Medición de la volatilidad en series de tiempo financieras: una evaluación a la tasa de cambio representativa del mercado (TRM) en Colombia

Existen diferentes métodos para la medición del agrupamiento de la volatilidad en las series financieras, en las cuales el supuesto sobre la distribución del error determina la estructura de la función de log verosimilitud. En este documento se explota la flexibilidad de los modelos ARCH para captur...

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Autores:: Montenegro, Roberto

Tipo de recurso:: Article of journal

Fecha de publicación:: 2010

Institución:: Universidad Católica de Colombia

Repositorio:: RIUCaC - Repositorio U. Católica

Idioma:: spa

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dc.title.spa.fl_str_mv	Medición de la volatilidad en series de tiempo financieras: una evaluación a la tasa de cambio representativa del mercado (TRM) en Colombia Measurement of volatility in financial time series: an evaluation of the representative exchange rate market (ERM) in Colombia
title	Medición de la volatilidad en series de tiempo financieras: una evaluación a la tasa de cambio representativa del mercado (TRM) en Colombia
spellingShingle	Medición de la volatilidad en series de tiempo financieras: una evaluación a la tasa de cambio representativa del mercado (TRM) en Colombia TRM ARCH GARCH IGARCH EGARCH TARCH MERCADO DE VALORES-COLOMBIA OPCIONES (FINANZAS)-COLOMBIA MERCADO DE CAPITALES-COLOMBIA
title_short	Medición de la volatilidad en series de tiempo financieras: una evaluación a la tasa de cambio representativa del mercado (TRM) en Colombia
title_full	Medición de la volatilidad en series de tiempo financieras: una evaluación a la tasa de cambio representativa del mercado (TRM) en Colombia
title_fullStr	Medición de la volatilidad en series de tiempo financieras: una evaluación a la tasa de cambio representativa del mercado (TRM) en Colombia
title_full_unstemmed	Medición de la volatilidad en series de tiempo financieras: una evaluación a la tasa de cambio representativa del mercado (TRM) en Colombia
title_sort	Medición de la volatilidad en series de tiempo financieras: una evaluación a la tasa de cambio representativa del mercado (TRM) en Colombia
dc.creator.fl_str_mv	Montenegro, Roberto
dc.contributor.advisor.spa.fl_str_mv	Engle, R.F.
dc.contributor.author.spa.fl_str_mv	Montenegro, Roberto
dc.subject.spa.fl_str_mv	TRM ARCH GARCH IGARCH EGARCH TARCH
topic	TRM ARCH GARCH IGARCH EGARCH TARCH MERCADO DE VALORES-COLOMBIA OPCIONES (FINANZAS)-COLOMBIA MERCADO DE CAPITALES-COLOMBIA
dc.subject.lemb.spa.fl_str_mv	MERCADO DE VALORES-COLOMBIA OPCIONES (FINANZAS)-COLOMBIA MERCADO DE CAPITALES-COLOMBIA
description	Existen diferentes métodos para la medición del agrupamiento de la volatilidad en las series financieras, en las cuales el supuesto sobre la distribución del error determina la estructura de la función de log verosimilitud. En este documento se explota la flexibilidad de los modelos ARCH para capturar los agrupamientos de la volatilidad de la Tasa Representativa del Mercado TRM colombiana. Los resultados indican que el modelo MA (1) en media y el modelo GARCH (1, 1) en varianza superan otro tipo de especificación, que trate de medir el agrupamiento de la volatilidad de la TRM colombiana
publishDate	2010
dc.date.issued.spa.fl_str_mv	2010-06
dc.date.accessioned.spa.fl_str_mv	2013-05-20T21:37:16Z
dc.date.available.spa.fl_str_mv	2013-05-20T21:37:16Z
dc.type.spa.fl_str_mv	Artículo de revista
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dc.identifier.citation.spa.fl_str_mv	Montenegro, R. (2010). Medición de la volatilidad en series de tiempo financieras: una evaluación a la tasa de cambio representativa del mercado (TRM) en Colombia. Revista Finanzas y Política Económica, Vol. 2 (1) Recuperado de http://editorial.ucatolica.edu.co/ojsucatolica/revistas_ucatolica/index.php/RFYPE/article/view/547/568
dc.identifier.issn.spa.fl_str_mv	2248-6046
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identifier_str_mv	Montenegro, R. (2010). Medición de la volatilidad en series de tiempo financieras: una evaluación a la tasa de cambio representativa del mercado (TRM) en Colombia. Revista Finanzas y Política Económica, Vol. 2 (1) Recuperado de http://editorial.ucatolica.edu.co/ojsucatolica/revistas_ucatolica/index.php/RFYPE/article/view/547/568 2248-6046
url	http://hdl.handle.net/10983/627
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dc.relation.ispartof.spa.fl_str_mv	Revista Finanzas y Política Económica, Vol. 2 no. 1 (ene.-jun. 2010); p. 126-130
dc.relation.references.spa.fl_str_mv	Andersen, T.G., Bollerslev, Tim, Diebold, Francis X, & Ebens, Heiko. “The Distribution of Realized Stock Return Volatility”. Journal of Financial Economics, 61: 43-76. 2001. Andersen, T.G., Bollerslev, Tim, Diebold, Francis X. & Labys, Paul. “Modelling and Forecasting Realized Volatility”. Econométrica, 71: 579-625. 2003. Andersen, T.G., Bollerslev, Tim, Diebold, F.X. & Labys, Paul. “The Distribution of Realized Exchange Rate Volatility”. Journal of the American Statistical Association, 96: 42-55. 2001. De Arce Borda, Rafael. 20 Years of Arch Modelling: a Survey of Different Models in the Family. Estudios de Economía Aplicada, 22(1). 2004. Bollerslev, Tim. “Modeling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Approach”. Review of Economics and Statistics, 72: 498-505. 1990. Bollerslev, Tim. “Generalized Autoregressive Conditional Heteroskedasticity” Journal of Econometrics, 31: 307-327. 1986. Bollerslev, Tim. “A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return”. Review of Economics and Statistics, 69 (3): 542-547. 1987. Bollerslev, Tim, R.Y. Chou & K.F. Kroner.“ARCH Models in Finance”. Journal of Econometrics, 52: 5-59. 1992. Bollerslev, Tim, Chou, Ray Y. & Kroner, Kenneth F. “ARCH Modeling in Finance: A Review of the Theory and Empirical Evidence”. Journal of Econometrics, 52: 5-59. Bollerslev, Tim, Engle, Robert, F. & Nelson, Daniel B. “ARCH Models”. Chapter 49 in Robert F. Engle and Daniel L. McFadden (eds.). Handbook of Econometrics, 4. Amsterdam: Elsevier Science B.V. 1994. Bollerslev, Tim &. Wooldridge, Jeffrey, M. “Quasi-Maximum Likelihood Estimation and Inference in Dynamic Models with Time Varying Covariances”. Econometric Reviews, 11: 143-172. 1992. Bollerslev, Tim. “Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts”. International Economic Review, 39: 885-905. 1998. Campbell, J.Y., Lo, A.W. & MacKinlay, A.C. The Econometrics of Financial Markets Princeton University Press. 1997. Ding, Zhuanxin, Granger, C. W. J. & Engle, R. F. “A Long Memory Property of Stock Market Returns and a New Model”. Journal of Empirical Finance, 1: 83-106. 1993. Engle, R.F. & Bollerslev, Tim.“Modelling the Persistence of Conditional Variances”. Econometric Reviews, 5: 1-50. 1986. Engle, R.F. & Bollerslev, Tim.“Modelling the Persistence of Conditional Variances”. Econometric Reviews, 5: 1-50. 1986. Engle, Robert F., Lilien, David M. & Robins, Russell P. “Estimating Time Varying Risk Premia in the Term Structure: The ARCH-M Model”. Econométrica, 55: 391-407. 1987. Engle, R.F. ARCH Selected Readings. Oxford University Press. 1995. Glosten, L. R., Jaganathan, R. & Runkle, D. “On the Relation between the Expected Value and the Volatility of the Normal Excess Return on Stocks”. Journal of Finance, 48: 1779-1801. 1993. Glosten, Lawrence R., Jagannathan, Ravi & Runkle, David E. “On the relation between the expected value and the volatility of the nominal excess return on stocks”. Staff Report 157, Federal Reserve Bank of Minneapolis. 1993. Nelson, Daniel B. “Conditional Heteroskedasticity in Asset Returns: A New Approach”. Econométrica, 59: 347-370. 1991. Schwert, W. “Stock Volatility and Crash of `87”. Review of Financial Studies, 3: 77-102. Taylor, S. Modeling Financial Time Series, New York: John Wiley & Sons. 1986. Vrontos, D., Dellaportas, P. & Politis, D. “Full-factor Multivariate GARCH model. Econometrics Journal, 6: 312-334. 2003. Zakoian, Jean-Michel. “Threshold heteroskedastic models”. Journal of Economic Dynamics and Control, 18(5): 931-955. 1994.
dc.rights.spa.fl_str_mv	Derechos Reservados - Universidad Católica de Colombia, 2010
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spelling	Engle, R.F. e66aa866-cf6d-48a7-b8e8-4639049c4f58Montenegro, Roberto846941a9-4132-4c84-921d-dbd37dda8a6d-12013-05-20T21:37:16Z2013-05-20T21:37:16Z2010-06Existen diferentes métodos para la medición del agrupamiento de la volatilidad en las series financieras, en las cuales el supuesto sobre la distribución del error determina la estructura de la función de log verosimilitud. En este documento se explota la flexibilidad de los modelos ARCH para capturar los agrupamientos de la volatilidad de la Tasa Representativa del Mercado TRM colombiana. Los resultados indican que el modelo MA (1) en media y el modelo GARCH (1, 1) en varianza superan otro tipo de especificación, que trate de medir el agrupamiento de la volatilidad de la TRM colombianaThere are different methods to measure the volatility regarding clustering in financial series, in which the assumption of the error distribution determines the structure of the log-likelihood function. This paper analyses the flexibility of ARCH models to capture the volatility of TRM in Colombia. The results show that the MA (1) model in mean and GARCH (1, 1) model in variance outperform another kind of specification, which tries to measure the volatility clustering of the TRM in Colombiaapplication/pdfMontenegro, R. (2010). Medición de la volatilidad en series de tiempo financieras: una evaluación a la tasa de cambio representativa del mercado (TRM) en Colombia. Revista Finanzas y Política Económica, Vol. 2 (1) Recuperado de http://editorial.ucatolica.edu.co/ojsucatolica/revistas_ucatolica/index.php/RFYPE/article/view/547/5682248-6046http://hdl.handle.net/10983/627spaRevista Finanzas y Política Económica, Vol. 2 no. 1 (ene.-jun. 2010); p. 126-130Andersen, T.G., Bollerslev, Tim, Diebold, Francis X, & Ebens, Heiko. “The Distribution of Realized Stock Return Volatility”. Journal of Financial Economics, 61: 43-76. 2001.Andersen, T.G., Bollerslev, Tim, Diebold, Francis X. & Labys, Paul. “Modelling and Forecasting Realized Volatility”. Econométrica, 71: 579-625. 2003.Andersen, T.G., Bollerslev, Tim, Diebold, F.X. & Labys, Paul. “The Distribution of Realized Exchange Rate Volatility”. Journal of the American Statistical Association, 96: 42-55. 2001.De Arce Borda, Rafael. 20 Years of Arch Modelling: a Survey of Different Models in the Family. Estudios de Economía Aplicada, 22(1). 2004.Bollerslev, Tim. “Modeling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Approach”. Review of Economics and Statistics, 72: 498-505. 1990.Bollerslev, Tim. “Generalized Autoregressive Conditional Heteroskedasticity” Journal of Econometrics, 31: 307-327. 1986.Bollerslev, Tim. “A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return”. Review of Economics and Statistics, 69 (3): 542-547. 1987.Bollerslev, Tim, R.Y. Chou & K.F. Kroner.“ARCH Models in Finance”. Journal of Econometrics, 52: 5-59. 1992.Bollerslev, Tim, Chou, Ray Y. & Kroner, Kenneth F. “ARCH Modeling in Finance: A Review of the Theory and Empirical Evidence”. Journal of Econometrics, 52: 5-59.Bollerslev, Tim, Engle, Robert, F. & Nelson, Daniel B. “ARCH Models”. Chapter 49 in Robert F. Engle and Daniel L. McFadden (eds.). Handbook of Econometrics, 4. Amsterdam: Elsevier Science B.V. 1994.Bollerslev, Tim &. Wooldridge, Jeffrey, M. “Quasi-Maximum Likelihood Estimation and Inference in Dynamic Models with Time Varying Covariances”. Econometric Reviews, 11: 143-172. 1992.Bollerslev, Tim. “Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts”. International Economic Review, 39: 885-905. 1998.Campbell, J.Y., Lo, A.W. & MacKinlay, A.C. The Econometrics of Financial Markets Princeton University Press. 1997.Ding, Zhuanxin, Granger, C. W. J. & Engle, R. F. “A Long Memory Property of Stock Market Returns and a New Model”. Journal of Empirical Finance, 1: 83-106. 1993.Engle, R.F. & Bollerslev, Tim.“Modelling the Persistence of Conditional Variances”. Econometric Reviews, 5: 1-50. 1986.Engle, R.F. & Bollerslev, Tim.“Modelling the Persistence of Conditional Variances”. Econometric Reviews, 5: 1-50. 1986.Engle, Robert F., Lilien, David M. & Robins, Russell P. “Estimating Time Varying Risk Premia in the Term Structure: The ARCH-M Model”. Econométrica, 55: 391-407. 1987.Engle, R.F. ARCH Selected Readings. Oxford University Press. 1995.Glosten, L. R., Jaganathan, R. & Runkle, D. “On the Relation between the Expected Value and the Volatility of the Normal Excess Return on Stocks”. Journal of Finance, 48: 1779-1801. 1993.Glosten, Lawrence R., Jagannathan, Ravi & Runkle, David E. “On the relation between the expected value and the volatility of the nominal excess return on stocks”. Staff Report 157, Federal Reserve Bank of Minneapolis. 1993.Nelson, Daniel B. “Conditional Heteroskedasticity in Asset Returns: A New Approach”. Econométrica, 59: 347-370. 1991.Schwert, W. “Stock Volatility and Crash of `87”. Review of Financial Studies, 3: 77-102.Taylor, S. Modeling Financial Time Series, New York: John Wiley & Sons. 1986.Vrontos, D., Dellaportas, P. & Politis, D. “Full-factor Multivariate GARCH model. Econometrics Journal, 6: 312-334. 2003.Zakoian, Jean-Michel. “Threshold heteroskedastic models”. Journal of Economic Dynamics and Control, 18(5): 931-955. 1994.Derechos Reservados - Universidad Católica de Colombia, 2010info:eu-repo/semantics/openAccessAtribución-NoComercial 4.0 Internacional (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/http://purl.org/coar/access_right/c_abf2TRMARCHGARCHIGARCHEGARCHTARCHMERCADO DE VALORES-COLOMBIAOPCIONES (FINANZAS)-COLOMBIAMERCADO DE CAPITALES-COLOMBIAMedición de la volatilidad en series de tiempo financieras: una evaluación a la tasa de cambio representativa del mercado (TRM) en ColombiaMeasurement of volatility in financial time series: an evaluation of the representative exchange rate market (ERM) in ColombiaArtículo de 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

Medición de la volatilidad en series de tiempo financieras: una evaluación a la tasa de cambio representativa del mercado (TRM) en Colombia

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