A Comparative Analysis of Several Popular Term Structure Estimation Models

Ferguson, Robert A.; Raymar, Steven

doi:10.3905/jfi.1998.408221

Cited by 18 publications

(9 citation statements)

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“…As an alternative to the above mathematical spline functions, Brown and Dybvig (1986), Schaefer (1994), De Munnik andSchotman (1994), Sercu and Wu (1997), and Ferguson and Raymar (1998) used economic functions such as the Vasicek (1977) and the Cox, Ingersoll, and Ross (1985) term structure models to fit the market yield curve. Unlike the mathematical spline functions which are able to approximate the discount function arbitrarily closely, although these economic functions can provide economic explanations, they seem to fail to provide a rich variety of shapes to fit the versatile market yield curve.…”

Section: Term Structure Fitting Methodologiesmentioning

confidence: 99%

“…Models such as those developed by McCulloch (1971), Carleton and Cooper (1976), Schaefer (1981), Vasicek and Fong (1982), Chambers, Carleton, and Waldman (1984), Nelson and Siegel (1987), Steeley (1991), Pham (1998), and Barzanti and Corradi (1998) used various mathematical spline functions to approximate the term structure. Others such as Brown and Dybvig (1986), Schaefer (1994), De Munnik andSchotman (1994), Sercu and Wu (1997), and Ferguson and Raymar (1998) used economic functions such as the Vasicek (1977) and the Cox, Ingersoll, and Ross (1985) term structure models to fit the market yield curve. The resulting term structure of interest rates from the empirical methodology can be directly put into interest rate contingent claim pricing models, such as the Ho and Lee (1986), the Babbs (1990), the Heath, Jarrow, and Morton (1992), and the Hull and White (1990) models, for pricing various interest rate contingent claims.…”

Section: Introductionmentioning

confidence: 99%

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Term Structure Fitting Models and Information Content: An Empirical Examination in Taiwanese Government Bond Market

Yeh

Lin

2003

Rev. Pac. Basin Finan. Mark. Pol.

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In this study, we apply empirical methodologies, which are essentially curve fitting techniques, and use cross-sectional bond price data to estimate and analyze the Taiwanese government bond (TGB) term structure of interest rates. We choose two economic models: the Vasicek model and the CIR model, and one mathematical model: the B-spline approximation function, as the discount bond function to extract the term structure from market coupon bond prices. To assess the fitting performances and investigate the economic information content of the term structure fitting models, we compare the estimation errors and examine whether trading mis-priced bonds according the fitting model, can provide excess returns. The hypothesis is that the mathematical model can fit the term structure better than the economic models. But the economic models, which contain economic information, are able to explain the term structure dynamics. Thus the economic models can perform better in identifying mis-priced bonds and in predicting excess trading returns, than the mathematical model. Using the methodologies in this study, we can investigate the term structure fitting problems and look at the economic information content of the term structure fitting models.

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Section: Term Structure Fitting Methodologiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Term Structure Fitting Models and Information Content: An Empirical Examination in Taiwanese Government Bond Market

Yeh

Lin

2003

Rev. Pac. Basin Finan. Mark. Pol.

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“…Buono, Gregory-Allen, and Yaari (1992) provide a detailed survey of previous approaches to yield curve smoothing. Ferguson and Raymar (1998) compare the results of several models that fit a term structure to market data. Adams and van Deventer (1994; hereafter AvD) introduce a mathematical measure of smoothness, and show that the yield curve with the smoothest possible forward rate function, consistent with the observable data, is related to, but significantly different from, the popular cubic spline approach to the smoothing of yields and discount bond prices.…”

Section: Yield Curve Smoothingmentioning

confidence: 99%

Pricing Eurodollar futures options using the BDT term structure model: The effect of yield curve smoothing

Bali

Karagozoglu

2000

J. Fut. Mark.

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“…When models with curvature are fitted, as in Ferguson and Raymar [1998], goodness of fit to a static yield curve is the evaluation criterion. Often the eventual application of such approaches is to determine whether particular fixed-income securities are expensive or cheap by pricing them "off the curve."…”

Section: Types Of Yield Curve Models and Their Predictive Strengthsmentioning

confidence: 99%

Forecasting the Yield Curve Shape

Dolan¹

1999

JFI

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M any models of yield curve shape have been proposed: from stochastic, to fundamental, to principal components. Most models are concerned with either achieving goodness of fit, given "rationality criteria"; the ability to forecast the level or slope of the term structure; or the ability to generate scenarios for pricing and immunization applications. With the exception of work on convexity bias, there is little work on predicting the curvature of the yield curve beyond eighteen months.Investment managers are keenly interested in models of the yield curve into which expectations can be embedded so that the analysis can be used to direct investments. To provide a model of yield curve shape that is effective for investment management, we must answer four questions: 1) which yield curve model should be used; 2) what a priori assumptions should be made; 3) how should the shape parameters be forecast; and 4) how effective are the forecasts for investment purposes.We summarize some of the major threads in term structure modeling as they pertain to the curvature of the term structure. We discuss why shape is important for investment management and evaluate a simple forecasting mechanism for the shape parameter. I. TYPES OF YIELD CURVE MODELS AND THEIR PREDICTIVE STRENGTHSYield curve models can be classified into three types:1. Stochastic, arbitrage-free. 2. Principal components. 3. Fundamental.The stochastic arbitrage-free models, such as Brennan and Schwartz [1982] and Heath, Jarrow, and Morton [1990], develop interest rate processes, given an underlying random variable (or variables), that: 1) meet rationality criteria, or 2) are unlikely to generate yield curves with arbitrage opportunities. One survey of such approaches, Chan et al. [1992], highlights their emphasis on the relationship between level of interest rates and volatility assumption for the random variable.Boero and Torricelli [1996] point out that many of the theories explain the term structure, given the long and short rates, especially Brennan and Schwartz. Boero and Torricelli also assert that Ho-Lee [1986] and the Heath, Jarrow, and Morton [1990] models are not models of the term structure, only models of how to price contingent claims.Because these models are designed for use in options pricing, the mean does not play a role. The mean, however, is very important to investment managers because it is the primary measure affecting a manager's view. We do not use stochastic models to predict any component of the yield curve shape.Principal components analysis (PCA) focuses on finding orthogonal factors, in the space of actual interest rate changes, that

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A Comparative Analysis of Several Popular Term Structure Estimation Models

Cited by 18 publications

References 0 publications

Term Structure Fitting Models and Information Content: An Empirical Examination in Taiwanese Government Bond Market

Term Structure Fitting Models and Information Content: An Empirical Examination in Taiwanese Government Bond Market

Pricing Eurodollar futures options using the BDT term structure model: The effect of yield curve smoothing

Forecasting the Yield Curve Shape

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