A dynamic model for the forward curve

This article develops and estimates a dynamic arbitrage-free model of the current forward curve as the sum of (i) an unconditional component, (ii) a maturity-specific component and (iii) a date-specific component. The model combines features of the Preferred Habitat model, the Expectations Hypothesi...

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Bibliographic Details
Main Authors: Chua, Choong Tze, Dean, Foster, Ramaswamy, Krishna, Stine, Robert
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2010
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Online Access:https://ink.library.smu.edu.sg/lkcsb_research/2492
https://ink.library.smu.edu.sg/context/lkcsb_research/article/3491/viewcontent/A_Dynamic_Model_for_the_Forward_Curve__1_.pdf
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Institution: Singapore Management University
Language: English
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Summary:This article develops and estimates a dynamic arbitrage-free model of the current forward curve as the sum of (i) an unconditional component, (ii) a maturity-specific component and (iii) a date-specific component. The model combines features of the Preferred Habitat model, the Expectations Hypothesis (ET) and affine yield curve models; it permits a class of low-parameter, multiple state variable dynamic models for the forward curve. We show how to construct alternative parametric examples of the three components from a sum of exponential functions, verify that the resulting forward curves satisfy the Heath-Jarrow-Morton (HJM) conditions, and derive the risk-neutral dynamics for the purpose of pricing interest rate derivatives. We select a model from alternative affine examples that are fitted to the Fama-Bliss Treasury data over an initial training period and use it to generate out-of-sample forecasts for forward rates and yields. For forecast horizons of 6 months or longer, the forecasts of this model significantly outperform those from common benchmark models.