Estimating and Forecasting the Term Structure of Interest Rates:US and Colombia Analysis
type: CreativeWork
description: 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.
abstract: 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.
author: Rodriguez Revilla, Cristhian Andres
language: spa
keywords: 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
license: http://creativecommons.org/licenses/by-nc-nd/2.5/co/
date published: 2016-02-18
date modified: 2026-07-27T20:46:41Z
provider: Universidad del Rosario
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Universidad del Rosario

PropertyValue
property ID: DOI
value: 10.48713/10336_11956