Maestría en Administración Financiera · 2025
Desarrollo y comparación de modelos ARIMA-GARCH y SARIMA-GARCH para la estimación del tipo de cambio USD/COP y propuesta de coberturas cambiarias con derivados forward para empresa importadora de autopartes en Colombia
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Resumen
This research analyzed the estimation of the USD/COP exchange rate through the development and comparison of ARIMA-GARCH and SARIMA-GARCH models to design hedging strategies. Historical data from the Representative Market Rate (2019-2024) and optimization techniques in Python were used. Results indicated that SARIMA-GARCH provided higher predictive accuracy by capturing seasonal fluctuations and reducing errors compared to ARIMA-GARCH. Based on these forecasts, forward contract hedging strategies were proposed to mitigate exchange rate risk. However, market uncertainty and unexpected events may affect model accuracy, making recalibration every 60-90 days advisable. The combination of time series models with conditional heteroskedasticity proved essential in volatile markets, although its high computational demand can be a limitation. This study provides applicable tools for exchange rate risk management, optimizing financial decision making for importing companies.