授予單位】：中國(guó)科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2013
【分類(lèi)號(hào)】：F830.91;N941.4

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

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本文編號(hào)：1439685