本文選題：“已實(shí)現(xiàn)”波動(dòng)率　切入點(diǎn)：Realized　出處：《天津商業(yè)大學(xué)》2017年碩士論文

【摘要】：自改革開(kāi)放以來(lái),隨著市場(chǎng)機(jī)制的不斷完善,我國(guó)資本市場(chǎng)有了較大的發(fā)展。作為國(guó)有企業(yè)改革的主要途徑,股票市場(chǎng)已經(jīng)成為國(guó)有企業(yè)進(jìn)行機(jī)制改革和融資的重要場(chǎng)所。股票市場(chǎng)不僅在推動(dòng)國(guó)民經(jīng)濟(jì)持續(xù)增長(zhǎng)上發(fā)揮了不可替代的作用,同時(shí)也對(duì)世界經(jīng)濟(jì)一體化影響巨大。與傳統(tǒng)的市場(chǎng)相比,股票市場(chǎng)是充滿(mǎn)了不確定性的市場(chǎng),信息的披露、資本的流動(dòng)會(huì)導(dǎo)致股票市場(chǎng)的價(jià)格出現(xiàn)波動(dòng),使投資者們對(duì)其難以把控。劇烈的股票價(jià)格波動(dòng)增加了投資者的投資風(fēng)險(xiǎn),會(huì)給投資者們帶來(lái)?yè)p失。因此,對(duì)股票市場(chǎng)價(jià)格波動(dòng)的研究是十分重要且十分有意義的。本文使用數(shù)理工具和計(jì)量方法,對(duì)我國(guó)的證券市場(chǎng)特征進(jìn)行描述和預(yù)測(cè),揭示其內(nèi)在規(guī)律。通過(guò)對(duì)股票價(jià)格波動(dòng)率的建模分析,加深對(duì)股票價(jià)格波動(dòng)實(shí)質(zhì)的認(rèn)識(shí),把握未來(lái)股票市場(chǎng)的趨勢(shì),同時(shí)發(fā)現(xiàn)我國(guó)股票市場(chǎng)有可能存在的問(wèn)題,并提出相應(yīng)的改進(jìn)措施。再進(jìn)一步,通過(guò)理論結(jié)果與現(xiàn)實(shí)結(jié)果相比較,發(fā)現(xiàn)理論與實(shí)際不一致的地方,進(jìn)而對(duì)所使用的模型可能存在的缺陷進(jìn)行改進(jìn)。其中,在對(duì)收益率的描述性統(tǒng)計(jì)分析中,除了對(duì)其主要指標(biāo)包括均值、標(biāo)準(zhǔn)差、偏度、峰度的分析外,還發(fā)現(xiàn)其波動(dòng)具有聚集性和周期性。從結(jié)果中可以看出,收益率序列呈現(xiàn)了尖峰厚尾的特征。在對(duì)“已實(shí)現(xiàn)”測(cè)度進(jìn)行比較時(shí),不同頻率所得到的“已實(shí)現(xiàn)”方差也呈現(xiàn)出不同的特征,時(shí)間間隔越小,頻率越大,序列的均值就越小。其中,5分鐘時(shí)間間隔下的“已實(shí)現(xiàn)”方差與“已實(shí)現(xiàn)”核估計(jì)的各項(xiàng)特征十分接近。收益率序列的波動(dòng)具有聚集性,即在一個(gè)較大幅度的波動(dòng)后會(huì)跟隨著另一個(gè)較大幅度的波動(dòng),在一個(gè)較小幅度的波動(dòng)后也同樣會(huì)跟隨另一個(gè)較小幅度的波動(dòng)。而其周期性,主要體現(xiàn)在與宏觀(guān)經(jīng)濟(jì)周期相吻合。在Skewed-T Realized GARCH模型的實(shí)證分析中,我們通過(guò)模型對(duì)數(shù)據(jù)的擬合優(yōu)度進(jìn)行比較,確立了最佳的模型滯后階數(shù)和最優(yōu)分布,同時(shí)也利用信息沖擊曲線(xiàn)等工具,分析了波動(dòng)的非對(duì)稱(chēng)效應(yīng)。在對(duì)模型的預(yù)測(cè)能力的分析上,通過(guò)與SkewedNormal Realized GARCH和傳統(tǒng)EGARCH模型的比較分析,分別從樣本內(nèi)預(yù)測(cè)和樣本外預(yù)測(cè)兩個(gè)方面驗(yàn)證了Skewed-T Realized GARCH的優(yōu)越性。Skewed-T Realized GARCH模型的優(yōu)越之處在于新引入的“已實(shí)現(xiàn)”測(cè)度,而其原因在于波動(dòng)率本身是劇烈波動(dòng)的,而傳統(tǒng)的EGARCH模型在收益率層面上是一個(gè)簡(jiǎn)單的ARMA過(guò)程,對(duì)于迅速變動(dòng)的波動(dòng)率序列擬合能力弱。而“已實(shí)現(xiàn)”測(cè)度可以對(duì)日內(nèi)波動(dòng)率的變動(dòng)做出迅速的反應(yīng),使得參與擬合的序列能夠包含日內(nèi)波動(dòng)率變化的信息。
[Abstract]:Since the reform and opening up, with the continuous improvement of the market mechanism, China's capital market has developed greatly. The stock market has become an important place for state-owned enterprises to carry out mechanism reform and financing. The stock market has not only played an irreplaceable role in promoting the sustained growth of the national economy. Compared with the traditional market, the stock market is full of uncertainty. The disclosure of information and the flow of capital will lead to the fluctuation of the price of the stock market. Make it difficult for investors to control. Sharp stock price fluctuations increase investors' investment risk and bring losses to investors. It is very important and meaningful to study the price fluctuation of stock market. In this paper, we use mathematical tools and measurement methods to describe and predict the characteristics of securities market in China. Through modeling and analyzing the volatility rate of stock price, we can deepen the understanding of the essence of the fluctuation of stock price, grasp the trend of stock market in the future, and find out the possible problems in the stock market of our country at the same time. And put forward the corresponding improvement measures. Further, by comparing the theoretical results with the practical results, we find that the theory is inconsistent with the practice, and then improve the possible defects of the model used. In the descriptive statistical analysis of the return rate, in addition to the analysis of the mean, standard deviation, deviation and kurtosis, it is also found that the volatility has aggregation and periodicity. When comparing the "realized" measure, the "realized" variance obtained from different frequencies also shows different characteristics. The smaller the time interval, the greater the frequency. The smaller the mean value of the sequence is, the closer the realized variance is to the kernel estimation at 5-minute intervals, and the volatility of the return series is convergent. That is, it follows another larger fluctuation after one larger fluctuation, and also follows another smaller fluctuation after one smaller fluctuation, and its periodicity, In the empirical analysis of the Skewed-T Realized GARCH model, we compare the goodness of fit of the data, and establish the best model lag order and optimal distribution. At the same time, the asymmetric effect of volatility is analyzed by means of information shock curve. The prediction ability of the model is compared with that of SkewedNormal Realized GARCH and traditional EGARCH model. The superiority of Skewed-T Realized GARCH in Skewed-T Realized GARCH model is verified from two aspects of intra-sample prediction and out-of-sample prediction, respectively. The advantage of Skewed-T Realized GARCH model lies in the newly introduced "realized" measure, and the reason is that volatility itself is highly fluctuating. On the other hand, the traditional EGARCH model is a simple ARMA process at the return level, which is weak for the rapidly changing volatility series, and the "realized" measure can react rapidly to the intraday volatility changes. So that the series involved in the fitting can contain information about intraday volatility changes.
【學(xué)位授予單位】：天津商業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：F832.51;F224

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