本文關(guān)鍵詞： Copula函數(shù) 尾部相關(guān)系數(shù) 廣義Pareto分布 VaR　出處：《天津財經(jīng)大學》2012年碩士論文　論文類型：學位論文

【摘要】：當前,隨著我國經(jīng)濟持續(xù)穩(wěn)定的發(fā)展,財政收入快速增長,財政政策的宏觀調(diào)控作用也不斷增強,國家的各項基礎(chǔ)設(shè)施建設(shè)取得了重大成就。但同時,我國的財政風險問題也逐漸顯現(xiàn)出來。國家財政支出壓力越來越大,國債發(fā)行規(guī)模不斷擴大,尤其是地方政府債務(wù)負擔越來越重,這使得我國的財政風險進一步擴大,如何防范財政風險,保持財政的穩(wěn)定性和可持續(xù)性,已經(jīng)成為一個重要性的課題。 當前財政風險問題的研究以定性分析為主,定量分析極少,并且大多數(shù)以財政風險的總體度量指標來衡量中央政府的財政風險,缺少對微觀債券流通市場風險的準確度量。即使有這方面的一些研究,大部分都是用傳統(tǒng)的線性方法對有關(guān)變量的風險相關(guān)性做了分析。然而這樣就導致了一些問題,如正態(tài)分布假設(shè)是否合理?傳統(tǒng)的線性相關(guān)系數(shù)是否能較好地反映變量之間的相依關(guān)系?怎樣才能準確度量出組合變量的風險價值?這些問題的解決對于我國債券市場的風險管理具有重大的意義,進而能夠更加全面的認識我國的財政風險,為財政風險的防范提供一些有用的措施和建議。 本文利用極值理論中的Copula函數(shù)度量了國債市場和企債市場的尾部相關(guān)性風險,并將其與傳統(tǒng)的線性方法得出的相關(guān)系數(shù)進行了對比。得出：傳統(tǒng)的線性相關(guān)系數(shù)低估了市場的非系統(tǒng)性風險,市場中存在著大量的極值風險。接著,將兩個市場收益率序列用廣義Pareto分布進行擬合,采用基于Copula函數(shù)的蒙特卡羅模擬法,計算出不同的資產(chǎn)權(quán)重和置信水平下的市場組合風險價值,即組合VaR (Value at risk).最后,針對我國目前債務(wù)風險的現(xiàn)狀,給出了一些政策建議。
[Abstract]:At present, with the sustained and stable development of China's economy, the rapid growth of fiscal revenue and the increasing macro-control role of fiscal policies, major achievements have been made in the construction of various infrastructure facilities in the country. The problem of fiscal risk in our country is also gradually emerging. The pressure of national financial expenditure is increasing, the scale of national debt issuance is expanding, especially the local government debt burden is becoming heavier and heavier, which makes the financial risk of our country further expand. How to prevent financial risks and maintain financial stability and sustainability has become an important issue. At present, the research of financial risk is mainly qualitative analysis, but the quantitative analysis is rare, and most of them measure the central government's fiscal risk by the overall measure of fiscal risk. There is a lack of accuracy in the market risk of micro-bond circulation. Even with some research in this area, the traditional linear method is used to analyze the risk correlation of the relevant variables. However, this leads to some problems. Is the assumption of normal distribution reasonable? Can the traditional linear correlation coefficient better reflect the dependent relationship between variables? How can we accurately measure the risk value of portfolio variables? The solution of these problems is of great significance to the risk management of our country's bond market, and then we can fully understand the financial risk of our country, and provide some useful measures and suggestions for the prevention of the financial risk. In this paper, we use the Copula function in the extreme value theory to measure the tail correlation risk between the bond market and the enterprise bond market. By comparing it with the correlation coefficient obtained by traditional linear method, it is concluded that the traditional linear correlation coefficient underestimates the non-systemic risk of the market, and there are a lot of extreme risk in the market. Two market yield sequences are fitted with generalized Pareto distribution, and Monte Carlo simulation method based on Copula function is used to calculate the market portfolio risk value under different asset weights and confidence levels, that is, portfolio VaR value at risk.Finally, In view of the present situation of debt risk in China, some policy suggestions are given.
【學位授予單位】：天津財經(jīng)大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：F832.51;F224

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本文編號：1531611