本文關(guān)鍵詞：基于高頻金融數(shù)據(jù)的中國股市波動性研究　出處：《湖南師范大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 高頻數(shù)據(jù) 波動率 加權(quán)已實現(xiàn)極差 VAR模型

【摘要】：隨著計算機技術(shù)的發(fā)展和全球經(jīng)濟一體化進(jìn)程的加快,高頻金融數(shù)據(jù)的獲得也越來越容易,高頻金融數(shù)據(jù)波動率的估計逐漸成為當(dāng)今的研究熱點問題之一。一般情況下,股市的高頻數(shù)據(jù)波動會表現(xiàn)出一些較低頻數(shù)據(jù)不同的特點,刻畫股市高頻數(shù)據(jù)波動性就是為了能夠準(zhǔn)確地描繪了股市波動的典型特征和趨勢,為股市風(fēng)險管理提供理論支撐。 本文以“已實現(xiàn)”波動率模型為基礎(chǔ),運用極差理論的方法,構(gòu)造賦權(quán)“已實現(xiàn)”極差波動,并研究了不同頻率的上證綜指和深證成指的波動特征。在分析賦權(quán)“已實現(xiàn)”極差波動的統(tǒng)計特征的基礎(chǔ)上,論文從微觀層面出發(fā),研究賦權(quán)“已實現(xiàn)”極差波動與交易量之間的相互作用關(guān)系。結(jié)果表明： (1)賦權(quán)“已實現(xiàn)”極差波動具有較小的方差,滿足波動估計量的無偏性和有效性,且經(jīng)對數(shù)化處理后基本符合正態(tài)分布,具有良好的統(tǒng)計性質(zhì)。 (2)深證成指1分鐘高頻數(shù)據(jù)的波動與交易量間不存在Granger關(guān)系,而上證綜指5分鐘高頻數(shù)據(jù)的波動與交易量互為Granger原因,這說明量價關(guān)系并不穩(wěn)定,尤其是在新興資本市場,很多投資者是屬于盲目性投資,存在從眾心理。 (3)對上證綜指5分鐘高頻數(shù)據(jù)構(gòu)建VAR模型,證實了波動與交易量之間存在聯(lián)動性,模型解釋了日內(nèi)波動的聚集性,而且交易量的變動引起價格波動,這在一定程度上解釋了收益波動的原因。同時,波動率也會反饋到交易量,進(jìn)而影響交易量的變動。
[Abstract]:With the development of computer technology and the acceleration of the process of global economic integration, the acquisition of high-frequency financial data is becoming easier and easier. The estimation of volatility of high-frequency financial data has gradually become one of the hot issues. In general, the volatility of high-frequency data in stock market will show some different characteristics than low-frequency data. In order to accurately describe the typical characteristics and trends of stock market volatility, it can provide theoretical support for stock market risk management. Based on the "realized" volatility model, this paper uses the method of range theory to construct the weighted "realized" range fluctuation. And studied the volatility characteristics of Shanghai Composite Index and Shenzhen Composite Index with different frequencies. On the basis of analyzing the statistical characteristics of "realized" range fluctuation, the paper starts from the micro level. The interaction between the "realized" range fluctuation and the trading volume is studied. The results show that: 1) the weighted "realized" range fluctuation has small variance, which satisfies the unbiased and validity of the fluctuation estimator, and basically accords with the normal distribution after logarithmic treatment, and has good statistical properties. (2) there is no Granger relationship between the fluctuation of high-frequency data and trading volume in Shenzhen Composite Index, while the fluctuation and trading volume of 5-minute high frequency data in Shanghai Composite Index are mutual Granger reasons. This shows that the relationship between volume and price is not stable, especially in emerging capital markets, many investors are blind investment, there is herd mentality. Thirdly, the VAR model is constructed for the 5-minute high frequency data of Shanghai Composite Index, which proves that there is a linkage between volatility and trading volume. The model explains the aggregation of intraday volatility, and the fluctuation of trading volume causes price volatility. At the same time, the volatility will also feed back to the trading volume, and then affect the change of trading volume.
【學(xué)位授予單位】：湖南師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F832.51;F224

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本文編號：1381259