本文關(guān)鍵詞： 時變Copula函數(shù) MCMC方法 債券市場 VaR Monte Carlo模擬　出處：《廣西師范大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：在金融危機背景下,雖然當(dāng)前全球經(jīng)濟緩慢復(fù)蘇,歐洲債務(wù)危機整體形勢也日趨穩(wěn)定,但全球經(jīng)濟和金融市場前景依舊不明朗。相對于我國持續(xù)低迷的股票、基金市場,國內(nèi)債券市場卻在迅速回漲。近年來,我國債券的發(fā)行期數(shù)和規(guī)模均呈現(xiàn)了較快的增長態(tài)勢,然而在日益加劇的金融風(fēng)險背景下,債券價格波動始終是一把雙刃劍。債券市場的風(fēng)險管理已經(jīng)成為金融機構(gòu)和投資者所面臨的最重要問題之一。針對目前我國不斷快速發(fā)展的債券市場以及債券指數(shù)走勢相應(yīng)的逐步轉(zhuǎn)暖,債券組合風(fēng)險的研究就顯得非常具有現(xiàn)實意義。 另一方面,Copula理論的出現(xiàn)并被引入金融研究領(lǐng)域,為彌補傳統(tǒng)風(fēng)險價值度量方面存在的一些缺點和不足提供了一條有效的途徑。在已有的Copula理論和MCMC方法應(yīng)用研究基礎(chǔ)上,鑒于大都單獨采用其中一種方法,而少有把兩種方法結(jié)合起來進行應(yīng)用研究,本文計劃將時變Copula與MCMC方法結(jié)合起來研究我國債券市場風(fēng)險。 論文結(jié)合我國債券市場的實際特點,選取國債和企債指數(shù),對債券投資組合建立了合適的時變Copula-GARCH-t模型,并根據(jù)MCMC方法確定了債券組合相應(yīng)的配置比例,然后計算債券投資組合的VaR。最后與傳統(tǒng)的靜態(tài)常相關(guān)模式下Copula函數(shù)度量VaR進行分析比較,得出的結(jié)論是時變Copula-MCMC方法,不僅在組合配置的穩(wěn)定性和精確度上要優(yōu)于傳統(tǒng)方法,而且能更準(zhǔn)確的量化投資組合的市場風(fēng)險,對投資組合風(fēng)險研究效果有良好的改善,具有科學(xué)性和實效性。 本文的特色主要體現(xiàn)在如下幾個方面： 1.采用GARCH-t模型估計Copula函數(shù)的邊際分布,即單變量債券收益率序列的分布,并且選取時變對稱的Joe-Clayton Copula函數(shù)來描述債券間的相關(guān)結(jié)構(gòu),比較符合現(xiàn)實債券市場變量間相關(guān)性隨時波動的特征。 2.根據(jù)資產(chǎn)收益率勝出的先驗概率,結(jié)合貝葉斯推斷中的MCMC方法確定債券組合的配置比例,在組合配置的精確度和穩(wěn)定性上要優(yōu)于傳統(tǒng)方法。
[Abstract]:In the context of the financial crisis, although the global economy is recovering slowly and the overall situation of the European debt crisis is becoming more stable, the prospects of the global economy and financial markets are still uncertain. In the fund market, the domestic bond market is rising rapidly. In recent years, the number and scale of bond issuance in China have shown a rapid growth trend, but in the context of increasing financial risks. Bond price fluctuation is always a double-edged sword. Risk management in bond market has become one of the most important problems faced by financial institutions and investors. The number of trends corresponding to the gradual warming. The study of bond portfolio risk is of great practical significance. On the other hand, the emergence of Copula theory was introduced into the field of financial research. In order to make up for some shortcomings and shortcomings of traditional risk value measurement, this paper provides an effective way. On the basis of the existing Copula theory and MCMC method application research. In view of the fact that one of the methods is used alone and few of the two methods are combined for application, this paper plans to combine the time-varying Copula method with the MCMC method to study the risk of bond market in China. According to the actual characteristics of the bond market in China, the paper establishes a suitable time-varying Copula-GARCH-t model for the bond portfolio by selecting the bond bond and enterprise bond index. According to the MCMC method, the corresponding allocation ratio of bond portfolio is determined. Then the bond portfolio VaR is calculated. Finally, it is compared with the traditional Copula function metric VaR under the static constant correlation model. The conclusion is that the time-varying Copula-MCMC method is not only superior to the traditional method in the stability and accuracy of portfolio allocation, but also more accurate to quantify the market risk of portfolio. Research on portfolio risk has a good effect, scientific and effective. The main features of this paper are as follows: 1. Using GARCH-t model to estimate the marginal distribution of Copula function, that is, the distribution of univariate bond yield series. Moreover, the time-varying symmetric Joe-Clayton Copula function is used to describe the correlation structure between bonds, which accords with the characteristics of volatility between variables in the real bond market. 2. According to the priori probability of asset yield winning and the MCMC method in Bayesian inference, the allocation ratio of bond portfolio is better than the traditional method in terms of accuracy and stability of portfolio allocation.
【學(xué)位授予單位】：廣西師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F224;F832.51

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