【摘要】：利率是指一定時(shí)期內(nèi)利息額與本金的比率,是各種金融資產(chǎn)定價(jià)的基礎(chǔ),同時(shí)也是國(guó)家進(jìn)行宏觀調(diào)控的重要指標(biāo)之一。利率期限結(jié)構(gòu)是指無(wú)風(fēng)險(xiǎn)的國(guó)債收益率與到期期限之間的關(guān)系,反應(yīng)的是宏觀經(jīng)濟(jì)中長(zhǎng)短期資金的供求關(guān)系。同時(shí),利率期限結(jié)構(gòu)與許多宏觀經(jīng)濟(jì)變量的聯(lián)系緊密,兩者之間的研究一直是金融領(lǐng)域的熱點(diǎn)之一。本文首先對(duì)利率期限結(jié)構(gòu)的相關(guān)理論進(jìn)行綜述,包括利率期限結(jié)構(gòu)的形成理論、利率期限結(jié)構(gòu)擬合模型的發(fā)展以及利率期限結(jié)構(gòu)和主要宏觀經(jīng)濟(jì)變量之間的關(guān)系研究。在此基礎(chǔ)上本文以中國(guó)銀行間國(guó)債利率期限結(jié)構(gòu)為中心展開,以Nelson-Siegel模型為工具對(duì)我國(guó)銀行間國(guó)債的利率期限結(jié)構(gòu)進(jìn)行了擬合實(shí)證分析,得到NS模型的水平、斜率和曲度三因子。在得到模型三因子后,本文對(duì)三因子序列進(jìn)行了進(jìn)一步的分析。第一步對(duì)模型所得的三因子與傳統(tǒng)利率期限結(jié)構(gòu)的代理變量進(jìn)行對(duì)比,分析兩者之間的異同點(diǎn);第二步用一階自回歸模型分別對(duì)所得的三因子序列進(jìn)行模型擬合得到未來(lái)的預(yù)測(cè)值,并對(duì)預(yù)測(cè)值的擬合效果進(jìn)行評(píng)估;第三步運(yùn)用隱馬爾科夫模型對(duì)利率期限結(jié)構(gòu)的狀態(tài)轉(zhuǎn)換特征進(jìn)行了研究;最后運(yùn)用線性回歸模型對(duì)宏觀經(jīng)濟(jì)變量對(duì)收益率曲線的影響進(jìn)行了研究分析。本文的主要結(jié)論有:第一,靜態(tài)擬合模型Nelson-Siegel模型能夠擬合我國(guó)銀行間國(guó)債不同形狀的利率期限結(jié)構(gòu);第二,用NS模型估計(jì)出的水平因子、斜率因子以及曲度因子與傳統(tǒng)利率期限結(jié)構(gòu)的代理變量具有較強(qiáng)的相關(guān)性,因此三因子具有明確的經(jīng)濟(jì)意義;第三,一階自回歸模型能夠較好地預(yù)測(cè)短期內(nèi)的利率期限結(jié)構(gòu),而隨著預(yù)測(cè)時(shí)間的延長(zhǎng),模型的預(yù)測(cè)效果逐漸變差;第四,HMM模型(狀態(tài)數(shù)為2)結(jié)果顯示我國(guó)銀行間利率期限結(jié)構(gòu)在短期存在著狀態(tài)轉(zhuǎn)換,且主要表現(xiàn)為收益率曲線傾斜度的變化,兩個(gè)狀態(tài)下的斜率因子均值分別為-1.87和-3.35。最后,NS模型三因子與本文所選宏觀經(jīng)濟(jì)變量的線性回歸模型結(jié)果顯示:雖然GDP和CPI與利率期限結(jié)構(gòu)的水平因子具有顯著的相關(guān)性,但是線性回歸模型結(jié)果顯示GDP和CPI對(duì)利率期限結(jié)構(gòu)的水平因子的影響非常輕微;GDP、CPI與銀行間隔夜拆借利率與斜率因子都具有顯著的相關(guān)性,根據(jù)線性回歸模型結(jié)果顯示銀行間隔夜拆借利率對(duì)利率期限結(jié)構(gòu)的斜率因子具有非常明顯的影響,當(dāng)銀行間隔夜拆借利率上升,即貨幣政策由寬松變?yōu)榫o縮時(shí),斜率因子值變大,傾斜度減小,CPI對(duì)斜率因子也有明顯的影響,CPI的增長(zhǎng)會(huì)同樣會(huì)使利率期限結(jié)構(gòu)的傾斜度減小,而GDP對(duì)斜率因子只有輕微的影響;曲度因子與GDP、CPI和貨幣政策之間不存在顯著的相關(guān)性,因此無(wú)法建立相關(guān)的線性回歸模型。
[Abstract]:Interest rate refers to the ratio of interest to principal in a certain period of time, which is the basis of pricing various financial assets, and is also one of the important indicators of macroeconomic regulation and control. The term structure of interest rate is closely related to many macroeconomic variables, and the research between them has been one of the hot topics in the financial field. Firstly, this paper reviews the related theories of term structure of interest rate, including the formation theory of term structure of interest rate, the development of term structure fitting model, the term structure of interest rate and the main macro-economy. On this basis, this paper takes the term structure of interest rate of Chinese interbank treasury bonds as the center, uses Nelson-Siegel model as a tool to fit the empirical analysis of the term structure of interest rate of Chinese interbank Treasury bonds, and obtains the level, slope and curvature of NS model. This paper makes a further analysis of the three-factor series. The first step is to compare the three factors obtained by the model with the proxy variables of the traditional term structure of interest rates, and analyze the similarities and differences between the two. The second step is to use the first-order autoregressive model to fit the three-factor series to get the future forecast value, and the forecast value. The third step is to use Hidden Markov Model (HMM) to study the state transition characteristics of term structure of interest rate. Finally, we use linear regression model to analyze the impact of macroeconomic variables on the yield curve. Secondly, the level factor, slope factor and curvature factor estimated by NS model have strong correlation with the proxy variables of traditional interest rate term structure, so the three factors have clear economic significance; thirdly, the first-order autoregressive model can better predict the short-term interest rate structure. Fourthly, the HMM model (state number 2) results show that there is a short-term state transition in the term structure of interest rates in China, and the main performance is the change of the slope of the yield curve, the slope factor mean values in the two states are - 1.87 and - 1.87 respectively. Finally, the linear regression model of NS model and macroeconomic variables selected in this paper shows that although GDP and CPI have significant correlation with the level of interest rate term structure, the linear regression model shows that GDP and CPI have very slight impact on the level of interest rate term structure factors; GDP, CPI and bank spacing. There is a significant correlation between the night lending rate and the slope factor. According to the linear regression model, the bank overnight lending rate has a very significant effect on the slope factor of the term structure of interest rate. When the bank overnight lending rate rises, that is, when the monetary policy changes from loose to tight, the slope factor increases and the slope decreases. CPI also has a significant impact on the slope factor, the growth of CPI will also reduce the slope of interest rate term structure, while GDP has only a slight impact on the slope factor; curvature factor has no significant correlation with GDP, CPI and monetary policy, so it is impossible to establish a relevant linear regression model.
【學(xué)位授予單位】：浙江財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F224;F822.0

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