本文關鍵詞： 收益率 波動率 ARCH模型 GARCH模型　出處：《山東大學》2017年碩士論文　論文類型：學位論文

【摘要】：中國證券市場經過了二十幾年的發(fā)展,取得了巨大的成果,對整個國民經濟做出了巨大的貢獻,但是,中國證券市場還處于發(fā)展的初級階段,基礎還比較薄弱,各種政策制度還不夠完善,在發(fā)展中暴露了很多問題,表現(xiàn)出了波動嚴重的不穩(wěn)定性和明顯的杠桿效應。中國證券市場中存在的問題,越來越受到投資者和專家學者的重視,這些問題對于改善中國金融市場具有重要的意義,所以本文的研究對象是中國證券市場的波動現(xiàn)象。隨著現(xiàn)代金融市場的不斷發(fā)展,人們發(fā)現(xiàn)ARCH族模型能夠對市場波動進行有效地刻畫,所以本文的研究方法是利用ARCH(GARCH)模型對波動率進行建模,從而較為精確的對金融市場上的風險進行度量,對風險的計量提出有價值的建議。本文以上證綜指、深證綜指及創(chuàng)業(yè)板指數(shù)的日收益率為基準,利用ARCH族模型并通過EViews軟件描述了我國股票價格收益率的統(tǒng)計特征,并對中國證券市場的波動進行了實證分析,在前人研究的基礎上,加入了成交量作為解釋變量進行了更為深入的研究。通過研究我們發(fā)現(xiàn),中國證券市場收益率的基本統(tǒng)計特征中,峰度都遠遠大于在正態(tài)分布下的3,具有過度峰度,說明了中國證券市場結構不夠完善,收益率波動較為突出,且收益率序列都是不服從正態(tài)分布的,且收益率序列存在ARCH效應、杠桿效應和不對稱性波動。在引入了成交量這一變量后,通過Granger因果關系檢驗,表明了上海證券市場和深圳證券市場的收益率和成交量之間是存在因果關系。當模型中加入了成交量后,反應股票價格波動持續(xù)性α1+β1的值減小了且擬合優(yōu)度提高了,說明加入了成交量之后,確實更進一步的解釋股票價格波動的原因。但是在創(chuàng)業(yè)板市場,成交量和股票價格波動的GRANGER因果關系的檢驗中,成交量變化率對收益率的波動并不能很好的解釋,因為P值不顯著。對加入了成交量的GARCH模型進行實證研究中,雖然成交量變化率的系數(shù)大于0,但是卻對均值方差的擬合并不是很好,在5%顯著水平下并不顯著,更進一步的表明了成交量對于收益率的波動并不能很好的解釋。
[Abstract]:After more than 20 years of development, China's securities market has made great achievements and made great contributions to the entire national economy. However, China's securities market is still in the initial stage of development and its foundation is still relatively weak. All kinds of policies and systems are not perfect enough, and many problems have been exposed in the course of development, showing serious volatility instability and obvious leverage effect. The problems existing in China's securities market have been paid more and more attention by investors and experts and scholars. These problems are of great significance to the improvement of China's financial market, so the object of this paper is the volatility of China's securities market. It is found that the ARCH family model can effectively depict the volatility of the market, so the research method of this paper is to use the Arch GARCH model to model the volatility, so as to measure the risk in the financial market more accurately. Based on the daily rate of return of Shanghai Composite Index, Shenzhen Composite Index and growth Enterprise Market Index, this paper describes the statistical characteristics of stock price rate of return in China by using ARCH family model and EViews software. On the basis of the previous studies, we add the trading volume as the explanatory variable to further study the volatility of China's securities market. Through the study, we find that, In the basic statistical characteristics of the return rate of China's securities market, kurtosis is far greater than that under normal distribution, which has excessive kurtosis, which indicates that the structure of China's securities market is not perfect, and the fluctuation of yield is more prominent. And the return series are all dissatisfied with normal distribution, and there are ARCH effect, leverage effect and asymmetry fluctuation in the return series. After introducing the variable of trading volume, Granger causality test is adopted. The results show that there is a causal relationship between the return rate and trading volume in Shanghai Stock Market and Shenzhen Stock Market. When the trading volume is added to the model, the value of 偽 1 尾 1, which reflects the volatility of the stock price, decreases and the goodness of fit increases. After adding the trading volume, it is true that the reason for the stock price fluctuation is further explained. But in the gem market, the GRANGER causality test of the volume and the stock price fluctuation, The change rate of turnover does not explain the volatility of yield because P value is not significant. The empirical study of GARCH model with turnover is carried out. Although the coefficient of change rate of turnover is greater than 0, the fitting of mean variance is not very good, and it is not significant at the level of 5%, which further shows that the trading volume does not explain the volatility of yield very well.
【學位授予單位】：山東大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F832.51;O212.1

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本文編號：1502177