本文選題：ARMA-GARCH模型 + 國債指數(shù)　； 參考：《合肥工業(yè)大學》2012年碩士論文

【摘要】：隨著歐債危機的爆發(fā)，很多經(jīng)濟學家和計量統(tǒng)計學家開始將研究的目光轉向國債市場。國債，是一個國家信用的體現(xiàn)，具有彰顯國家公信力的價值。那么，使用計量統(tǒng)計學工具對于國債市場的走勢進行量化的數(shù)據(jù)分析，并進行預測，以達到風險控制的目的，將會是非常有意義的課題。 本文主要是使用ARCH類模型族研究我國的國債指數(shù)收益率序列，通過研究我們發(fā)現(xiàn)，我國的國債指數(shù)收益率序列由于其數(shù)據(jù)本身聯(lián)動的慣性和相對于經(jīng)濟、政策的滯后性，，會呈現(xiàn)出一定的序列相關，所以本文采用ARMA模型來描述國債收益率序列，GARCH模型用來擬合誤差。結合考慮金融數(shù)據(jù)本身所具有的尖峰厚尾及異方差性，以及投資者對于投資風險的承受能力所體現(xiàn)出的有偏性，本文對其收益率序列建立誤差分布為正態(tài)，GED和t分布的ARMA-GARCH模型，這樣更符合實際，研究效果更好。隨后，本文嘗試使用交叉驗證的方法用ARMA-GARCH模型對國債指數(shù)的走勢進行預測，與已有研究相比，也取得了較好的研究結果。本文的全文內(nèi)容將分成以下五個部分： 第一章對本文的研究背景, ARCH類模型國內(nèi)外的研究情況進行簡要概述，并提出本文的研究目的和分析方法。 第二章對涉及到的ARCH類模型的結構進行簡要概述，其中包括對基于不同誤差分布下ARMA-GARCH模型的介紹。 第三章利用EViews5.1軟件對上證國債指數(shù)日收益率序列的尖峰厚尾、有偏性、自相關性、平穩(wěn)性、和異方差性等特性進行基本統(tǒng)計分析，以確定合適的分析模型。 第四章依據(jù)AIC準則進行參數(shù)估計以確定ARMA(p,q)-GARCH(r,s)的參數(shù)，從而可以選取合理的ARCH類模型對國債收益率序列進行擬合，同時使用交叉驗證的方法對國債收益率序列進行預測，最后對基于不同誤差分布下模型的擬合與預測效果進行比較，找出相對更適合于進行國債指數(shù)研究的模型。 第五章研究的結論。
[Abstract]:With the outbreak of the European debt crisis, many economists and statisticians are turning their attention to the bond market. National debt, is the embodiment of a national credit, with the value of highlighting the credibility of the country. Therefore, it will be a very meaningful subject to use econometric statistical tools to analyze and forecast the trend of the national debt market to achieve the purpose of risk control. In this paper, we mainly use the ARCH model family to study the national debt index yield series of our country. Through the study, we find that the series of the national debt index yield rate of our country is lagging behind because of the inertia of the data itself and the lag of the policy relative to the economy. So the ARMA model is used to describe the bond yield series and the GARCH model is used to fit the error. Considering the sharp and thick tail and heteroscedasticity of financial data and the bias of investors' ability to bear investment risk, this paper establishes a ARMA-GARCH model with the error distribution of normal GED and t distribution for the return series. This is more in line with the reality, the research results are better. Subsequently, this paper attempts to use cross-validation method to predict the trend of treasury bond index by using ARMA-GARCH model, and better results are obtained compared with the previous research. The full text of this article will be divided into the following five parts: In the first chapter, the research background of this paper, the research situation of ARCH class model at home and abroad are briefly summarized, and the purpose and analysis method of this paper are put forward. Chapter 2 gives a brief overview of the structure of the ARCH class model, including the introduction of the ARMA-GARCH model based on different error distributions. In chapter 3, we use EViews5.1 software to analyze the characteristics of the sharp, thick tail, bias, autocorrelation, stationarity and heteroscedasticity of the daily yield series of Shanghai Treasury bond index, so as to determine the appropriate analysis model. In chapter 4, we estimate the parameters according to the AIC criterion to determine the parameters of ARMA-PQ / GARCHRN), so that we can select a reasonable ARCH model to fit the yield series of treasury bonds, and use the method of cross-validation to predict the yield series of treasury bonds, at the same time, we can use the method of cross-validation to predict the yield series of treasury bonds. Finally, the fitting and forecasting results of the model based on different error distribution are compared, and the model which is more suitable for the research of national debt index is found out. The fifth chapter is the conclusion of the research.
【學位授予單位】：合肥工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：F224;F812.5

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