Titulo:

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

Sumario:

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.

Guardado en:

2248-6046

2011-7663

2

2009-01-01

125

132

Roberto Montenegro - 2010

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spelling 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.
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.
There 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 Colombia.
Montenegro, Roberto
Trm
Arch
Garch
Igarch
Egarch
Tarch
Trm
Arch
Garch
Igarch
Egarch
Tarch
2
1
Artículo de revista
Journal article
2010-01-01T00:00:00Z
2010-01-01T00:00:00Z
2009-01-01
application/pdf
Universidad Católica de Colombia
Revista Finanzas y Política Económica
2248-6046
2011-7663
https://revfinypolecon.ucatolica.edu.co/article/view/547
https://revfinypolecon.ucatolica.edu.co/article/view/547
spa
https://creativecommons.org/licenses/by-nc-sa/4.0/
Roberto Montenegro - 2010
125
132
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. Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive. 2002.
Engle, R.F. Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of UK Inflation. Econométrica, 50: 987-1008. 1982.
Engle, R.F. & Bollerslev, Tim.Modelling the Persistence of Conditional Variances?. Econometric Reviews, 5: 1-50. 1986.
Engle, Robert F. Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of U.K. Inflation. Econométrica, 50: 987-1008. 1982.
Engle, Robert F. & Bollerslev, Tim. Modeling the Persistence of Conditional Variances. Econometric Reviews, 5: 1-50. 1996.
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.
https://revfinypolecon.ucatolica.edu.co/article/download/547/568
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http://purl.org/coar/resource_type/c_6501
http://purl.org/redcol/resource_type/ARTREF
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Text
Publication
institution UNIVERSIDAD CATÓLICA DE COLOMBIA
thumbnail https://nuevo.metarevistas.org/UNIVERSIDADCATOLICADECOLOMBIA/logo.png
country_str Colombia
collection Revista Finanzas y Política Económica
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.
Montenegro, Roberto
Arch
Garch
Igarch
Egarch
Tarch
Arch
Garch
Igarch
Egarch
Tarch
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.
title_eng Measurement of volatility in financial time series : an evaluation of the representative exchange rate market (ERM) in 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.
description_eng There 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 Colombia.
author Montenegro, Roberto
author_facet Montenegro, Roberto
topic Arch
Garch
Igarch
Egarch
Tarch
Arch
Garch
Igarch
Egarch
Tarch
topic_facet Arch
Garch
Igarch
Egarch
Tarch
Arch
Garch
Igarch
Egarch
Tarch
topicspa_str_mv Arch
Garch
Igarch
Egarch
Tarch
citationvolume 2
citationissue 1
publisher Universidad Católica de Colombia
ispartofjournal Revista Finanzas y Política Económica
source https://revfinypolecon.ucatolica.edu.co/article/view/547
language spa
format Article
rights https://creativecommons.org/licenses/by-nc-sa/4.0/
Roberto Montenegro - 2010
info:eu-repo/semantics/openAccess
http://purl.org/coar/access_right/c_abf2
references 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. Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive. 2002.
Engle, R.F. Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of UK Inflation. Econométrica, 50: 987-1008. 1982.
Engle, R.F. & Bollerslev, Tim.Modelling the Persistence of Conditional Variances?. Econometric Reviews, 5: 1-50. 1986.
Engle, Robert F. Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of U.K. Inflation. Econométrica, 50: 987-1008. 1982.
Engle, Robert F. & Bollerslev, Tim. Modeling the Persistence of Conditional Variances. Econometric Reviews, 5: 1-50. 1996.
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.
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