本文關(guān)鍵詞： 重標(biāo)極差分析法 Hurst指數(shù) 分形維 相空間重構(gòu) Lyapunov指數(shù)　出處：《西北農(nóng)林科技大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：我國(guó)商品期貨市場(chǎng)的發(fā)展時(shí)間較短,只有二十幾年,在各方面都處于起步階段。但即便如此,農(nóng)產(chǎn)品期貨在套期保值和維護(hù)市場(chǎng)穩(wěn)定方面的作用也已經(jīng)愈發(fā)顯著。因此,對(duì)于金融研究人員來說,如果正確認(rèn)識(shí)農(nóng)產(chǎn)品期貨市場(chǎng)就顯得尤為重要。 傳統(tǒng)上,資本市場(chǎng)的理論基礎(chǔ)是有效市場(chǎng)理論(EMT),它的假設(shè)基礎(chǔ)為線性基礎(chǔ),認(rèn)為資本市場(chǎng)的收益率是服從正態(tài)分布的。然而,頻繁發(fā)生的金融危機(jī)讓學(xué)者們對(duì)資本市場(chǎng)背后的假設(shè)提出了種種質(zhì)疑。而非線性科學(xué)的快速發(fā)展則為學(xué)者們研究金融市場(chǎng)提供了一個(gè)更加有效的工具,使人們不再拘泥于線性理論和有效市場(chǎng)的束縛。 本文以近些年的研究為基礎(chǔ),以兩種比較流行的非線性分析方法——分形理論與混沌理論為基礎(chǔ),對(duì)我國(guó)大豆期貨市場(chǎng)的價(jià)格和成交量波動(dòng)進(jìn)行考察和分析,并首次對(duì)大豆期貨的成交量進(jìn)行了研究。 首先,運(yùn)用重標(biāo)極差分析法(Rescaled Range Analysis, R/S)對(duì)我國(guó)大豆期貨市場(chǎng)整體和單個(gè)大豆期貨的收益率及成交量進(jìn)行了實(shí)證分析,結(jié)果表明：大豆期貨整體收益率序列和成交量序列的Hurst指數(shù)明顯大于0.5,即表現(xiàn)出分形特征。對(duì)單個(gè)大豆期貨合約的研究表明,盡管并非每個(gè)品種都表現(xiàn)出明顯的分形特征,但大多數(shù)的期貨品種的分形特征較為明顯。隨后,采用打亂數(shù)據(jù)的方法對(duì)分形結(jié)果進(jìn)行了檢驗(yàn),打亂后數(shù)據(jù)的Hurst指數(shù)小于打亂前的Hurst指數(shù),表明原始序列存在短期記憶性,證明了非周期循環(huán)的存在。 第二,采用相空間投影的方法對(duì)大豆期貨的價(jià)格序列和成交量序列進(jìn)行了研究。首先采用自相關(guān)函數(shù)法分別計(jì)算了價(jià)格序列和成交量序列的延滯時(shí)間T和嵌入維m,隨后采用小數(shù)據(jù)量算法計(jì)算了大豆期貨價(jià)格波動(dòng)和成交量波動(dòng)的混沌特征參數(shù)。結(jié)果表明：我國(guó)大豆期貨市場(chǎng)的價(jià)格序列的最大Lyapunov指數(shù)為正數(shù),同時(shí),其關(guān)聯(lián)維數(shù)為非整數(shù),這表明,我國(guó)大豆期貨市場(chǎng)存在典型的混沌特征；而成交量波動(dòng)雖然具有正的最大Lyapunov指數(shù),但其關(guān)聯(lián)維數(shù)較小,說明其具有弱混沌特征。 作為對(duì)比,本文第四部分計(jì)算了對(duì)數(shù)收益率序列的混沌特征,其相空間投影表現(xiàn)出一定的隨機(jī)性,表明收益率序列的混沌特征并不明顯。因此,將收盤價(jià)作為研究?jī)r(jià)格序列的參數(shù)較為合適。 綜上,我國(guó)大豆期貨市場(chǎng)的價(jià)格序列具有明顯的分形特征和混沌特征；成交量序列呈現(xiàn)出明顯的分形特征和弱的混沌特征。這表明,采用傳統(tǒng)的以線性模型為基礎(chǔ)的有效市場(chǎng)理論無法解釋我國(guó)大豆期貨市場(chǎng)的價(jià)格及成交量的變化。
[Abstract]:The development of commodity futures market in China is relatively short, only more than 20 years, and it is at the initial stage in every aspect. But even so, the role of agricultural product futures in hedging and maintaining market stability has become more and more significant. For financial researchers, if the correct understanding of the agricultural futures market is particularly important. Traditionally, the theoretical basis of the capital market is the efficient market theory (EMTT), which assumes that the return rate of the capital market is normally distributed. Frequent financial crises have made scholars question the assumptions behind capital markets. The rapid development of nonlinear science has provided a more effective tool for scholars to study financial markets. So that people are no longer bound to linear theory and efficient market constraints. Based on the research in recent years, based on two popular nonlinear analysis methods-fractal theory and chaos theory, this paper investigates and analyzes the fluctuation of price and turnover of soybean futures market in China. The trading volume of soybean futures was studied for the first time. First of all, we use rescaled Range analysis (R / S) to analyze the yield and turnover of soybean futures in China. The results show that the Hurst index of the whole yield series and volume series of soybean futures is more than 0.5, that is to say, it shows fractal characteristics. The study of single soybean futures contract shows that, although not every variety shows obvious fractal characteristics, However, the fractal characteristics of most futures varieties are obvious. Then, the fractal results are tested by the method of scrambling data. The Hurst index of the disturbed data is smaller than that of the Hurst index before scrambling, which indicates that the original sequence has short-term memory. The existence of aperiodic cycles is proved. Second, The price sequence and volume sequence of soybean futures were studied by the method of phase space projection. Firstly, the delay time T and embedded dimension of price sequence and volume sequence were calculated by autocorrelation function method. The chaotic characteristic parameters of price fluctuation and trading volume fluctuation of soybean futures are calculated by using the algorithm of small amount of data. The results show that the maximum Lyapunov index of the price series of soybean futures market in China is a positive number. At the same time, the correlation dimension is non-integer, which indicates that there are typical chaotic characteristics in the soybean futures market in China, while the volatility of trading volume has a positive maximum Lyapunov index, but its correlation dimension is small, which indicates that it has weak chaotic characteristics. By contrast, the chaotic characteristics of logarithmic rate of return series are calculated in the 4th part of this paper. The phase space projection shows a certain randomness, which indicates that the chaotic characteristics of the return sequence are not obvious. It is more appropriate to take the closing price as the parameter of the study price sequence. In summary, the price sequence of soybean futures market in China has obvious fractal and chaotic characteristics, while the trading volume series has obvious fractal characteristics and weak chaotic characteristics. The traditional efficient market theory based on linear model can not explain the change of price and turnover of soybean futures market in China.
【學(xué)位授予單位】：西北農(nóng)林科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F724.5

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