【摘要】：市場(chǎng)經(jīng)濟(jì)不斷發(fā)展,人們生活中必不可少的就是投資理財(cái),隨著市場(chǎng)經(jīng)濟(jì)的日趨發(fā)展以及受?chē)?guó)外投資策略的影響,人們投資理財(cái)意識(shí)也不斷提高,人們總是希望通過(guò)投資理財(cái)獲得高于銀行利率的收益,但是投資有風(fēng)險(xiǎn),其實(shí)金融市場(chǎng)是有規(guī)律可循的,只要能夠合理地測(cè)度金融風(fēng)險(xiǎn),就可以一定程度上規(guī)避風(fēng)險(xiǎn),從而減少一些不必要的損失。因此進(jìn)行有效的金融監(jiān)管具有重要的現(xiàn)實(shí)意義。金融資產(chǎn)的風(fēng)險(xiǎn)管理是金融監(jiān)管的重要組成部分,要想進(jìn)行有效的金融監(jiān)管必須做好金融風(fēng)險(xiǎn)管理工作。 金融時(shí)序數(shù)據(jù)多數(shù)表現(xiàn)出不穩(wěn)定的特點(diǎn),資產(chǎn)收益率存在一定的波動(dòng)性,可以用波動(dòng)性來(lái)衡量資產(chǎn)的風(fēng)險(xiǎn)。這種波動(dòng)呈現(xiàn)一種趨勢(shì)：幅度較大的波動(dòng)會(huì)相對(duì)聚集在某一段時(shí)間里,而幅度較小的波動(dòng)會(huì)聚集在另一段時(shí)間里。本文針對(duì)金融資產(chǎn)的這種特性,運(yùn)用MCRR方法研究我國(guó)股市風(fēng)險(xiǎn),樣本選取的是2008年1月到2013年3月上證指數(shù)和深圳成分指數(shù)日收益率。 本文共分為五個(gè)部分。第一部分是本文的引言部分,主要說(shuō)明本文的研究背景和研究意義、文獻(xiàn)綜述、研究思路及本文的創(chuàng)新與不足之處；第二部分介紹有關(guān)的模型理論知識(shí),包括ARCH族模型(ARCH、GARCH、TGARCH、 EGARCH等)的具體含義和作用,還有測(cè)度風(fēng)險(xiǎn)的兩種方法——VaR和MCRR方法,分別介紹了兩者的定義、計(jì)算方法和檢驗(yàn)方法；第三部分建立了各種GARCH模型,主要是為了測(cè)度風(fēng)險(xiǎn)做準(zhǔn)備,包括數(shù)據(jù)的描述性統(tǒng)計(jì)分析、平穩(wěn)性檢驗(yàn)、自相關(guān)檢驗(yàn),GARCH族模型的估計(jì)等；第四部分給出了VaR和MCRR方法測(cè)度風(fēng)險(xiǎn)的結(jié)果及檢驗(yàn)；第五部分給出本文的結(jié)論和建議。 本文實(shí)證結(jié)果顯示,與VaR方法相比較,MCRR方法有很多的優(yōu)點(diǎn)。 首先,計(jì)算MCRR的估計(jì)方法更加精確。估計(jì)VaR的三種方法有參數(shù)法、歷史模擬法和蒙特卡羅模擬方法。其中參數(shù)法依賴于收益率分布的假定,歷史模擬法嚴(yán)重依賴歷史數(shù)據(jù),雖然蒙特卡羅模擬方法被認(rèn)為是最全面和靈活的方法,但是該方法的模擬過(guò)程依賴特定的隨機(jī)過(guò)程而不能保證準(zhǔn)確模擬資產(chǎn)價(jià)格變化的過(guò)程,可能會(huì)導(dǎo)致不能準(zhǔn)確地測(cè)度金融風(fēng)險(xiǎn)。運(yùn)用Bootstrap方法計(jì)算MCRR,能夠保證模擬資產(chǎn)價(jià)格變化的隨機(jī)性,尤其能夠考慮到金融時(shí)序數(shù)據(jù)的厚尾特征,從而準(zhǔn)確測(cè)度金融風(fēng)險(xiǎn)。 其次,MCRR方法不僅能夠測(cè)度風(fēng)險(xiǎn)的大小還能給出風(fēng)險(xiǎn)的范圍。 最后,MCRR方法的優(yōu)勢(shì)還體現(xiàn)在GARCH模型上。從計(jì)算VaR的各種GARCH模型發(fā)現(xiàn),這些模型都沒(méi)有考慮模型中存在的“過(guò)度的波動(dòng)持續(xù)性”,當(dāng)把這種特性考慮進(jìn)來(lái)時(shí),即用GARCH-ONV模型模擬金融資產(chǎn)波動(dòng)性,發(fā)現(xiàn)與其他GARCH模型比較,GARCH-ONV模型的衰減系數(shù)較小。關(guān)于風(fēng)險(xiǎn)測(cè)度結(jié)果比較,也發(fā)現(xiàn)GARCH-ONV估計(jì)的風(fēng)險(xiǎn)較小。這些都說(shuō)明了其他GARCH模型中存在的“過(guò)度的波動(dòng)持續(xù)性”,導(dǎo)致風(fēng)險(xiǎn)的高估,從而需要更高的資本要求。所以運(yùn)用GARCH-ONV模型模擬金融資產(chǎn)的波動(dòng)性,進(jìn)行風(fēng)險(xiǎn)測(cè)度更準(zhǔn)確。 因此,本文建議使用MCRR方法測(cè)度金融資產(chǎn)風(fēng)險(xiǎn)。進(jìn)行有效的金融風(fēng)險(xiǎn)管理能夠?yàn)榻?jīng)濟(jì)主體提供一個(gè)安全穩(wěn)定的經(jīng)營(yíng)環(huán)境,從而促進(jìn)經(jīng)濟(jì)發(fā)展；進(jìn)行有效的金融風(fēng)險(xiǎn)管理能夠減少經(jīng)濟(jì)危機(jī)的發(fā)生,有利于社會(huì)的穩(wěn)定。
[Abstract]:With the development of the market economy, people's life is essential to the investment and financing. With the development of the market economy and the influence of the foreign investment strategy, people's investment and financial management consciousness is also rising, and people always want to obtain the income higher than the bank interest rate through the investment finance, But the investment has the risk, in fact, the financial market is regular, so long as the financial risk can be measured reasonably, the risk can be avoided to a certain extent, so that some unnecessary losses can be reduced. Therefore, effective financial supervision is of great practical significance. The risk management of financial assets is an important part of financial supervision. Most of the financial time sequence data shows the characteristics of the instability, the rate of return of the assets has a certain volatility, and the wind of the assets can be measured with the volatility. Insurance. This kind of fluctuation presents a tendency: a large wave of amplitude will be relatively concentrated in a certain period of time, while the smaller amplitude will gather for another period of time In the light of this characteristic of financial assets, this paper uses the MCRR method to study the stock market risk in China. The samples are selected from January 2008 to March 2013 and the Shenzhen component index daily income. Rate. This article is divided into five. The first part is the introduction part of this paper, which mainly explains the research background and research significance, the literature review, the research thinking and the innovation and the deficiency of this paper. The second part introduces the relevant model theory, including ARCH, GARCH, TGA. The specific meaning and function of RCH, EGARCH, etc., and two methods of measure risk, VaR and MCRR method, are introduced in this paper. The definition, calculation method and test method of the two are introduced. The third part has set up a variety of GARCH models, mainly for the preparation of the measure risk, including the descriptive system of data. The fourth part gives the results and tests of the measure risk of the VaR and the MCRR method, and the fifth part gives the conclusion of this paper. The empirical results of this paper show that the MCRR method can be compared with the VaR method. A lot of advantages. First, calculate the estimate of the MCRR The method is more accurate. Three methods of estimating the VaR have the parameter method, the history simulation method and the control method. The Monte Carlo simulation method, in which the parameter method relies on the assumption that the yield distribution is distributed, the historical simulation method is heavily dependent on the historical data, although the Monte Carlo simulation method is considered the most complete Surface and flexible methods, but the simulation process of the method relies on a particular random process to ensure that the process of accurately simulating the change in the asset price may lead to an inability to accurately The financial risk is measured. The MCRR is calculated by the Bootstrap method, which can guarantee the randomness of the change of the price of the simulated asset, especially the thick-tail feature of the financial time sequence data can be taken into account. Second, the MCRR method can not only measure the size of the risk The scope of the risk is also given. Finally, the advantage of the MCRR method also The GARCH model has not taken into account the "over-fluctuation persistence" present in the model. The GARCH-ONV model is used to model the volatility of the financial assets, and the GARCH-O model is found to be compared with other GARCH models. The attenuation coefficient of the NV model is small. As for the comparison of the risk measure results, GARCH is also found. -The risk of the ONV estimate is small. These all account for the "over-fluctuation persistence" present in other GARCH models, resulting in an overestimation of the risk, Therefore, the GARCH-ONV model is used to model the fluctuation of the financial assets. The risk measure is more accurate. Therefore, it is recommended to use M The CRR method measures the risk of financial assets. Effective financial risk management can provide a safe and stable operating environment for the economic subject, thus promoting economic development, and carrying out effective financial risk management to reduce economic risk
【學(xué)位授予單位】：東北財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類(lèi)號(hào)】：F832.51;F224

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