Estimating and Forecasting the Term Structure of Interest Rates:US and Colombia Analysis

In this paper we use the most representative models that exist in the literature on term structure of interest rates. In particular, we explore affine one factor models and polynomial-type approximations such as Nelson and Siegel. Our empirical application considers monthly data of USA and Colombia for estimation and forecasting. We find that affine models do not provide adequate performance either in-sample or out-of-sample. On the contrary, parsimonious models such as Nelson and Siegel have adequate results in-sample, however out-of-sample they are not able to systematically improve upon random walk base forecast.

Grantor dc:publisher

Universidad del Rosario

Year dc:date

2016

Author dc:creator

• Rodriguez Revilla, Cristhian Andres

• Term structure
• Out-of-sample forecasting
• Nelson-Siegel model
• Linear regression
• Affine models
• Kalman Filter
• Root Mean
• Squared Error
• Economía financiera
• Finanzas
• Negociaciones internacionales
• Economía internacional

Statement dc:rights

• info:eu-repo/semantics/openAccess

Licence

• http://creativecommons.org/licenses/by-nc-nd/2.5/co/

Language dc:language

spa

Identifier

http://repository.urosario.edu.co/handle/10336/11956

OAI identifier oai:identifier

oai:repository.urosario.edu.co:10336/11956