國債收益率曲線的動態(tài)估計與預(yù)測
本文選題:國債的利率期限結(jié)構(gòu) + Diebold-Li模型 ; 參考:《華中科技大學(xué)》2013年碩士論文
【摘要】:收益率曲線是在某一固定時點上,不同期限下的收益率與其相應(yīng)的期限之間的圖形關(guān)系。它所對應(yīng)的函數(shù)關(guān)系便是我們通常所熟知的利率期限結(jié)構(gòu)。國債的收益率往往被視為無風(fēng)險利率,是一切金融產(chǎn)品收益水平計算和衡量的基準(zhǔn)。同時,國債收益率的影響現(xiàn)如今已經(jīng)擴(kuò)展到了金融市場之外。短期利率已然成為各國央行貨幣政策工具箱的香餑餑,它不僅是傳遞中央銀行貨幣政策的主要媒介,,更是央行調(diào)控通脹,干預(yù)宏觀經(jīng)濟(jì)的利器。 因而,本文的研究落腳于利率期限結(jié)構(gòu)的動態(tài)估計與預(yù)測。我們在總結(jié)現(xiàn)有動態(tài)利率期限結(jié)構(gòu)估計方法的前提下,引入了動態(tài)因子模型作為分析框架。在這一框架下,我們將靜態(tài)估計中的短,中,長期三項的待估計參數(shù)分別解釋為推動收益率曲線變動的水平因子,斜率因子和曲度因子。我們的實證研究表明在動態(tài)因子模型分析框架下的這些因子無論在樣本內(nèi)對收益率的擬合效果,還是在樣本外預(yù)測的均方根差(RMSE)上都有優(yōu)異表現(xiàn)。在估計上,我們通過對傳統(tǒng)模型的部分參數(shù)事先假定,大大簡化了因子提取的估計方法。我們的主要結(jié)論有Dynamic Svensson模型在樣本內(nèi)對收益率曲線的擬合能力全面優(yōu)于Diebold-Li模型,但是在樣本外預(yù)測上,Diebold-Li模型在提前六個月的預(yù)測上表現(xiàn)要優(yōu)于Dynamic Svensson模型。此外,對因子設(shè)定的動態(tài)過程對于預(yù)測結(jié)果具有較為明顯影響。
[Abstract]:The yield curve is the graphic relationship between the yield and its corresponding term at a fixed time point.The corresponding function is the term structure of interest rate.Treasury yields are often seen as risk-free interest rates and a benchmark for the calculation and measurement of yield levels for all financial products.At the same time, the impact of bond yields has now extended beyond financial markets.Short-term interest rate has become a hot spot in the monetary policy toolbox of central banks. It is not only the main medium for transmitting monetary policy of central banks, but also a sharp weapon for central banks to control inflation and intervene in macro economy.Therefore, the research of this paper is based on the dynamic estimation and prediction of interest rate term structure.On the premise of summing up the existing methods of estimating the term structure of dynamic interest rate, we introduce the dynamic factor model as the analytical framework.In this framework, we interpret the three parameters to be estimated in static estimation as horizontal factor, slope factor and curvature factor, respectively.Our empirical study shows that these factors in the framework of dynamic factor model analysis have excellent performance both in the fitting effect of the return rate in the sample and in the root-mean-square difference (RMSE) predicted outside the sample.In terms of estimation, we presuppose some parameters of the traditional model, which greatly simplifies the estimation method of factor extraction.Our main conclusion is that Dynamic Svensson model is superior to Diebold-Li model in fitting yield curve in sample, but Diebold-Li model is superior to Dynamic Svensson model in predicting six months ahead of sample.In addition, the dynamic process of factor setting has a significant effect on the prediction results.
【學(xué)位授予單位】:華中科技大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2013
【分類號】:F832.51;F224
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