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Modeling and comovements of the Colombian exchange rate, 2011-2017 [Modelación y co-movimientos de la tasa de cambio Colombiana, 2011-2017]

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Maya Sierra G.
Marín Rodríguez N.J.
TY - GEN T1 - Modeling and comovements of the Colombian exchange rate, 2011-2017 [Modelación y co-movimientos de la tasa de cambio Colombiana, 2011-2017] AU - Maya Sierra G. AU - Marín Rodríguez N.J. UR - http://hdl.handle.net/11407/5665 PB - Universidad Pablo de Olavide AB - The exchange rate is influenced by multiple national and international macroeconomic factors, which generates high levels of uncertainty. The objective of this research is the construction of ARIMA-GARCH and ARIMAX-GARCH models as a tool for the forecast of the exchange rate in Colombia from the daily returns of the closing prices USD/COP and its analysis of dynamic correlation with some of the most explicative variables. The results suggest that the incorporation of significant exogenous variables within the ARIMAX-GARCH model with persistent correlation according to the DCC (Dinamic Conditional Correlation) model to the USD/COP pair generates out-of-sample forecasts with better performance than the ARIMA-GARCH univariate models. © 2019, Universidad Pablo de Olavide. ER - @misc{11407_5665, author = {Maya Sierra G. and Marín Rodríguez N.J.}, title = {Modeling and comovements of the Colombian exchange rate, 2011-2017 [Modelación y co-movimientos de la tasa de cambio Colombiana, 2011-2017]}, year = {}, abstract = {The exchange rate is influenced by multiple national and international macroeconomic factors, which generates high levels of uncertainty. The objective of this research is the construction of ARIMA-GARCH and ARIMAX-GARCH models as a tool for the forecast of the exchange rate in Colombia from the daily returns of the closing prices USD/COP and its analysis of dynamic correlation with some of the most explicative variables. The results suggest that the incorporation of significant exogenous variables within the ARIMAX-GARCH model with persistent correlation according to the DCC (Dinamic Conditional Correlation) model to the USD/COP pair generates out-of-sample forecasts with better performance than the ARIMA-GARCH univariate models. © 2019, Universidad Pablo de Olavide.}, url = {http://hdl.handle.net/11407/5665} }RT Generic T1 Modeling and comovements of the Colombian exchange rate, 2011-2017 [Modelación y co-movimientos de la tasa de cambio Colombiana, 2011-2017] A1 Maya Sierra G. A1 Marín Rodríguez N.J. LK http://hdl.handle.net/11407/5665 PB Universidad Pablo de Olavide AB The exchange rate is influenced by multiple national and international macroeconomic factors, which generates high levels of uncertainty. The objective of this research is the construction of ARIMA-GARCH and ARIMAX-GARCH models as a tool for the forecast of the exchange rate in Colombia from the daily returns of the closing prices USD/COP and its analysis of dynamic correlation with some of the most explicative variables. The results suggest that the incorporation of significant exogenous variables within the ARIMAX-GARCH model with persistent correlation according to the DCC (Dinamic Conditional Correlation) model to the USD/COP pair generates out-of-sample forecasts with better performance than the ARIMA-GARCH univariate models. © 2019, Universidad Pablo de Olavide. OL Spanish (121)
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Abstract
The exchange rate is influenced by multiple national and international macroeconomic factors, which generates high levels of uncertainty. The objective of this research is the construction of ARIMA-GARCH and ARIMAX-GARCH models as a tool for the forecast of the exchange rate in Colombia from the daily returns of the closing prices USD/COP and its analysis of dynamic correlation with some of the most explicative variables. The results suggest that the incorporation of significant exogenous variables within the ARIMAX-GARCH model with persistent correlation according to the DCC (Dinamic Conditional Correlation) model to the USD/COP pair generates out-of-sample forecasts with better performance than the ARIMA-GARCH univariate models. © 2019, Universidad Pablo de Olavide.
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