{"title":"Pronósticos de la estructura temporal de las tasas de interés en México con base en un modelo afín","authors":"Rocío Elizondo","doi":"10.24201/ee.v32i2.7","DOIUrl":null,"url":null,"abstract":"This paper shows that an affine model allows to equalize or improve the forecasts of the term structure of interest rates in Mexico. The forecasting model is a linear relationship between interest rates and three observable factors, using maturities 1-60 months. Affine model predictions are compared with those of forward rates, AR(1), VAR(1), and random walks. Affine model has a performance comparable to other models for horizons of 12- and 18-months, except for the random walk, which presents smaller forecast for maturities of 24- and 36- months. However, improving its forecasting performance for the 24- month horizon, and especially for 60-month maturities.","PeriodicalId":43766,"journal":{"name":"Estudios De Economia","volume":"5 5","pages":"213-253"},"PeriodicalIF":0.4000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Estudios De Economia","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.24201/ee.v32i2.7","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 3
Abstract
This paper shows that an affine model allows to equalize or improve the forecasts of the term structure of interest rates in Mexico. The forecasting model is a linear relationship between interest rates and three observable factors, using maturities 1-60 months. Affine model predictions are compared with those of forward rates, AR(1), VAR(1), and random walks. Affine model has a performance comparable to other models for horizons of 12- and 18-months, except for the random walk, which presents smaller forecast for maturities of 24- and 36- months. However, improving its forecasting performance for the 24- month horizon, and especially for 60-month maturities.