Author: Desmond John Mc Manus
Publisher:
ISBN:
Category : Interest rates
Languages : en
Pages : 50
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Book Description
Considers a wide range of several continuous-time one-factor models for short-term interest rates that are nested into one general model.
Author: D. Mc Manus
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Mr.Vadim Khramov
Publisher: International Monetary Fund
ISBN: 1475591225
Category : Business & Economics
Languages : en
Pages : 27
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Book Description
This paper sheds light on a narrow but crucial question in finance: What should be the parameters of a model of the short-term real interest rate? Although models for the nominal interest rate are well studied and estimated, dynamics of the real interest rate are rarely explored. Simple ad hoc processes for the short-term real interest rate are usually assumed as building blocks for more sophisticated models. In this paper, parameters of the real interest rate model are estimated in the broad class of single-factor interest rate diffusion processes on U.S. monthly data. It is shown that the elasticity of interest rate volatility—the relationship between the volatility of changes in the interest rate and its level—plays a crucial role in explaining real interest rate dynamics. The empirical estimates of the elasticity of the real interest rate volatility are found to be about 0.5, much lower than that of the nominal interest rate. These estimates show that the square root process, as in the Cox-Ingersoll-Ross model, provides a good characterization of the short-term real interest rate process.
Author: Rajna Gibson
Publisher: Now Publishers Inc
ISBN: 1601983727
Category : Business & Economics
Languages : en
Pages : 171
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Book Description
Modeling the Term Structure of Interest Rates provides a comprehensive review of the continuous-time modeling techniques of the term structure applicable to value and hedge default-free bonds and other interest rate derivatives.
Author: Teresa Corzo
Publisher:
ISBN:
Category :
Languages : en
Pages : 43
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Book Description
We present and estimate, using nonparametric regression techniques, a model of short term interest rate dynamics and use the estimation to value bonds. We study the case of two European countries - Spain and Italy - that belong to EMU, and compare the resulting bond prices of a one factor model with that of a two factor, the second factor being a stochastic mean. The pricing errors for both models are 34% smaller than those reported on the parametric literature. Furthermore, the two factor model, which takes into account the convergence with Europe of the domestic economies, obtains better results than the one factor model. Our findings give strong support to the importance of a correct specification of the volatility of interest rates.
Author: Mr.Vadim Khramov
Publisher: International Monetary Fund
ISBN: 147559464X
Category : Business & Economics
Languages : en
Pages : 27
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Book Description
This paper sheds light on a narrow but crucial question in finance: What should be the parameters of a model of the short-term real interest rate? Although models for the nominal interest rate are well studied and estimated, dynamics of the real interest rate are rarely explored. Simple ad hoc processes for the short-term real interest rate are usually assumed as building blocks for more sophisticated models. In this paper, parameters of the real interest rate model are estimated in the broad class of single-factor interest rate diffusion processes on U.S. monthly data. It is shown that the elasticity of interest rate volatility—the relationship between the volatility of changes in the interest rate and its level—plays a crucial role in explaining real interest rate dynamics. The empirical estimates of the elasticity of the real interest rate volatility are found to be about 0.5, much lower than that of the nominal interest rate. These estimates show that the square root process, as in the Cox-Ingersoll-Ross model, provides a good characterization of the short-term real interest rate process.
Author: Ah Hin Pooi
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Ren-Raw Chen
Publisher: World Scientific
ISBN: 9789810227517
Category : Business & Economics
Languages : en
Pages : 182
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Book Description
The book is a systematic summary of modern term structure theories and how interest rate contingent claims are priced under such theories. This is the first book on such an attempt. The book reviews important term structure models and chooses one model to consistantly demonstrate contingent claim pricing. Well-known models are included and their relationships are thoroughly discussed. The book also provides a complete process of model implementation from parameter estimation to hedging. Examples are provided throughout.
Author:
Publisher: Alchemy Technologies
ISBN:
Category :
Languages : en
Pages : 58
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Book Description
Author: Fathi Abid
Publisher:
ISBN:
Category :
Languages : en
Pages : 13
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Book Description
The aim of this paper is twofold; first we concentrate on the work of Vasicek (1977) and Cox, Ingersoll and Ross (1985). We examine and test empirically each model and discuss its performance in predicting the term structure of interest rates using a parametric estimating approach GMM (Generalized Moments Method). Second we estimate the term structure of interest rate dynamics using a nonparametric approach ANN (Artificial Neural Network). Two neural network models are performed. The first model uses spreads between interest rates of 10 different maturities as the only explanatory variable of interest rate changes. The second model introduces two factors, spreads and interest rates' levels. Using historical U.S. Treasury bill rates and Treasury bond yields, we compare the ability of each model to predict the term structure of interest rates. Data are daily and cover the period from 3 January 1995 to 29 December 2000. Results suggest that, neural network; Vasicek (1977) and Cox, Ingersoll and Ross (1985) models generate different yield curves. Neural network models outperform the parametric standard models. The most successful forecast is obtained with two factors neural network model.
