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滬深300指數(shù)收益率波動性分階段研究

發(fā)布時間:2018-06-05 01:08

  本文選題:杠桿效應 + 波動非對稱性; 參考:《江西財經(jīng)大學》2012年碩士論文


【摘要】:相當長一段時間以來,金融領域中的研究人員一直致力于對股票價格與其波動率之間關系的研究,這是一項意義重大的課題,而在金融實證領域中對股價波動非對稱性的研究方興未艾。市場波動性在計量風險的大小、檢驗市場的效率性以及估算CAPM中待估計參數(shù)值等方面得到了廣泛的應用,股價的適度波動在一定程度上可以起到提高市場流動性和活躍市場的作用,它是金融經(jīng)濟學中的一項核心內(nèi)容。 本文以反映股市整體走勢的滬深300指數(shù)作為研究對象,對我國股市的波動特點進行分階段實證研究,進而對波動非對稱性進行更加合理、全面的解釋。研究結(jié)果如下: 三個階段的日收益率序列都表現(xiàn)出波動聚集性與尖峰厚尾性。相對于S1階段而言,S2、S3階段的峰度系數(shù)顯著地變小,這表明我國股市波動異常行為正伴隨著股市的成熟日漸減少。GJR-GARCH-M模型和EGARCH-M模型擬合結(jié)果顯示S1階段是非平穩(wěn)過程,S2、S3階段是平穩(wěn)過程,且平穩(wěn)性逐漸增強。在平穩(wěn)過程中,滬深300指數(shù)收益率的相對風險系數(shù)由負數(shù)變成正數(shù),投資者由風險愛好型轉(zhuǎn)變?yōu)轱L險厭惡性,這說明我國股市經(jīng)過二十多年的發(fā)展,市場中的不理性投資現(xiàn)象正在逐漸減少,市場參與者的投資行為漸近理性。 我國股市不僅存在“杠桿效應”,即相對于利好消息而言,等同程度的利空消息對股市造成的波動較大,還存在“反杠桿效應”,即相對于利空消息來說,等同程度的利好消息對股市產(chǎn)生更大的波動效果。因此本文認為股市波動非對稱效應不等同于杠桿效應,波動非對稱性應為利好消息與等同程度的利空消息對股市波動產(chǎn)生不一樣的效果。S2階段的杠桿系數(shù)絕對值最大,說明在金融危機的背景下我國提高印花稅稅率對股市造成了較大的波動效果。 三個階段的信息沖擊曲線表明,我國股市的信息沖擊曲線并不是都呈現(xiàn)V型的,還有L型的。S2階段信息沖擊曲線之所以呈現(xiàn)L型,是因為財政部提高印花稅稅率對我國股市產(chǎn)生了較大的波動。
[Abstract]:For a long time, researchers in the financial field have been working on the relationship between stock prices and their volatility, which is a significant topic. In the field of financial empirical research on the asymmetric volatility of stock prices is in the ascendant. Market volatility has been widely used in measuring the size of risk, testing the efficiency of the market and estimating the parameters to be estimated in CAPM. The moderate fluctuation of stock price can improve the liquidity of the market and activate the market to a certain extent. It is a core content in the financial economics. This paper takes the CSI 300 index which reflects the overall trend of the stock market as the research object, carries on the stage empirical research to the fluctuation characteristic of our country stock market, and then carries on the more reasonable and comprehensive explanation to the fluctuation asymmetry. The findings are as follows: The three stages of daily yield series all show volatility aggregation and peak thick tail. Compared with the S1 stage, the kurtosis coefficient of S2S3 phase has been significantly reduced. This indicates that the abnormal behavior of stock market volatility is decreasing with the maturity of the stock market. The fitting results of GJR-GARCH-M model and EGARCH-M model show that the S1 stage is a stationary process and the stationarity is gradually enhanced. In the steady process, the relative risk coefficient of the Shanghai and Shenzhen 300 index returns has changed from a negative number to a positive number, and the investors have changed from a risk-loving type to a risk-averse one. This shows that the stock market in our country has developed after more than 20 years of development. The irrational investment phenomenon in the market is gradually decreasing, and the investment behavior of market participants is asymptotically rational. There is not only "leverage effect" in China's stock market, that is, relative to the good news, the volatility of the stock market caused by the same degree of bad news is larger, but also the "anti-leverage effect", that is, relative to the bad news. The same level of good news on the stock market has greater volatility effect. Therefore, this paper holds that the asymmetric effect of stock market volatility is not equal to the leverage effect, and the asymmetry of volatility should be the maximum absolute value of leverage coefficient in S.2 stage, which is different from that of good news and the same degree of bad news. Under the background of the financial crisis, the increase of stamp duty rate has a great effect on the stock market. The information shock curve of three stages shows that the information shock curve of China's stock market is not all V-shaped, and the information shock curve of S-2 stage of L type is L-type. It is because the Ministry of Finance raised the stamp duty tax rate to our country stock market produced the big fluctuation.
【學位授予單位】:江西財經(jīng)大學
【學位級別】:碩士
【學位授予年份】:2012
【分類號】:F832.51;F224

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