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  本文關(guān)鍵詞：CVaR和CES的局部線性估計(jì)的模擬研究與實(shí)證分析　出處：《廣西師范大學(xué)》2014年碩士論文　論文類(lèi)型：學(xué)位論文

  更多相關(guān)文章： CVaR CES 局部線性估計(jì) N-W估計(jì)

【摘要】：隨著經(jīng)濟(jì)全球化的進(jìn)程加快,人們逐漸意識(shí)到在獲得更大的機(jī)遇的同時(shí),風(fēng)險(xiǎn)必然隨之加劇。于是乎,越來(lái)越多的人們開(kāi)始重視這個(gè)問(wèn)題——如何度量甚至是控制風(fēng)險(xiǎn)?國(guó)內(nèi)外,許多的學(xué)者開(kāi)始了這方面的研究,1994年,Morgan投資銀行在"Risk metrics"的系統(tǒng)中最早提出VaR技術(shù),因?yàn)樗�具有的多方面的�?yōu)勢(shì),慢慢的被大家所接受,到目前為止,VaR方法作為一種國(guó)際性經(jīng)融風(fēng)險(xiǎn)管控指標(biāo),成為了更多企業(yè)必不可少的風(fēng)險(xiǎn)管理工具。 風(fēng)險(xiǎn)價(jià)值VaR是一種重要的金融風(fēng)險(xiǎn)度量指標(biāo),近期有很多關(guān)于動(dòng)態(tài)VaR以及條件VaR(CVaR)等方面的研究。本文介紹了國(guó)內(nèi)外對(duì)VaR的研究,以及CVaR對(duì)VaR的改進(jìn),隨后介紹了三種選擇窗寬的方法：Silverman的大拇指法則、極大光滑原則和交叉驗(yàn)證法。提出用一種新的非參數(shù)估計(jì)--局部線性估計(jì)對(duì)條件風(fēng)險(xiǎn)價(jià)值CVaR和期望損失ES(expected shortfall)進(jìn)行估計(jì),并與N-W估計(jì)進(jìn)行對(duì)比,對(duì)比不同方法不同估計(jì)值與真值之間的誤差,發(fā)現(xiàn)局部線性估計(jì)優(yōu)于N-W核估計(jì)。在模擬研究中,通過(guò)Silverman大拇指法則選擇窗寬,用R軟件編寫(xiě)程序,進(jìn)行隨機(jī)數(shù)生成樣本,計(jì)算CVaR和CES的估計(jì)值,用列表展現(xiàn)出不同的置信水平P值和X的情況下,CVaR和CES的變化。最后,在實(shí)證研究中,選取上證指數(shù)和滬深300指數(shù)數(shù)據(jù)(樣本期為2010年3月29日～2011年1月20日)為研究對(duì)象,先用ADF檢驗(yàn)序列,發(fā)現(xiàn)上證指數(shù)序列和滬深300指數(shù)序列一階差分后的序列不存在單位根,所以該序列都是一階單整序列。 最后,用局部線性估計(jì)的方法計(jì)算了股票市場(chǎng)數(shù)據(jù)所隱含的CVaR和CES.無(wú)論是滬深300指數(shù),還是上證指數(shù),利用非參數(shù)局部線性估計(jì)估計(jì)得到的風(fēng)險(xiǎn)波動(dòng)函數(shù),都呈現(xiàn)U型,即所謂的“波動(dòng)率微笑”現(xiàn)象,這可以看成是一種變異風(fēng)險(xiǎn)度量,有著隨r波動(dòng)的特性,容易分析并且直觀。對(duì)于缺乏概率統(tǒng)計(jì)相關(guān)知識(shí)的一般投資者來(lái)說(shuō),所使用的風(fēng)險(xiǎn)度量指標(biāo)——標(biāo)準(zhǔn)差的概念,分析起來(lái)并不直觀,也不容易被解釋、認(rèn)同。無(wú)論是CVaR或者CES,估計(jì)值的圖形都呈現(xiàn)U型,正好對(duì)應(yīng)于所謂的“波動(dòng)率微笑”。當(dāng)風(fēng)險(xiǎn)傾向降低,上證指數(shù)的滯后損失值將會(huì)慢慢趨向于經(jīng)驗(yàn)平均值。這些結(jié)果對(duì)股票市場(chǎng)風(fēng)險(xiǎn)評(píng)價(jià)有一定的參考價(jià)值。
[Abstract]:With the acceleration of the process of economic globalization, people are gradually realizing that while getting more opportunities, the risks will inevitably increase. More and more people are beginning to pay attention to this question-how to measure and even control risk? At home and abroad, many scholars began to study this aspect. In 1994, Morgan Investment Bank first put forward VaR technology in the system of "Risk metrics". Because it has many advantages, gradually accepted by everyone, so far VaR method as an international financial risk management index, has become an essential risk management tool for more enterprises. Value of risk (VaR) is an important measure of financial risk. Recently, there are many researches on dynamic VaR and conditional VaR Cvar. This paper introduces the research of VaR at home and abroad, and the improvement of VaR by CVaR. Then three methods of selecting window width: Silverman's thumb rule are introduced. Maximum smoothness principle and cross validation method. A new nonparametric estimator, local linear estimator, is proposed for conditional risk value (CVaR) and expected loss ES( s). Expected shortfall. By comparing with N-W estimation and comparing the error between different estimators and true values of different methods, it is found that local linear estimation is better than N-W kernel estimation. The window width is selected by the Silverman thumb rule, and the program is written with R software. The samples are generated by random numbers, and the estimated values of CVaR and CES are calculated. Show the change of Cvar and CES in the case of P and X with different confidence levels. Finally, in the empirical study. The data of Shanghai Stock Exchange Index and Shanghai and Shenzhen 300 Index (sample period from March 29th 2010 to January 20th 2011) were selected as the research object, and the ADF test sequence was used first. It is found that there is no unit root in the sequence after the first order difference between the Shanghai stock index sequence and the Shanghai and Shenzhen 300 index sequence, so the sequence is single integer sequence of the first order. Finally, the implicit CVaR and CESs of stock market data are calculated by using the method of local linear estimation, whether the CSI 300 index or the Shanghai Stock Exchange index. All the risk fluctuation functions obtained by using non-parametric local linear estimators are U-shaped, that is, the so-called "volatility smile" phenomenon, which can be regarded as a variation risk measure with the characteristic of fluctuation with r. It is easy to analyze and intuitionistic. For the general investors who lack the relevant knowledge of probability and statistics, the concept of standard deviation, which is used as a risk measure, is not intuitively analyzed and can not be easily explained. Agree. Regardless of whether it is CVaR or CES, the figure of the estimate is U-shaped, which corresponds to the so-called "volatility smile." when the risk propensity decreases. The lag loss value of Shanghai Stock Exchange Index will gradually tend to the empirical average. These results have certain reference value for stock market risk evaluation.
【學(xué)位授予單位】：廣西師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：O212.7;F830.91

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