NDLI: Estimation of a Nonparametric model for Bond Prices from Cross-section and Time series Information

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Estimation of a Nonparametric model for Bond Prices from Cross-section and Time series Information

Content Provider	Scilit
Author	Koo, Bonsoo Vecchia, Davide La Linton, Oliver B.
Copyright Year	2019
Description	Journal: SSRN Electronic Journal We develop estimation methodology for an additive nonparametric panel model that is suitable for capturing the pricing of coupon-paying government bonds followed over many time periods. We use our model to estimate the discount function and yield curve of nominally riskless government bonds. The novelty of our approach is the combination of two different techniques: cross-sectional nonparametric methods and kernel estimation for time varying dynamics in the time series context. The resulting estimator is used for predicting individual bond prices given the full schedule of their future payments. In addition, it is able to capture the yield curve shapes and dynamics commonly observed in the fixed income markets. We establish the consistency, the rate of convergence, and the asymptotic normality of the proposed estimator. A Monte Carlo exercise illustrates the good performance of the method under different scenarios. We apply our methodology to the daily CRSP bond market dataset, and compare ours with the popular Diebold and Li (2006) method.
Related Links	https://www.monash.edu/business/ebs/research/publications/ebs/wp04-2020.pdf https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=3341344
ISSN	10914358
e-ISSN	15565068
DOI	10.2139/ssrn.3341344
Journal	SSRN Electronic Journal
Language	English
Publisher	Elsevier BV
Publisher Date	2019-02-25
Access Restriction	Open
Subject Keyword	Journal: SSRN Electronic Journal Statistics and Probability Nonparametric Inference Panel Data Time Varying Yield Curve Dynamics
Content Type	Text
Resource Type	Article
Subject	Public Health, Environmental and Occupational Health Psychiatry and Mental Health

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