本文關鍵詞：基于組合預測方法的國債利率期限結構實證研究　出處：《東北財經(jīng)大學》2012年碩士論文　論文類型：學位論文

  更多相關文章： 國債利率期限結構 組合預測方法 國債理論定價 擬合優(yōu)度

【摘要】：本文研究的對象是利率期限結構,利率期限結構是指不同期限的利率與該期限之間的關系,它需要用債券的即期利率與其剩余到期期限之間的關系來表示。研究利率期限結構具有重要的理論和實踐意義,它可為確定基準利率提供理論支撐,為債券和金融衍生品的定價提供理論基礎,同時可以為金融風險控制和利率風險管理提供操作依據(jù),有利于設計合理的金融產品,有利于發(fā)現(xiàn)市場中的套利機會,提高金融市場的效率。 利率期限結構相關理論的研究大體經(jīng)歷了傳統(tǒng)的定性研究階段和現(xiàn)代定量精確研究階段。傳統(tǒng)的定性研究大體有預期理論和市場分割理論。后來人們更多的借鑒數(shù)學模型,從而更精確的預測和模擬利率,提出的模型歸納起來主要有逐點遞推法、樣條函數(shù)法和簡約模型法等。 基于不同利率期限結構模型所采用的具體數(shù)學模型不同,因此各模型存在不同的優(yōu)缺點,而實際經(jīng)濟環(huán)境中利率期限結構則復雜多變,這導致各模型對實際利率期限結構的擬合優(yōu)度會出現(xiàn)階段性的波動,不存在擬合優(yōu)度穩(wěn)定不變的單一利率期限結構模型,因此僅采用單一利率期限結構模型對我國利率期限結構進行估計,效果并非最好。為了提高利率的擬合預測效果,本文借助了組合預測方法,組合預測方法是把各種模型組合起來,按模型的擬合優(yōu)度大小分配給各模型適當?shù)臋嘀?擬合優(yōu)度高的模型會分配給較大的權重,從而分散單一預測模型的不確定性,以提高預測整體的精確度和穩(wěn)定性。 本文對各利率期限結構模型對國債的理論定價能力進行了實證比較,每一樣本交易日隨機選取部分樣本用于各模型參數(shù)的估計,先用單一利率期限結構模型對國債利率期限結構進行實證研究,選用了多項式樣條函數(shù)模型、Nelson-Siegel模型和Nelson-Siegel模型的擴展Svensson模型三個單一模型。在完成單一模型的估計后,本文利用國債價格擬合誤差最小這個組合優(yōu)化準則,對三個單一模型進行組合,估計出三個模型的組合權重。利用當日估計出的組合權重,借助組合預測方法形成組合預測模型,并利用該模型對當日剩余國債樣本進行理論定價。在評價各利率期限結構模型對真實利率曲線的擬合優(yōu)度上,本文選取的準則是對國債價格的預測能力,即通過貼現(xiàn)求出附息國債的理論定價,并與實際交易價格進行比較,用定價的精確度和穩(wěn)定性評價各利率期限結構模型的優(yōu)劣。在進行詳細的統(tǒng)計分析對比后,本文最后得出結論：本文提出的基于組合預測方法的利率期限結構模型不管是在國債理論定價精確度,還是在理論定價穩(wěn)定性上都優(yōu)于其他三個單項模型(多項式樣條函數(shù)模型、Svensson模型和Nelson-Siegel模型),組合預測方法對各單項模型的組合達到了預定的效果,其組合了各單項模型對實際利率期限結構曲線反映的特點,對擬合優(yōu)度高的模型賦予了較高的組合權重,使組合在一起的模型強于任一單項模型。 本文在最后提出了今后研究的方向。在今后的研究過程中,會更加注重單項模型的選擇,在組合模型中加入更多的單項模型以提高組合模型的對實際利率期限結構曲線的擬合優(yōu)度。同時也會更加注重組合權重參數(shù)估計算法的研究,從而使估計出的權重更精確。
[Abstract]:The object of this paper is the term structure of interest rate, the interest rate term structure refers to the relationship between the interest rate and the different period of time, it needs to use the spot rate of bonds between the remaining maturity of the form. It has important theoretical and practical significance of the study on the interest rate term structure, which can provide theoretical support for the determination of the benchmark interest rate and provide a theoretical basis for the bonds and financial derivatives pricing, and can provide operation basis for the control of financial risk and interest rate risk management, is conducive to the rational design of financial products, is conducive to the arbitrage opportunity in the market, improve the efficiency of the financial market.
Study on the related theory of the term structure of interest rates has undergone qualitative research stage of traditional and modern precise quantitative research stage. Traditional qualitative research has largely expected theory and market segmentation theory. Then more and more people from the mathematical model, thus more accurate prediction and Simulation of the interest rate, the proposed model can be summed up by recursive method the spline function method, and the simple model.
The mathematical model of the structure model based on different interest rate term is different, so the models have different advantages and disadvantages, and the term structure of interest rate in actual economic environment is complex and changeable, which leads to the goodness of the actual model of the term structure of interest rates will appear periodic fluctuations, there is no single interest rate term structure model fitting is stable, so only by a single interest rate term structure model to estimate the term structure of interest rate in China, the effect is not the best. In order to improve the rate of fitting prediction results based on the combined forecasting method, combination forecasting method is the combination of model, the weights assigned to each model according to the goodness of fit of proper size the model fitting degree is high, the model will be assigned a larger weight, in order to disperse the single prediction model of uncertainty, in order to improve the prediction accuracy of the overall And stability.
In this paper, each term structure model are empirically compared to the bond pricing theory, estimation of each trading day samples randomly selected part samples for each model parameter, the term structure of interest rates for empirical research with a single interest rate term structure model, choose the polynomial spline function model, Nelson-Siegel model and Nelson-Siegel model the extended Svensson model three single models. In the estimation of single model, the minimum of the combinatorial optimization criterion of bond price fitting error of three single model group, estimate the combination weights of the three models. The combination weights estimated by the day, the combination forecasting method of formation combination forecasting model and on the day of the remaining sample bonds pricing theory by using the model. In the evaluation of the interest rate term structure model of the real interest rate curve The goodness of fit, the criterion is the ability to predict bond prices, namely the discount for treasury bond pricing theory, and compared with the actual transaction price, the evaluation model of interest rate term structure with the merits of pricing accuracy and stability. In the process of detailed comparative analysis, this paper concludes conclusion: Based on the model of interest rate term structure combination forecast method in bond pricing accuracy, or in the theory of pricing stability is better than that of the other three individual models (polynomial spline function model, Svensson model and Nelson-Siegel model), a combination model of each single model to achieve the intended effect. The combination of the characteristics of each single model of actual interest rate term structure curve reflects the combination of the right fit high model gives higher weight to group The combined model is stronger than any single model.
At the end of this paper, the future research direction is put forward. In the future research, will pay more attention to the selection of a single model, adding more individual models to improve the structure of the combined model actual interest rate curve fit in the combined model. At the same time will be more filling recombination algorithm of weight parameter estimation. In order to make the estimated weight more accurate.

【學位授予單位】：東北財經(jīng)大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：F810.5;F820;F224

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