Comportamiento de la UVR en el largo plazo

Evelyn Lucía Taylor-Conto; Romario Ademir Conto-López

doi:10.24310/recta.24.1.2023.19860

Autores/as

Evelyn Lucía Taylor-Conto Universidad Nacional de Colombia
Romario Ademir Conto-López Instituto Tecnológico Metropolitano

DOI:

https://doi.org/10.24310/recta.24.1.2023.19860

Palabras clave:

UVR, series de tiempo, SARIMA, regresión lineal, Holt-Winters, Redes Neuronales

Resumen

En este artículo se implementan diferentes técnicas para predecir la unidad de valor real colombiana (UVR), basándose únicamente en el histórico de su comportamiento. La UVR representa el poder adquisitivo basado en la variación del índice de precios al consumidor (IPC) para el mes calendario inmediatamente anterior al calculado, además muchos créditos de vivienda están indexados a la UVR en Colombia, permitiendo que las entidades financieras conserven el poder adquisitivo del dinero prestado. Para el estudio son consideradas técnicas de pronóstico mediante modelos SARIMA, regresión lineal, suavizamiento Holt-Winters aditivo y multiplicativo, y redes neuronales artificiales. De acuerdo con el análisis, se obtiene que la mejor técnica para realizar predicciones al final del ciclo estacional es el suavizamiento Holt-Winters multiplicativo y para predecir a mitad del ciclo estacional es un modelo SARIMA (1,1,1) (0,1,1).

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