Modelos de transferencia entre series de tiempo con valores positivos y aplicación a la transmisión de volatilidades

ilustraciones, diagramas, tablas

Autores:: Cataño Ospina, Jaider Andrés

Tipo de recurso:

Fecha de publicación:: 2021

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: spa

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dc.title.spa.fl_str_mv	Modelos de transferencia entre series de tiempo con valores positivos y aplicación a la transmisión de volatilidades
dc.title.translated.eng.fl_str_mv	Transfer models between time series with positive values and their application to the transmission of volatilities
title	Modelos de transferencia entre series de tiempo con valores positivos y aplicación a la transmisión de volatilidades
spellingShingle	Modelos de transferencia entre series de tiempo con valores positivos y aplicación a la transmisión de volatilidades 330 - Economía::332 - Economía financiera 330 - Economía::339 - Macroeconomía y temas relacionados 510 - Matemáticas::519 - Probabilidades y matemáticas aplicadas Estadística Time-series analysis Análisis de series de tiempo Series de tiempo Transmisión Volatilidad Causalidad Time series Transmission Causality Volatility
title_short	Modelos de transferencia entre series de tiempo con valores positivos y aplicación a la transmisión de volatilidades
title_full	Modelos de transferencia entre series de tiempo con valores positivos y aplicación a la transmisión de volatilidades
title_fullStr	Modelos de transferencia entre series de tiempo con valores positivos y aplicación a la transmisión de volatilidades
title_full_unstemmed	Modelos de transferencia entre series de tiempo con valores positivos y aplicación a la transmisión de volatilidades
title_sort	Modelos de transferencia entre series de tiempo con valores positivos y aplicación a la transmisión de volatilidades
dc.creator.fl_str_mv	Cataño Ospina, Jaider Andrés
dc.contributor.advisor.none.fl_str_mv	Giraldo Gómez, Norman Diego
dc.contributor.author.none.fl_str_mv	Cataño Ospina, Jaider Andrés
dc.subject.ddc.spa.fl_str_mv	330 - Economía::332 - Economía financiera 330 - Economía::339 - Macroeconomía y temas relacionados 510 - Matemáticas::519 - Probabilidades y matemáticas aplicadas
topic	330 - Economía::332 - Economía financiera 330 - Economía::339 - Macroeconomía y temas relacionados 510 - Matemáticas::519 - Probabilidades y matemáticas aplicadas Estadística Time-series analysis Análisis de series de tiempo Series de tiempo Transmisión Volatilidad Causalidad Time series Transmission Causality Volatility
dc.subject.lem.none.fl_str_mv	Estadística
dc.subject.lemb.none.fl_str_mv	Time-series analysis Análisis de series de tiempo
dc.subject.proposal.spa.fl_str_mv	Series de tiempo Transmisión Volatilidad Causalidad
dc.subject.proposal.eng.fl_str_mv	Time series Transmission Causality
dc.subject.proposal.fra.fl_str_mv	Volatility
description	ilustraciones, diagramas, tablas
publishDate	2021
dc.date.accessioned.none.fl_str_mv	2021-11-10T15:30:13Z
dc.date.available.none.fl_str_mv	2021-11-10T15:30:13Z
dc.date.issued.none.fl_str_mv	2021-11-09
dc.type.spa.fl_str_mv	Trabajo de grado - Maestría
dc.type.driver.spa.fl_str_mv	info:eu-repo/semantics/masterThesis
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dc.type.content.spa.fl_str_mv	Text
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status_str	acceptedVersion
dc.identifier.uri.none.fl_str_mv	https://repositorio.unal.edu.co/handle/unal/80675
dc.identifier.instname.spa.fl_str_mv	Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv	Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv	https://repositorio.unal.edu.co/
url	https://repositorio.unal.edu.co/handle/unal/80675 https://repositorio.unal.edu.co/
identifier_str_mv	Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv	spa
language	spa
dc.relation.references.spa.fl_str_mv	Agresti, Alan. 2015. Foundations of linear and generalized linear models. John Wiley & Sons. Akaike, Hirotugu. 1974. A new look at the statistical model identification. IEEE transactions on automatic control, 19(6), 716–723. Alves, Mariane B, Gamerman, Dani, & Ferreira, Marco A. 2010. Transfer functions in dynamic generalized linear models. Statistical Modelling, 10(1), 3–40. Andel, Martin. 1991. Non-negative linear processes. Applications of Mathematics, Vol. 36(4), 277–283. Ardia, David, & Hoogerheide, Lennart F. 2010. Bayesian estimation of the garch (1, 1) model with student-t innovations. The R Journal, 2(2), 41–47. Ardia, David, et al. 2008. Financial risk management with Bayesian estimation of GARCH models. Vol. 18. Springer Baaske, Markus. 2017. Multivariate GARCH models: a survey. Journal of applied econometrics.Estimation. R package version 0.16-6. https://CRAN.R--project.org/package=qle. Balli, Faruk, Balli, Hatice O, Louis, Rosmy Jean, & Vo, Tuan Kiet. 2015. The transmission of market shocks and bilateral linkages: Evidence from emerging economies. International Review of Financial Analysis, 42, 349–357. Bauwens, L., Laurent, S., & Rombouts, J. V. 2006. Multivariate GARCH models: a survey. Journal of applied econometrics, 21(1), 79–109. Beirne, J., G. M. Caporale M. Schulze-Ghattas, & Spagnolo, N. 2013. Volatility Spillovers and Contagion from Mature to Emerging Stock Markets. Review of International Economics, 21(5), 1060–1075. Benjamin, M. A., Rigby, R. A., & Stasinopoulos, D. M. 2003. Generalized autoregressive moving average models. Journal of the American Statistical association, 98(461), 214– 223. BoIlerslev, T. 1986. Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 69, 307–327. Borda Ángel, Juan Pablo, et al. Comparación de metodologías de valor en riesgo (VaR), sobre un portafolio de activos financieros. B.S. thesis, Universidad de La Sabana. Boubaker, Heni, & Raza, Syed Ali. 2016. On the dynamic dependence and asymmetric comovement between the US and Central and Eastern European transition markets. Physica A: Statistical Mechanics and its Applications, 459, 9–23. Bougerol, Ph., & Picard, N. 1992. Stationarity of Garch processes and of some nonnegative time series. Journal of econometrics, 52(1-2), 115–127. Clements, Hurn., & Volkov, V. V. 2015. Volatility transmission in global financial markets. Journal of Empirical Finance, 32, 3–18. Cox, David Roxbee, & Snell, E Joyce. 2018. Analysis of binary data. Routledge. Czado, C. 2018. Lecture Slides on GLM. Lehrstuhl für Mathematische Statistik. Fakultät für Mathematik Technische Universität München. Debaly, M. Z., & Truquet, L. 2019. Iterations of dependent random maps and exogeneity in nonlinear dynamics. arXiv preprint arXiv:1908.00845. Demirhan, H. 2020. dLagM: An R package for distributed lag models and ARDL bounds testing. 15(2), https://doi.org/10.1371/journal.pone.0228812. Dickey, David A, & Fuller, Wayne A. 1979. Distribution of the estimators for autoregressive time series with a unit root. Journal of the American statistical association, 74(366a), 427–431. Emenike, K. O. 2014. Volatility transmission between stock and foreign exchange markets: Evidence from Nigeria. Journal of Banking and Financial Economics, 1 (1), 59–72. Engle, R. F., Ito, T., & Lin, W. L. 1988. Meteor showers or heat waves? Heteroskedastic intra-daily volatility in the foreign exchange market. (No. w2609, National Bureau of Economic Research. Campani, C. H., & Durães, A. G. D. S. 2018. Forecasting USD-BRL Currency Rate Volatility using Realized and Implied Volatilities Data. Estudos Econômicos (São Paulo), 48(4), 687–719. Clements, Hurn., & Volkov, V. V. 2015. Volatility transmission in global financial markets. Journal of Empirical Finance, 32, 3–18. Fleming, Jeff, Kirby, Chris, & Ostdiek, Barbara. 2008. The specification of GARCH models with stochastic covariates. Journal of Futures Markets: Futures, Options, and Other Derivative Products, 28(10), 911–934. Fleming, J., Kirby C. Ostdiek B. 2002. No Contagion, Only Interdependence: Measuring Stock Market Comovements. The Journal of Finance, 57(5), 2223–2261. Francq, Christian, & Zakoian, Jean-Michel. 2019. GARCH models: structure, statistical inference and financial applications. John Wiley & Sons. Francq, C. Thieu, L. Q. 2019. QML inference for volatility models with covariates. Econometric Theory, 35(1), 37–72. Galeano-González, David Andrés. 2015. A transfer function model for volatilities between water inflows and spot prices for Colombian electricity market. Master thesis, Universidad Nacional de Colombia – Sede Medellín, http://bdigital.unal.edu.co/49539/. Gamba-Santamaria, Santiago, Gomez-Gonzalez, Jose Eduardo, Hurtado-Guarin, Jorge Luis, & Melo-Velandia, Luis Fernando. 2017. Stock market volatility spillovers: Evidence for Latin America. Finance Research Letters, 20, 207–216. Garzón, Miller J Ariza, & Lozano, Javier B Cadena. 2014. Identificación de relaciones entre variables de política económica en Colombia a través de funciones de correlación cruzada. Cuadernos de Administración, 30(51), 36–48. Ghalanos, A. 2020. Introduction to the rugarch package. Version 1.3-8, Technical report v. Available at http://cran. r–project. org/web/packages/rugarch. Ghalanos, Alexios, Ghalanos, Maintainer Alexios, & Rcpp, LinkingTo. 2019. Package rugarch. Giraitis, Liudas, Kokoszka, Piotr, Leipus, Remigijus, & Teyssiére, Gilles. 2003. Rescaled variance and related tests for long memory in volatility and levels. Journal of econometrics, 112(2), 265–294. Gomes, M., & Chaibi, A. 2014. Volatility Spillovers Between Oil Prices And Stock Returns: A Focus On Frontier Markets. Journal of Applied Business Research (JABR), 30(2), 509–526. Granger, Clive WJ. 1969. Investigating causal relations by econometric models and crossspectral methods. Econometrica: journal of the Econometric Society, 424–438. Guesmi, Khaled, & Goutte, Stephane. 2020. Risk Factors and Contagion in Commodity Markets and Stocks Markets. World Scientific. Han, H. 2007. GARCH (1, 1) Process with Persistent Covariates. Citeseer Han, H., & Kristensen, D. 2015. Semiparametric multiplicative GARCH-X model: Adopting economic variables to explain volatility.Toulouse, France: Toulouse School of Economics. Hassler, U., & Wolters, J. 2006. Autoregressive distributed lag models and cointegration. In Modern Econometric Analysis. Heidelberg: Springer, Berlin. Hastie, T.J., & Tibshirani, R. 1990. Generalized Additive Models. London: hapman and Hall. Judge, G. G.and Hill, R. C.and Griffiths-W.and Lutkepohl H., & Lee, T. C. 1982. Introduction to the Theory and Practice of Econometrics. John Wiley and Sons. Kanas, Angelos. 1998. Volatility spillovers across equity markets: European evidence. Applied financial economics, 8(3), 245–256. Kiviaho, Jarno, Nikkinen, Jussi, Piljak, Vanja, & Rothovius, Timo. 2014. The co-movement dynamics of European frontier stock markets. European Financial Management, 20(3), 574–595. Koutmos, Gregory, & Booth, G Geoffrey. 1995. Asymmetric volatility transmission in international stock markets. Journal of international Money and Finance, 14(6), 747–762. Kwiatkowski, Denis, Phillips, Peter CB, Schmidt, Peter, & Shin, Yongcheol. 1992. Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? Journal of econometrics, 54(1-3), 159–178. Le Quyen, Thieu. 2016. Infèrence de modèles conditionnellement hètèroscèdastiques avec variables exogènes [math.ST]. Ph.D. thesis. Li, W.K. 1994. Time Series Models Based on Generalized Linear Models: Some Further Results. Biometrics, Vol. 50, No. 2, 506–511. Lin, W. L., Engle, R. F., & Ito, T. 1994. Do bulls and bears move across borders? International transmission of stock returns and volatility. Review of financial studies, 7(3), 507–538. Lo, Andrew W. 1991. Long-term memory in stock market prices. Econometrica: Journal of the Econometric Society, 1279–1313. Longerstaey, Jacques, & Spencer, Martin. 1996. Riskmetricstm: technical document. Morgan Guaranty Trust Company of New York: New York, 51, 54. Lopez, R. 2015. Do stylized facts of equity-based volatility indices apply to fixed-income volatility indices? Evidence from the US Treasury market. International Review of Financial Analysis, 42, 292–303. Lunn, DJ., Thomas, A., Best, N., & D, Spiegelhalter. 1972. Generalized linear models. Journal of the Royal Statistical Society: Series A (General), 135(3), 370–384. McCullagh, P., & Nelder, J.A. 1989. Generalized Linear Models. London: Chapman and Hall. Nana, G. A. N., Korn, R., & Erlwein-Sayer, C. 2013. GARCH-extended models: theoretical properties and applications. arXiv preprint arXiv:1307.6685. Newey, Whitney K, & West, Kenneth D. 1987. Hypothesis testing with efficient method of moments estimation. International Economic Review, 777–787. Pesaran, M. H., & Pick, A. 2007. Econometric issues in the analysis of contagion. Journal of Economic Dynamics and Control, 31(4), 1245–1277. Phillips, Peter CB, & Perron, Pierre. 1988. Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. Regino, A. 2006. Estimación y Comparación del Efecto de Asimetría en Modelos GJR, con Aplicaciones. Tesis de Maestría en Estadística. Escuela de Estadística. M.Phil. thesis, Universidad Nacional de Colombia-Sede Medellín. Rocha, A. V., & Cribari-Neto, F. 2009. Beta autoregressive moving average models. Test, 18(3), 529. Rodríguez Castellanos, Arturo, Urionabarrenetxea Zabalandikoetxea, Sara, & San Martín Albizuri, Nerea. 2008. Crisis financieras y globalización: un análisis de sus factores determinantes. Problemas del desarrollo, 39(153), 159–183. Ruppert, D., Wand M. P., & Carroll, R. J. 2003. Semiparametric Regression. Cambridge Series in Statistical and Probabilistic Mathematics. Cambridge: Cambridge University: 12. Serra, T. 2011. Volatility spillovers between food and energy markets: a semiparametric approach. Energy Economics, 33(6), 1155–1164. Shaikh, Imlak. 2021. Impact of COVID-19 pandemic on the energy markets. Economic Change and Restructuring, 1–52. Shepard, N. 1995. Generalized linear autoregressions Economics Working Papers. University of Oxford: Nuffield College. Soriano, P., & Climent, F. 2006. Volatility transmission models: a survey. Revista de economfinanciera, 10), 32–81. Straumann, D., & Mikosch, T. 2006. Quasi-Maximum-Likelihood Estimation in Conditionally Heteroscedastic Time Series: A Stochastic Recurrence Equations Approach. The Annals of Statistics, Vol. 34, No. 5, 2449–2495. Subba Rao, S. 2015. A course in Time Series Analysis. En https://www.stat.tamu.edu/ ~suhasini/teaching673/time_series.pdf. Tsai, H., & Chan, K. S. 2007. A Note on Non-Negative Arma Processes. Journal of Time Series Analysis, 28(3), 350–360. Tsay, Ruey S. 2005. Analysis of financial time series. John Wiley and Sons. Wood, S.N. 2017. Generalized Additive Models: An Introduction with R. (2nd edition). Chapman and Hall/CRC. Wuertz, Diethelm, Setz, Tobias, Chalabi, Yohan, Boudt, Chris, Chausse, Pierre, Miklovac, Michal, Setz, Maintainer Tobias, & RUnit, Suggests. 2013. Package fGarch. Tech. rept. Technical report, working paper/manual, 09.11. 2009. URL https://cran.r-project.org/. Zanobetti, A., Wand, M. P., Schwartz, J., & Ryan, L. M. 2000. Generalized additive distributed lag models: quantifying mortality displacement. Biostatistics, 1(3), 279–292. Zeger, Scott L., & Qaqish, Bahjat. 1988. Markov Regression Models for Time Series: A Quasi-Likelihood Approach. Biometrics, 44(4), 1019–1031. McFadden, Daniel. 1974. Conditional Logit Analysis of Qualitative Choice Behavior" in P. Zarembka Eds. Frontiers in Econometrics, New York Acedemic press.
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dc.publisher.spa.fl_str_mv	Universidad Nacional de Colombia
dc.publisher.program.spa.fl_str_mv	Medellín - Ciencias - Maestría en Ciencias - Estadística
dc.publisher.department.spa.fl_str_mv	Escuela de estadística
dc.publisher.faculty.spa.fl_str_mv	Facultad de Ciencias
dc.publisher.place.spa.fl_str_mv	Medellín, Colombia
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spelling	Reconocimiento 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Giraldo Gómez, Norman Diego1fe8759b9fc1218bec22a4b4a06a0ff7Cataño Ospina, Jaider Andrés375824927c7c3008b87853e4cd78c3d92021-11-10T15:30:13Z2021-11-10T15:30:13Z2021-11-09https://repositorio.unal.edu.co/handle/unal/80675Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramas, tablasSe exponen diferentes modelos de transferencia entre series de tiempo con valores positivos, el problema principal que aborda este trabajo es la revisión de modelos para transferencia de volatilidades unidireccionales GARCH-X, GLM-GAMMA, G-ARMA y ARDL, para luego con cada modelo realizar dos aplicaciones sobre transmisión de volatilidades, la primera aplicación es sobre la influencia de las volatilidades del precio en dólares del barril de referencia WTI en las del COLCAP y la otra aplicación de las volatilidades de los índices bursátiles pertenecientes al grupo que conforma el Mercado Integrado Latinoamericano (MILA) sobre las del COLCAP. Por último, se realizó un análisis comparativo de los resultados obtenidos, con el fin de determinar cuál modelo captura mejor el efecto de transmisión. (Texto tomado de la fuente)In this thesis different transfer models between time series with positive values are studied. The main problem is the review of unidireccional models for volatility transfer as the GARCH-X, GLM-GAMMA, G-ARMA and ARDL models. Then, with each model, we analyze two applications on the transmission of volatilities, the first application is on the influence of the volatilities of the dollar price of the WTI reference barrel on those of the COLCAP and the other application of the volatilities of the stock indices belonging to the group that makes up the Latin American Integrated Market (MILA) over those of COLCAP. Finally, a comparative analysis of the results obtained is carried out, in order to determine which model best captures the transmission effect.MaestríamaestríaMétodos Estadísticos en Finanzas y ActuariaÁrea Curricular Estadísticaxv, 66 páginasapplication/pdfspaUniversidad Nacional de ColombiaMedellín - Ciencias - Maestría en Ciencias - EstadísticaEscuela de estadísticaFacultad de CienciasMedellín, ColombiaUniversidad Nacional de Colombia - Sede Medellín330 - Economía::332 - Economía financiera330 - Economía::339 - Macroeconomía y temas relacionados510 - Matemáticas::519 - Probabilidades y matemáticas aplicadasEstadísticaTime-series analysisAnálisis de series de tiempoSeries de tiempoTransmisiónVolatilidadCausalidadTime seriesTransmissionCausalityVolatilityModelos de transferencia entre series de tiempo con valores positivos y aplicación a la transmisión de volatilidadesTransfer models between time series with positive values and their application to the transmission of volatilitiesTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMAgresti, Alan. 2015. Foundations of linear and generalized linear models. John Wiley & Sons.Akaike, Hirotugu. 1974. A new look at the statistical model identification. IEEE transactions on automatic control, 19(6), 716–723.Alves, Mariane B, Gamerman, Dani, & Ferreira, Marco A. 2010. Transfer functions in dynamic generalized linear models. Statistical Modelling, 10(1), 3–40.Andel, Martin. 1991. Non-negative linear processes. Applications of Mathematics, Vol. 36(4), 277–283.Ardia, David, & Hoogerheide, Lennart F. 2010. Bayesian estimation of the garch (1, 1) model with student-t innovations. The R Journal, 2(2), 41–47.Ardia, David, et al. 2008. Financial risk management with Bayesian estimation of GARCH models. Vol. 18. SpringerBaaske, Markus. 2017. Multivariate GARCH models: a survey. Journal of applied econometrics.Estimation. R package version 0.16-6. https://CRAN.R--project.org/package=qle.Balli, Faruk, Balli, Hatice O, Louis, Rosmy Jean, & Vo, Tuan Kiet. 2015. The transmission of market shocks and bilateral linkages: Evidence from emerging economies. International Review of Financial Analysis, 42, 349–357.Bauwens, L., Laurent, S., & Rombouts, J. V. 2006. Multivariate GARCH models: a survey. Journal of applied econometrics, 21(1), 79–109.Beirne, J., G. M. Caporale M. Schulze-Ghattas, & Spagnolo, N. 2013. Volatility Spillovers and Contagion from Mature to Emerging Stock Markets. Review of International Economics, 21(5), 1060–1075.Benjamin, M. A., Rigby, R. A., & Stasinopoulos, D. M. 2003. Generalized autoregressive moving average models. Journal of the American Statistical association, 98(461), 214– 223.BoIlerslev, T. 1986. Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 69, 307–327.Borda Ángel, Juan Pablo, et al. Comparación de metodologías de valor en riesgo (VaR), sobre un portafolio de activos financieros. B.S. thesis, Universidad de La Sabana.Boubaker, Heni, & Raza, Syed Ali. 2016. On the dynamic dependence and asymmetric comovement between the US and Central and Eastern European transition markets. Physica A: Statistical Mechanics and its Applications, 459, 9–23.Bougerol, Ph., & Picard, N. 1992. Stationarity of Garch processes and of some nonnegative time series. Journal of econometrics, 52(1-2), 115–127.Clements, Hurn., & Volkov, V. V. 2015. Volatility transmission in global financial markets. Journal of Empirical Finance, 32, 3–18.Cox, David Roxbee, & Snell, E Joyce. 2018. Analysis of binary data. Routledge.Czado, C. 2018. Lecture Slides on GLM. Lehrstuhl für Mathematische Statistik. Fakultät für Mathematik Technische Universität München.Debaly, M. Z., & Truquet, L. 2019. Iterations of dependent random maps and exogeneity in nonlinear dynamics. arXiv preprint arXiv:1908.00845.Demirhan, H. 2020. dLagM: An R package for distributed lag models and ARDL bounds testing. 15(2), https://doi.org/10.1371/journal.pone.0228812.Dickey, David A, & Fuller, Wayne A. 1979. Distribution of the estimators for autoregressive time series with a unit root. Journal of the American statistical association, 74(366a), 427–431.Emenike, K. O. 2014. Volatility transmission between stock and foreign exchange markets: Evidence from Nigeria. Journal of Banking and Financial Economics, 1 (1), 59–72.Engle, R. F., Ito, T., & Lin, W. L. 1988. Meteor showers or heat waves? Heteroskedastic intra-daily volatility in the foreign exchange market. (No. w2609, National Bureau of Economic Research.Campani, C. H., & Durães, A. G. D. S. 2018. Forecasting USD-BRL Currency Rate Volatility using Realized and Implied Volatilities Data. Estudos Econômicos (São Paulo), 48(4), 687–719.Clements, Hurn., & Volkov, V. V. 2015. Volatility transmission in global financial markets. Journal of Empirical Finance, 32, 3–18.Fleming, Jeff, Kirby, Chris, & Ostdiek, Barbara. 2008. The specification of GARCH models with stochastic covariates. Journal of Futures Markets: Futures, Options, and Other Derivative Products, 28(10), 911–934.Fleming, J., Kirby C. Ostdiek B. 2002. No Contagion, Only Interdependence: Measuring Stock Market Comovements. The Journal of Finance, 57(5), 2223–2261.Francq, Christian, & Zakoian, Jean-Michel. 2019. GARCH models: structure, statistical inference and financial applications. John Wiley & Sons.Francq, C. Thieu, L. Q. 2019. QML inference for volatility models with covariates. Econometric Theory, 35(1), 37–72.Galeano-González, David Andrés. 2015. A transfer function model for volatilities between water inflows and spot prices for Colombian electricity market. Master thesis, Universidad Nacional de Colombia – Sede Medellín, http://bdigital.unal.edu.co/49539/.Gamba-Santamaria, Santiago, Gomez-Gonzalez, Jose Eduardo, Hurtado-Guarin, Jorge Luis, & Melo-Velandia, Luis Fernando. 2017. Stock market volatility spillovers: Evidence for Latin America. Finance Research Letters, 20, 207–216.Garzón, Miller J Ariza, & Lozano, Javier B Cadena. 2014. Identificación de relaciones entre variables de política económica en Colombia a través de funciones de correlación cruzada. Cuadernos de Administración, 30(51), 36–48.Ghalanos, A. 2020. Introduction to the rugarch package. Version 1.3-8, Technical report v. Available at http://cran. r–project. org/web/packages/rugarch.Ghalanos, Alexios, Ghalanos, Maintainer Alexios, & Rcpp, LinkingTo. 2019. Package rugarch.Giraitis, Liudas, Kokoszka, Piotr, Leipus, Remigijus, & Teyssiére, Gilles. 2003. Rescaled variance and related tests for long memory in volatility and levels. Journal of econometrics, 112(2), 265–294.Gomes, M., & Chaibi, A. 2014. Volatility Spillovers Between Oil Prices And Stock Returns: A Focus On Frontier Markets. Journal of Applied Business Research (JABR), 30(2), 509–526.Granger, Clive WJ. 1969. Investigating causal relations by econometric models and crossspectral methods. 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Frontiers in Econometrics, New York Acedemic press.EstudiantesInvestigadoresLICENSElicense.txtlicense.txttext/plain; charset=utf-84074https://repositorio.unal.edu.co/bitstream/unal/80675/1/license.txt8153f7789df02f0a4c9e079953658ab2MD51ORIGINAL1036636839.2021.pdf1036636839.2021.pdfTesis de Maestría en Ciencias - Estadísticaapplication/pdf751133https://repositorio.unal.edu.co/bitstream/unal/80675/2/1036636839.2021.pdf5288c91f94465de59a99ad58de55919dMD52THUMBNAIL1036636839.2021.pdf.jpg1036636839.2021.pdf.jpgGenerated Thumbnailimage/jpeg4716https://repositorio.unal.edu.co/bitstream/unal/80675/3/1036636839.2021.pdf.jpgf5590045c6c9ac8a12c25f402a1a3cf8MD53unal/80675oai:repositorio.unal.edu.co:unal/806752024-08-01 23:09:59.617Repositorio Institucional Universidad Nacional de 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EVESURBIFBPUiBMQSBTRUNSRVRBUsONQSBHRU5FUkFMLiAqTEEgVEVTSVMgQSBQVUJMSUNBUiBERUJFIFNFUiBMQSBWRVJTScOTTiBGSU5BTCBBUFJPQkFEQS4gCgpBbCBoYWNlciBjbGljIGVuIGVsIHNpZ3VpZW50ZSBib3TDs24sIHVzdGVkIGluZGljYSBxdWUgZXN0w6EgZGUgYWN1ZXJkbyBjb24gZXN0b3MgdMOpcm1pbm9zLiBTaSB0aWVuZSBhbGd1bmEgZHVkYSBzb2JyZSBsYSBsaWNlbmNpYSwgcG9yIGZhdm9yLCBjb250YWN0ZSBjb24gZWwgYWRtaW5pc3RyYWRvciBkZWwgc2lzdGVtYS4KClVOSVZFUlNJREFEIE5BQ0lPTkFMIERFIENPTE9NQklBIC0gw5psdGltYSBtb2RpZmljYWNpw7NuIDE5LzEwLzIwMjEK

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