Modeling and comovements of the Colombian exchange rate, 2011-2017 [Modelación y co-movimientos de la tasa de cambio Colombiana, 2011-2017]
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 dai...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2019
- Institución:
- Universidad de Medellín
- Repositorio:
- Repositorio UDEM
- Idioma:
- spa
- OAI Identifier:
- oai:repository.udem.edu.co:11407/5665
- Acceso en línea:
- http://hdl.handle.net/11407/5665
- Palabra clave:
- Correlation
Exchange rate
Forecast models
Macroeconomic fundamentals
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- http://purl.org/coar/access_right/c_16ec
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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] |
| title |
Modeling and comovements of the Colombian exchange rate, 2011-2017 [Modelación y co-movimientos de la tasa de cambio Colombiana, 2011-2017] |
| spellingShingle |
Modeling and comovements of the Colombian exchange rate, 2011-2017 [Modelación y co-movimientos de la tasa de cambio Colombiana, 2011-2017] Correlation Exchange rate Forecast models Macroeconomic fundamentals |
| title_short |
Modeling and comovements of the Colombian exchange rate, 2011-2017 [Modelación y co-movimientos de la tasa de cambio Colombiana, 2011-2017] |
| title_full |
Modeling and comovements of the Colombian exchange rate, 2011-2017 [Modelación y co-movimientos de la tasa de cambio Colombiana, 2011-2017] |
| title_fullStr |
Modeling and comovements of the Colombian exchange rate, 2011-2017 [Modelación y co-movimientos de la tasa de cambio Colombiana, 2011-2017] |
| title_full_unstemmed |
Modeling and comovements of the Colombian exchange rate, 2011-2017 [Modelación y co-movimientos de la tasa de cambio Colombiana, 2011-2017] |
| title_sort |
Modeling and comovements of the Colombian exchange rate, 2011-2017 [Modelación y co-movimientos de la tasa de cambio Colombiana, 2011-2017] |
| dc.subject.none.fl_str_mv |
Correlation Exchange rate Forecast models Macroeconomic fundamentals |
| topic |
Correlation Exchange rate Forecast models Macroeconomic fundamentals |
| description |
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. |
| publishDate |
2019 |
| dc.date.accessioned.none.fl_str_mv |
2020-04-29T14:53:36Z |
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2020-04-29T14:53:36Z |
| dc.date.none.fl_str_mv |
2019 |
| dc.type.eng.fl_str_mv |
Article |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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http://purl.org/coar/resource_type/c_6501 http://purl.org/coar/resource_type/c_2df8fbb1 |
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info:eu-repo/semantics/article |
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1886516X |
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http://hdl.handle.net/11407/5665 |
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1886516X |
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http://hdl.handle.net/11407/5665 |
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spa |
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spa |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077110612&partnerID=40&md5=743f984a25659ba72c23d8bd219027da |
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28 |
| dc.relation.citationstartpage.none.fl_str_mv |
301 |
| dc.relation.citationendpage.none.fl_str_mv |
341 |
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Abhyankar, A., Sarno, L., Valente, G., Exchange rates and fundamentals: Evidence on the economic value of predictability (2005) Journal of International Economics, 66 (2), pp. 325-348 Andrews, B.H., Dean, M.D., Building ARIMA and ARIMAX Models for Predicting Long-Term Disability Benefit Application Rates in the Public / Private Sectors Sponsored by Society of Actuaries Health Section Prepared by University of Southern Maine (2013) Building ARIMA and ARIMAX Models for Predicting Long-Term Disability Benefit Application Rates in the Public/Private Sectors Sponsored Anggraeni, W., Vinarti, R.A., Kurniawati, Y.D., Performance Comparisons between Arima and Arimax Method in Moslem Kids Clothes Demand Forecasting: Case Study (2015) Procedia Computer Science, 72, pp. 630-637 Babu, A.S., Reddy, B.A., Exchange Rate Forecasting using ARIMA, Neural Network and Fuzzy Neuron (2015) Journal of Stock & Forex Trading, 4 (3), pp. 1-5 Bloomberg, L.P., (2017) Bloomberg Terminal, , https://www.bloomberg.com/, Stock last price from 1/1/11 to 06/30/17. Recuperado de: Bollerslev, T., Generalized autoregressive conditional heteroskedasticity (1986) Journal of Econometrics, 31 (3), pp. 307-327 Box, G.E., Jenkins, G.M., (1970) Time series analysis, control, and forescasting, 3226 (3228), p. 10. , San Francisco, CA: Holden Day Cardenas, M., La tasa de cambio en Colombia (1997) Cuadernos de Fedesarrollo, , No. 012740. Bogotá Carr, P., Wu, L., Theory and evidence on the dynamic interactions between sovereign credit default swaps and currency options (2007) Journal of Banking and Finance, 31 (8), pp. 2383-2403 Cassel, G., (1922) Money and foreign exchange after 1914, pp. 101-170. , London: Constable and Company Limited Chavarro, F., Política monetaria en Colombia, 1999-2000 (2008) Revista Criterio Libre, 9, pp. 73-93 Chavarro, F., Grautoff, M., El trilema de la Banca Central Colombiana: Un problema intertemporal (2010) Criterio Libre, 8, pp. 15-30. , http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:No+Title#0, Recuperado de: Chiang, T.C., Jeon, B.N., Li, H., Dynamic correlation analysis of financial contagion: Evidence from Asian markets (2007) Journal of International Money and Finance, 26 (7), pp. 1206-1228 Chinn, M.D., Meese, R.A., Banking on currency forecasts: How predictable is change in money (1995) Journal of International Economics, 38 (1-2), pp. 161-178 Chong, M., Aguilar, R., (2016) Proyección de Series de Tiempo para el Consumo de la Energía Eléctrica a Clientes Residenciales en Ecuador, pp. 56-76. , 29(Julio) Davis, J.S., External debt and monetary policy autonomy (2017) Ensayos Sobre Política Económica, 35, pp. 53-63 Echavarría, J.J., Misas, M., López, E., La Tasa de Cambio Real de Equilibrio en Colombia y su Desalineamiento: Estimación a través de un modelo SVEC (2007) Borradores de Economía, 472, pp. 2-37 Echavarría, J.J., Vásquez, D., Villamizar, M., The Real Exchange Rate in Colombia: Too Far from Equilibrium (2005) Ensayos Sobre Política Económica, 49, pp. 134-191 Ecopetrol, S.A., (2016), http://www.ecopetrol.com.co/wps/portal/es/ecopetrol-web/nuestra-empresa/quienes-somos/acerca-de-ecopetrol/nuestra-historia, (14 de junio). Recuperado de: Edwards, S., Savastano, M.A., Exchange Rates in Emerging Economies: What do we Know? What do we need to know? (1999) National Bureau of Economic Research Working Paper Series Ehrmann, M., Fratzscher, M., Exchange rates and fundamentals: New evidence from real-time data (2005) Journal of International Money and Finance, 24 (2), pp. 317-341 Engel, C., West, K.D., Exchange Rates and Fundamentals (2005) Journal of Political Economy, 113 (3), pp. 485-517 Engle, R., Autoregressive Conditional Heteroscedasticity With Estimates of the Variance of United Kingdom Inflation1 (1982) Econometrica, 50 (4), pp. 987-1007 Engle, R., Dynamic Conditional Correlation (2002) Journal of Business & Economic Statistics, 20 (3), pp. 339-350 Evans, M.D.D., Order flows and the exchange rate disconnect puzzle (2010) Journal of International Economics, 80 (1), pp. 58-71 Fahimifard, S.M., Homayounifar, M., Sabouhi, M., Moghaddamnia, A.R., Comparison of ANFIS, ANN, GARCH and ARIMA Techniques to Exchange Rate Forecasting (2009) Journal of Applied Sciences, 9 (20), pp. 3641-3651 Fama, E.F., The Behavior of Stock-Market Prices (1965) The Journal of Business, 38 (1), pp. 34-105 Fernández-Rodriguez, F., Sosvilla-Rivero, S., Andrada-Félix, J., Exchange-rate forecasts with simultaneous nearest-neighbour methods: Evidence from the EMS (1999) International Journal of Forecasting, 15, pp. 383-392 Fernández, F., González, C., Sosvilla, S., On the profitability of technical trading rules based on artificial neural networks: (2000) Economics Letters, 69 (1), pp. 89-94 Frenkel, J.A., Mussa, M.L., Chapter 14 Asset markets, exchange rates and the balance of payments (1985) Handbook of International Economics, 2, pp. 679-747 Gioqinang, Z., Hu, M.Y., Neural network forecasting of the British Pound/US Dollar exchange rate (1998) Omega, 26 (4), pp. 495-506 Gómez, J., Hernández, J.M., Composición cambiaria y Poder Adquisitivo de las reservas internacionales (2011) Borradores de Economía, Banco de La Republica, (654) González, C., (2003) Nuevas perspectivas del análisis técnico de los mercados bursátiles mediante el aprendizaje automático. Aplicaciones al índice general de la bolsa de Madrid. Resarch Gate, , http://hdl.handle.net/10553/2156, Recuperado de: Granger, C.W., Investigating Causal Relations by Econometric Models and Cross-spectral Methods (1986) Econometrica: Journal of the Econometric Society, 37 (3), pp. 424-438 Hassan, M.K., Kayhan, S., Bayat, T., Does credit default swap spread affect the value of the Turkish LIRA against the U. S dollar? (2017) Borsa Istanbul Review, 17 (1), pp. 1-9 Jalil, M.A., Misas, M., Evaluaciòn de pronòsticos del tipo de cambio utilizando redes neuronales y funciones de pèrdida asimètricas (2007) Revista Colombiana de Estadistica, 30 (1), pp. 143-161 Julio, B., Yook, Y., Policy Uncertainty, Irreversibility, and Cross-Border Flows of Capital Federal Reserve Board of Governors (2016) Journal of International Economics, 103, pp. 13-26 Kamruzzaman, J., Sarker, R.A., Forecasting of currency exchange rates using ANN: A case study (2003) Neural Networks and Signal Processing, 1, pp. 793-797 Kim, B.-H., Kim, H.-K., Oh, K.-Y., The purchasing power parity of Southeast Asian currencies: A time-varying coefficient approach (2009) Economic Modelling, 26 (1), pp. 96-106 Krugman, P.R., Obstfeld, M., Melitz, M.J., (2012) Economía international: Teoría y política, , Pearson Lothian, J.R., Taylor, M.P., Real exchange rate behavior: The recent float from the perspective of the past two centuries (1996) Journal of Political Economy, 104 (3), pp. 488-509 MacDonald, R., Marsh, I.W., On Fundamentals and Exchange Rates: A Casselian Perspective (1997) The Review of Economics and Statistics, 79 (4), pp. 655-664 Majhi, R., Panda, G., Sahoo, G., Efficient prediction of exchange rates with low complexity artificial neural network models (2009) Expert Systems with Applications, 36 (1), pp. 181-189 Malkiel, B.G., A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing (10th Edition) (2015) W W Norton & Co Inc, p. 496 Mandelbrot, B., The Variation of Certain Speculative Prices The Variation of Certain Speculative Prices (1963) The Journal of Business, 36 (4), pp. 394-419 Marsh, I.W., Sarno, L., (2012) Handbook of Exchange Rates, , Handbook of Exchange Rates Medeiros, R., Júnior, J.L.R., O Relacionamento entre a Taxa de Câmbio R $/US $ e Fundamentos (2009) Insper Working Paper, , (No wpe_190). Insper Instituto de Ensino e Pesquisa. IBMEX Sao Paulo Meese, R., Rogoff, K., The Out-of-Sample Failure of Empirical Exchange Rate Models: Sampling Error or Misspecification? (1983) Exchange rates and international macroeconomics, pp. 67-112. , University of Chicago Press Murcia, A., Rojas, D., Determinantes de la tasa de cambio en Colombia: Un enfoque de microestructura de mercados (2015) Ensayos Sobre Política Económica, 33 (74), pp. 207-219 (2012) UK Brent Oil, , https://www.onefinancialmarkets.com/market-library/uk-brent-oil Ordoñez, M.L., Riesgo y volatilidad del tipo de cambio en Colombia, evaluación y pronóstico 2000-2006 (2016) Revista FACE, 2, pp. 33-57 Pacelli, V., Forecasting Exchange Rates: A Comparative Analysis (2012) International Journal of Business and Social Science, 3 (10), pp. 145-156 Panda, C., Narasimhan, V., Forecasting exchange rate better with artificial neural network (2007) Journal of Policy Modeling, 29 (2), pp. 227-236 Parisi, A., Parisi, F., Cañas, E., Reglas simples de analisis tecnico y modelos autprregresivos en el mercado cambiario chileno entre 1995 al 2001 (2002) Estudios de Administración, 9 (2), pp. 69-88 Pekta?, A.O., Kerem, H., ANN hybrid model versus ARIMA and ARIMAX models of runoff coefficient (2013) Journal of Hydrology, 500, pp. 21-36 Peter, D., Silvia, P., ARIMA vs ARIMAX-which approach is better to analyze and forecast macroeconomic time series? (2012) Proceedings of 30th International Conference Mathematical Methods in Economics, 2, pp. 136-140 Reboredo, J.C., Modelling oil price and exchange rate co-movements (2012) Journal of Policy Modeling, 34 (3), pp. 419-440 Rime, D., Sarno, L., Sojli, E., Exchange rate forecasting, order flow and macroeconomic information (2010) Journal of International Economics, 80 (1), pp. 72-88 Rojas, M.E., Duque, A.F., Colombia sobre el producto interno bruto, la inversión extranjera directa y la balanza comercial (2014) Escuela de Ingenieria de Antioquia, , http://repository.eia.edu.co/bitstream/11190/238/1/ADMO0817.pdf Samuelson, P.A., Proof that properly anticipated prices fluctuate randomly (1965) IMR Industrial Management Review, 6 (2), pp. 41-49 Serwa, D., Bohl, M.T., Financial contagion vulnerability and resistance: A comparison of European stock markets (2005) Economic Systems, 29 (3), pp. 344-362 Stein, J.L., Allen, P.R., (1997) Fundamental determinants of exchange rates, , United Kingdom: Clarendon Press, Oxford Syllignakis, M.N., Kouretas, G.P., Dynamic correlation analysis of financial contagion: Evidence from the Central and Eastern European markets (2011) International Review of Economics & Finance, 20 (4), pp. 717-732 Taylor, M.P., Editorial: Long-run purchasing power parity and real exchange rates: Introduction and overview (2009) Applied Economics Letters, 16 (1), pp. 1-4 Tosoni, G.A., Necessary Levels, Costs and Policies for International Reserves in Latin America (2011) Economía Mexicana Nueva Época, 20 (1), pp. 145-180. , http://ideas.repec.org/a/emc/ecomex/v20y2011i1p145-180.html Uribe, J., Jiménez, D., Fernández, J., Regímenes de volatilidad del tipo de cambio en Colombia e intervenciones de política (2015), 74 (100), pp. 1-31 Velásquez, D.J., González, L.M., Modelado del índice de tipo de cambio real colombiano usando redes neuronales artificiales (2006) Cuadernos de Administración, 19 (32), pp. 319-336. , http://www.redalyc.org/articulo.oa?id=20503213 Wu, C.C., Chung, H., Chang, Y.H., The economic value of co-movement between oil price and exchange rate using copula-based GARCH models (2012) Energy Economics, 34 (1), pp. 270-282 Zalduendo, J., Determinants of Venezuela's Equilibrium Real Exchange Rate (2006) IMF Working Paper, pp. 3-17. , WP/06/74 |
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Universidad Pablo de Olavide |
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Ingeniería Financiera |
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Facultad de Ingenierías |
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Universidad Pablo de Olavide |
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Revista de Metodos Cuantitativos para la Economia y la Empresa |
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Universidad de Medellín |
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Repositorio Institucional Universidad de Medellin |
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20192020-04-29T14:53:36Z2020-04-29T14:53:36Z1886516Xhttp://hdl.handle.net/11407/5665The 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.spaUniversidad Pablo de OlavideIngeniería FinancieraFacultad de Ingenieríashttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85077110612&partnerID=40&md5=743f984a25659ba72c23d8bd219027da28301341Abhyankar, A., Sarno, L., Valente, G., Exchange rates and fundamentals: Evidence on the economic value of predictability (2005) Journal of International Economics, 66 (2), pp. 325-348Andrews, B.H., Dean, M.D., Building ARIMA and ARIMAX Models for Predicting Long-Term Disability Benefit Application Rates in the Public / Private Sectors Sponsored by Society of Actuaries Health Section Prepared by University of Southern Maine (2013) Building ARIMA and ARIMAX Models for Predicting Long-Term Disability Benefit Application Rates in the Public/Private Sectors SponsoredAnggraeni, W., Vinarti, R.A., Kurniawati, Y.D., Performance Comparisons between Arima and Arimax Method in Moslem Kids Clothes Demand Forecasting: Case Study (2015) Procedia Computer Science, 72, pp. 630-637Babu, A.S., Reddy, B.A., Exchange Rate Forecasting using ARIMA, Neural Network and Fuzzy Neuron (2015) Journal of Stock & Forex Trading, 4 (3), pp. 1-5Bloomberg, L.P., (2017) Bloomberg Terminal, , https://www.bloomberg.com/, Stock last price from 1/1/11 to 06/30/17. Recuperado de:Bollerslev, T., Generalized autoregressive conditional heteroskedasticity (1986) Journal of Econometrics, 31 (3), pp. 307-327Box, G.E., Jenkins, G.M., (1970) Time series analysis, control, and forescasting, 3226 (3228), p. 10. , San Francisco, CA: Holden DayCardenas, M., La tasa de cambio en Colombia (1997) Cuadernos de Fedesarrollo, , No. 012740. BogotáCarr, P., Wu, L., Theory and evidence on the dynamic interactions between sovereign credit default swaps and currency options (2007) Journal of Banking and Finance, 31 (8), pp. 2383-2403Cassel, G., (1922) Money and foreign exchange after 1914, pp. 101-170. , London: Constable and Company LimitedChavarro, F., Política monetaria en Colombia, 1999-2000 (2008) Revista Criterio Libre, 9, pp. 73-93Chavarro, F., Grautoff, M., El trilema de la Banca Central Colombiana: Un problema intertemporal (2010) Criterio Libre, 8, pp. 15-30. , http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:No+Title#0, Recuperado de:Chiang, T.C., Jeon, B.N., Li, H., Dynamic correlation analysis of financial contagion: Evidence from Asian markets (2007) Journal of International Money and Finance, 26 (7), pp. 1206-1228Chinn, M.D., Meese, R.A., Banking on currency forecasts: How predictable is change in money (1995) Journal of International Economics, 38 (1-2), pp. 161-178Chong, M., Aguilar, R., (2016) Proyección de Series de Tiempo para el Consumo de la Energía Eléctrica a Clientes Residenciales en Ecuador, pp. 56-76. , 29(Julio)Davis, J.S., External debt and monetary policy autonomy (2017) Ensayos Sobre Política Económica, 35, pp. 53-63Echavarría, J.J., Misas, M., López, E., La Tasa de Cambio Real de Equilibrio en Colombia y su Desalineamiento: Estimación a través de un modelo SVEC (2007) Borradores de Economía, 472, pp. 2-37Echavarría, J.J., Vásquez, D., Villamizar, M., The Real Exchange Rate in Colombia: Too Far from Equilibrium (2005) Ensayos Sobre Política Económica, 49, pp. 134-191Ecopetrol, S.A., (2016), http://www.ecopetrol.com.co/wps/portal/es/ecopetrol-web/nuestra-empresa/quienes-somos/acerca-de-ecopetrol/nuestra-historia, (14 de junio). Recuperado de:Edwards, S., Savastano, M.A., Exchange Rates in Emerging Economies: What do we Know? What do we need to know? (1999) National Bureau of Economic Research Working Paper SeriesEhrmann, M., Fratzscher, M., Exchange rates and fundamentals: New evidence from real-time data (2005) Journal of International Money and Finance, 24 (2), pp. 317-341Engel, C., West, K.D., Exchange Rates and Fundamentals (2005) Journal of Political Economy, 113 (3), pp. 485-517Engle, R., Autoregressive Conditional Heteroscedasticity With Estimates of the Variance of United Kingdom Inflation1 (1982) Econometrica, 50 (4), pp. 987-1007Engle, R., Dynamic Conditional Correlation (2002) Journal of Business & Economic Statistics, 20 (3), pp. 339-350Evans, M.D.D., Order flows and the exchange rate disconnect puzzle (2010) Journal of International Economics, 80 (1), pp. 58-71Fahimifard, S.M., Homayounifar, M., Sabouhi, M., Moghaddamnia, A.R., Comparison of ANFIS, ANN, GARCH and ARIMA Techniques to Exchange Rate Forecasting (2009) Journal of Applied Sciences, 9 (20), pp. 3641-3651Fama, E.F., The Behavior of Stock-Market Prices (1965) The Journal of Business, 38 (1), pp. 34-105Fernández-Rodriguez, F., Sosvilla-Rivero, S., Andrada-Félix, J., Exchange-rate forecasts with simultaneous nearest-neighbour methods: Evidence from the EMS (1999) International Journal of Forecasting, 15, pp. 383-392Fernández, F., González, C., Sosvilla, S., On the profitability of technical trading rules based on artificial neural networks: (2000) Economics Letters, 69 (1), pp. 89-94Frenkel, J.A., Mussa, M.L., Chapter 14 Asset markets, exchange rates and the balance of payments (1985) Handbook of International Economics, 2, pp. 679-747Gioqinang, Z., Hu, M.Y., Neural network forecasting of the British Pound/US Dollar exchange rate (1998) Omega, 26 (4), pp. 495-506Gómez, J., Hernández, J.M., Composición cambiaria y Poder Adquisitivo de las reservas internacionales (2011) Borradores de Economía, Banco de La Republica, (654)González, C., (2003) Nuevas perspectivas del análisis técnico de los mercados bursátiles mediante el aprendizaje automático. Aplicaciones al índice general de la bolsa de Madrid. Resarch Gate, , http://hdl.handle.net/10553/2156, Recuperado de:Granger, C.W., Investigating Causal Relations by Econometric Models and Cross-spectral Methods (1986) Econometrica: Journal of the Econometric Society, 37 (3), pp. 424-438Hassan, M.K., Kayhan, S., Bayat, T., Does credit default swap spread affect the value of the Turkish LIRA against the U. S dollar? (2017) Borsa Istanbul Review, 17 (1), pp. 1-9Jalil, M.A., Misas, M., Evaluaciòn de pronòsticos del tipo de cambio utilizando redes neuronales y funciones de pèrdida asimètricas (2007) Revista Colombiana de Estadistica, 30 (1), pp. 143-161Julio, B., Yook, Y., Policy Uncertainty, Irreversibility, and Cross-Border Flows of Capital Federal Reserve Board of Governors (2016) Journal of International Economics, 103, pp. 13-26Kamruzzaman, J., Sarker, R.A., Forecasting of currency exchange rates using ANN: A case study (2003) Neural Networks and Signal Processing, 1, pp. 793-797Kim, B.-H., Kim, H.-K., Oh, K.-Y., The purchasing power parity of Southeast Asian currencies: A time-varying coefficient approach (2009) Economic Modelling, 26 (1), pp. 96-106Krugman, P.R., Obstfeld, M., Melitz, M.J., (2012) Economía international: Teoría y política, , PearsonLothian, J.R., Taylor, M.P., Real exchange rate behavior: The recent float from the perspective of the past two centuries (1996) Journal of Political Economy, 104 (3), pp. 488-509MacDonald, R., Marsh, I.W., On Fundamentals and Exchange Rates: A Casselian Perspective (1997) The Review of Economics and Statistics, 79 (4), pp. 655-664Majhi, R., Panda, G., Sahoo, G., Efficient prediction of exchange rates with low complexity artificial neural network models (2009) Expert Systems with Applications, 36 (1), pp. 181-189Malkiel, B.G., A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing (10th Edition) (2015) W W Norton & Co Inc, p. 496Mandelbrot, B., The Variation of Certain Speculative Prices The Variation of Certain Speculative Prices (1963) The Journal of Business, 36 (4), pp. 394-419Marsh, I.W., Sarno, L., (2012) Handbook of Exchange Rates, , Handbook of Exchange RatesMedeiros, R., Júnior, J.L.R., O Relacionamento entre a Taxa de Câmbio R $/US $ e Fundamentos (2009) Insper Working Paper, , (No wpe_190). Insper Instituto de Ensino e Pesquisa. IBMEX Sao PauloMeese, R., Rogoff, K., The Out-of-Sample Failure of Empirical Exchange Rate Models: Sampling Error or Misspecification? 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