Análisis de la influencia de la pandemia de COVID-19 sobre la transmisión de volatilidad en la colaboración de los mercados de valores extranjeros e indios

El artículo evalúa el impacto de la COVID-19 en la transmisión de volatilidad del mercado bursátil en la India utilizando índices de acciones (NSE, Bolsa Nacional de Valores de India) y de bonos (Foreign Exchange). El artículo utilizó el modelo TGARCH (1,1) para evaluar la volatilidad de los índices...

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Autores:
Das, Runumi
Debnath, Arabinda
Tipo de recurso:
Article of investigation
Fecha de publicación:
2022
Institución:
Universidad Católica de Colombia
Repositorio:
RIUCaC - Repositorio U. Católica
Idioma:
eng
OAI Identifier:
oai:repository.ucatolica.edu.co:10983/29480
Acceso en línea:
https://hdl.handle.net/10983/29480
https://doi.org/10.14718/revfinanzpolitecon.v14.n2.2022.5
Palabra clave:
stock
stock indices
spillover
NSE
TGARCH
VAR-BEKK
GARCH
foreign exchange
volatility
volatility spillover
bolsa de valores
índices bursátiles
cambio de divisas
volatilidad
transmisión de volatilidad
NSE
TGARCH
VAR-BEKK-GARCH
Rights
openAccess
License
Runumi Das, Arabinda Debnath - 2022
id UCATOLICA2_1a4864e6528f5ed531a9a09e758fb800
oai_identifier_str oai:repository.ucatolica.edu.co:10983/29480
network_acronym_str UCATOLICA2
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repository_id_str
dc.title.spa.fl_str_mv Análisis de la influencia de la pandemia de COVID-19 sobre la transmisión de volatilidad en la colaboración de los mercados de valores extranjeros e indios
dc.title.translated.eng.fl_str_mv Analyzing the COVID-19 Pandemic Volatility Spillover Influence on the Collaboration of Foreign and Indian Stock Markets
title Análisis de la influencia de la pandemia de COVID-19 sobre la transmisión de volatilidad en la colaboración de los mercados de valores extranjeros e indios
spellingShingle Análisis de la influencia de la pandemia de COVID-19 sobre la transmisión de volatilidad en la colaboración de los mercados de valores extranjeros e indios
stock
stock indices
spillover
NSE
TGARCH
VAR-BEKK
GARCH
foreign exchange
volatility
volatility spillover
bolsa de valores
índices bursátiles
cambio de divisas
volatilidad
transmisión de volatilidad
NSE
TGARCH
VAR-BEKK-GARCH
title_short Análisis de la influencia de la pandemia de COVID-19 sobre la transmisión de volatilidad en la colaboración de los mercados de valores extranjeros e indios
title_full Análisis de la influencia de la pandemia de COVID-19 sobre la transmisión de volatilidad en la colaboración de los mercados de valores extranjeros e indios
title_fullStr Análisis de la influencia de la pandemia de COVID-19 sobre la transmisión de volatilidad en la colaboración de los mercados de valores extranjeros e indios
title_full_unstemmed Análisis de la influencia de la pandemia de COVID-19 sobre la transmisión de volatilidad en la colaboración de los mercados de valores extranjeros e indios
title_sort Análisis de la influencia de la pandemia de COVID-19 sobre la transmisión de volatilidad en la colaboración de los mercados de valores extranjeros e indios
dc.creator.fl_str_mv Das, Runumi
Debnath, Arabinda
dc.contributor.author.spa.fl_str_mv Das, Runumi
Debnath, Arabinda
dc.subject.eng.fl_str_mv stock
stock indices
spillover
NSE
TGARCH
VAR-BEKK
GARCH
foreign exchange
volatility
volatility spillover
topic stock
stock indices
spillover
NSE
TGARCH
VAR-BEKK
GARCH
foreign exchange
volatility
volatility spillover
bolsa de valores
índices bursátiles
cambio de divisas
volatilidad
transmisión de volatilidad
NSE
TGARCH
VAR-BEKK-GARCH
dc.subject.spa.fl_str_mv bolsa de valores
índices bursátiles
cambio de divisas
volatilidad
transmisión de volatilidad
NSE
TGARCH
VAR-BEKK-GARCH
description El artículo evalúa el impacto de la COVID-19 en la transmisión de volatilidad del mercado bursátil en la India utilizando índices de acciones (NSE, Bolsa Nacional de Valores de India) y de bonos (Foreign Exchange). El artículo utilizó el modelo TGARCH (1,1) para evaluar la volatilidad de los índices bursátiles y sectoriales de la NSE. Además, el estudio tenía como objetivo comparar los rendimientos de los precios de las acciones en los escenarios anteriores y posteriores al COVID-19 con los índices globales, como el NASDAQ, el Nikkei 225 y el FTSE100. Posteriormente, utilizó los índices bursátiles y de bonos para explorar la influencia de la transmisión de volatilidad por medio del modelo vectorial autorregresivo-Baba, Engle, Kraft y Kroner con GARCH multivariante (VAR-BEKK-GARCH). Los resultados de la variable mostraron una correlación negativa y estadísticamente significativa que sugiere que el brote de COVID-19 redujo la volatilidad del mercado de valores en la India. En términos de errores históricos, los coeficientes representan la persistencia de la volatilidad para cada nación. El NIFTY y el NASDAQ son los que tienen el mayor y más prolongado efecto de transmisión. Según los resultados, la India es el país menos sensible a las perturbaciones externas.
publishDate 2022
dc.date.accessioned.none.fl_str_mv 2022-06-29 00:00:00
2023-01-23T16:16:29Z
dc.date.available.none.fl_str_mv 2022-06-29 00:00:00
2023-01-23T16:16:29Z
dc.date.issued.none.fl_str_mv 2022-06-29
dc.type.spa.fl_str_mv Artículo de revista
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dc.identifier.eissn.none.fl_str_mv 2011-7663
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dc.relation.citationedition.spa.fl_str_mv Núm. 2 , Año 2022 : Vol. 14 Núm. 2 (2022)
dc.relation.citationendpage.none.fl_str_mv 452
dc.relation.citationissue.spa.fl_str_mv 2
dc.relation.citationstartpage.none.fl_str_mv 411
dc.relation.citationvolume.spa.fl_str_mv 14
dc.relation.ispartofjournal.spa.fl_str_mv Revista Finanzas y Política Económica
dc.relation.references.eng.fl_str_mv Al-Awadhi, A. M., Alsaifi, K., Al-Awadhi, A., & Alhammadi, S. (2020). Death and contagious infectious diseases: Impact of the COVID-19 virus on stock market returns. Journal of Behavioral and Experimental Finance, 27, 100326. https://doi.org/10.1016/j.jbef.2020.100326
Alam, M. N., Alam, M. S., & Chavali, K. (2020). Stock market response during COVID-19 lockdown period in India: An event study. The Journal of Asian Finance, Economics and Business, 7(7), 131-137.
Ambros, M., Frenkel, M., Huynh, T.L.D., & Kilinc, M. (2021). COVID-19 pandemic news and stock market reaction during the onset of the crisis: evidence from highfrequency data. Applied Economics Letters, 28(19), 1-4. https://doi.org/10.1080/13504851.2020.1851643
Andersen, T. G., & Bollerslev, T. (1998). Answering the skeptics: Yes, standard volatility models do provide accurate forecasts. International Economic Review, 885-905.
Baek, S., Mohanty, S.K., & Glambosky, M. (2020). COVID-19 and stock market volatility: An industry level analysis. Finance Research Letters, 37, 101748. https://doi.org/10.1016/j.frl.2020.101748
Bal, D., & Mohanty, S. (2021). Sectoral nonlinear causality between stock marketvolatility and the COVID-19 pandemic: Evidence from India. Asian Economics Letters, 2(1), 1-4. https://doi.org/10.46557/001c.21380
Bharti, & Kumar, A. (2021). Exploring Herding Behaviour in Indian Equity Market during COVID-19 Pandemic: Impact of Volatility and Government Response. Millennial Asia, 1-19. https://doi.org/10.1177/09763996211020687
Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journalof Econometrics, 31(3), 307-327. https://doi.org/10.1016/0304-4076(86)90063-1
Bora, D., & Basistha, D. (2021). The outbreak of COVID-19 pandemic and its impact on stock market volatility: Evidence from a worst-affected economy. Journal of Public Affairs, 21(4), e262. https://doi.org/10.1002/pa.2623
Chaudhary, R., Bakhshi, P., & Gupta, H. (2020). Volatility in international stock markets: An empirical study during COVID-19. Journal of Risk and Financial Management, 13(9), 208. https://doi.org/10.3390/jrfm13090208
Cheung, Y. W., & Lai, K. S. (1995). Lag order and critical values of the augmented Dickey-Fuller test. Journal of Business & Economic Statistics, 13(3), 277-280. https://doi.org/10.1080/07350015.1995.10524601
Contessi, S., & De Pace, P. (2021). The international spread of COVID-19 stock market collapses. Finance Research Letters, 42, 101894. https://doi.org/10.1016/j.frl.2020.101894
Diebold, F. X., & Yilma, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. The Economic Journal, 119(534), 158-171. https://doi.org/10.1111/j.1468-0297.2008.02208.x
Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the Econometric Society, 50(4), 987-1007.
Engle, R. F., & Kroner, K. F. (1995). Multivariate simultaneous generalized ARCH. Econometric Theory, 11(1), 122-150. https://doi.org/10.1017/S0266466600009063
Faniband, M., & Faniband, T. (2021). Government Bonds and Stock Market: Volatility Spillover Effect. Indian Journal of Research in Capital Markets, 8(1-2), 61-71. https://doi.org/10.17010/ijrcm/2021/v8i1-2/165087
Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. The Journal of Finance, 48(5), 1779-1801. https://doi.org/10.1111/j.1540-6261.1993.tb05128.x
Gupta, K., Das, S., & Gupta, K. (2022). Volatility in Indian Stock Markets During COVID-19: An Analysis of Equity Investment Strategies. International Journal of Business Analytics, 9(1), 1-16. https://doi.org/10.4018/IJBAN.288512
Guru, B.K., & Das, A. (2021). COVID-19 and uncertainty spillovers in Indian stock market. MethodsX, 8, 101199. https://doi.org/10.1016/j.mex.2020.101199
Iqbal, J., Azher, S., & Ijaz, A. (2010). Predictive ability of Value-at-Risk methods: evidence from the Karachi Stock Exchange-100 Index (No. 18/2010). EERI Research Paper Series. http://hdl.handle.net/10419/142580
Just, M., & Echaust, K. (2020). Stock market returns, volatility, correlation and liquidity during the COVID-19 crisis: Evidence from the Markov switching approach. Finance Research Letters, 37, 101775. https://doi.org/10.1016/j.frl.2020.101775
Li, W., Chien, F., Kamran, H.W., Aldeehani, T.M., Sadiq, M., Nguyen, V.C., & Taghizadeh-Hesary, F. (2021). The nexus between COVID-19 fear and stock market volatility. Economic Research-Ekonomska Istraživanja, 1-22. https://doi.org/10.1080/1331677X.2021.1914125
Li, Y., Liang, C., Ma, F., & Wang, J. (2020). The role of the IDEMV in predicting European stock market volatility during the COVID-19 pandemic. Finance Research Letters, 36, 101749. https://doi.org/10.1016/j.frl.2020.101749
Malik, K., Sharma, S., & Kaur, M. (2021). Measuring contagion during COVID-19 through volatility spillovers of BRIC countries using diagonal BEKK approach. Journal of Economic Studies. https://doi.org/10.1108/JES-05-2020-0246
Mishra, A. K., Rath, B. N., & Dash, A. K. (2020). Does the Indian financial market nosedive because of the COVID-19 outbreak, in comparison to after demonetisation and the GST? Emerging Markets Finance and Trade, 56(10), 2162-2180. https://doi.org/10.1080/1540496X.2020.1785425
Papadamou, S., Fassas, A., Kenourgios, D., & Dimitriou, D. (2020). Direct and indirect effects of COVID-19 pandemic on implied stock market volatility: Evidence frompanel data analysis. MPRA Paper 100020, University Library of Munich, Germany.
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dc.rights.eng.fl_str_mv Runumi Das, Arabinda Debnath - 2022
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spelling Das, Runumi2cd1dbd8-cc37-444b-866b-a83cd8abcc9b300Debnath, Arabinda15f3ee7a-b62b-4acb-b649-8ad6f9a4c2bf3002022-06-29 00:00:002023-01-23T16:16:29Z2022-06-29 00:00:002023-01-23T16:16:29Z2022-06-29El artículo evalúa el impacto de la COVID-19 en la transmisión de volatilidad del mercado bursátil en la India utilizando índices de acciones (NSE, Bolsa Nacional de Valores de India) y de bonos (Foreign Exchange). El artículo utilizó el modelo TGARCH (1,1) para evaluar la volatilidad de los índices bursátiles y sectoriales de la NSE. Además, el estudio tenía como objetivo comparar los rendimientos de los precios de las acciones en los escenarios anteriores y posteriores al COVID-19 con los índices globales, como el NASDAQ, el Nikkei 225 y el FTSE100. Posteriormente, utilizó los índices bursátiles y de bonos para explorar la influencia de la transmisión de volatilidad por medio del modelo vectorial autorregresivo-Baba, Engle, Kraft y Kroner con GARCH multivariante (VAR-BEKK-GARCH). Los resultados de la variable mostraron una correlación negativa y estadísticamente significativa que sugiere que el brote de COVID-19 redujo la volatilidad del mercado de valores en la India. En términos de errores históricos, los coeficientes representan la persistencia de la volatilidad para cada nación. El NIFTY y el NASDAQ son los que tienen el mayor y más prolongado efecto de transmisión. Según los resultados, la India es el país menos sensible a las perturbaciones externas.This article assesses the impact of COVID-19 on stock market volatility spillover in India using equity (NSE exchange) and bond (Foreign Exchange) indices. The article utilized the TGARCH model (1,1) to evaluate the volatility of the NSE stock exchange and sectoral indices. Furthermore, the study aimed to compare stock price returns in pre- and post-COVID-19 scenarios to global indices, such as NASDAQ, Nikkei 225, and FTSE100. Subsequently, it utilised stock exchange and bond indices to explore the volatility spillover influence using vector autoregressive-Baba, Engle, Kraft, and Kroner with multivariate GARCH (VAR-BEKKGARCH model). The findings of the variable showed a negative and statistically significant correlation that suggests that the COVID-19 outbreak lowered stock market volatility in India. In terms of historical errors, the coefficients represent the  persistence of volatility for each nation. NIFTY and  ASDAQ have the largest and longest-term spillover effect.  According to the findings, India is the least sensitive country to external shocks.text/htmlapplication/pdftext/xml10.14718/revfinanzpolitecon.v14.n2.2022.52011-76632248-6046https://hdl.handle.net/10983/29480https://doi.org/10.14718/revfinanzpolitecon.v14.n2.2022.5engUniversidad Católica de Colombiahttps://revfinypolecon.ucatolica.edu.co/article/download/4401/4364https://revfinypolecon.ucatolica.edu.co/article/download/4401/4321https://revfinypolecon.ucatolica.edu.co/article/download/4401/4389Núm. 2 , Año 2022 : Vol. 14 Núm. 2 (2022)452241114Revista Finanzas y Política EconómicaAl-Awadhi, A. M., Alsaifi, K., Al-Awadhi, A., & Alhammadi, S. (2020). Death and contagious infectious diseases: Impact of the COVID-19 virus on stock market returns. Journal of Behavioral and Experimental Finance, 27, 100326. https://doi.org/10.1016/j.jbef.2020.100326Alam, M. N., Alam, M. S., & Chavali, K. (2020). Stock market response during COVID-19 lockdown period in India: An event study. The Journal of Asian Finance, Economics and Business, 7(7), 131-137.Ambros, M., Frenkel, M., Huynh, T.L.D., & Kilinc, M. (2021). COVID-19 pandemic news and stock market reaction during the onset of the crisis: evidence from highfrequency data. Applied Economics Letters, 28(19), 1-4. https://doi.org/10.1080/13504851.2020.1851643Andersen, T. G., & Bollerslev, T. (1998). Answering the skeptics: Yes, standard volatility models do provide accurate forecasts. International Economic Review, 885-905.Baek, S., Mohanty, S.K., & Glambosky, M. (2020). COVID-19 and stock market volatility: An industry level analysis. Finance Research Letters, 37, 101748. https://doi.org/10.1016/j.frl.2020.101748Bal, D., & Mohanty, S. (2021). Sectoral nonlinear causality between stock marketvolatility and the COVID-19 pandemic: Evidence from India. Asian Economics Letters, 2(1), 1-4. https://doi.org/10.46557/001c.21380Bharti, & Kumar, A. (2021). Exploring Herding Behaviour in Indian Equity Market during COVID-19 Pandemic: Impact of Volatility and Government Response. Millennial Asia, 1-19. https://doi.org/10.1177/09763996211020687Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journalof Econometrics, 31(3), 307-327. https://doi.org/10.1016/0304-4076(86)90063-1Bora, D., & Basistha, D. (2021). The outbreak of COVID-19 pandemic and its impact on stock market volatility: Evidence from a worst-affected economy. Journal of Public Affairs, 21(4), e262. https://doi.org/10.1002/pa.2623Chaudhary, R., Bakhshi, P., & Gupta, H. (2020). Volatility in international stock markets: An empirical study during COVID-19. Journal of Risk and Financial Management, 13(9), 208. https://doi.org/10.3390/jrfm13090208Cheung, Y. W., & Lai, K. S. (1995). Lag order and critical values of the augmented Dickey-Fuller test. Journal of Business & Economic Statistics, 13(3), 277-280. https://doi.org/10.1080/07350015.1995.10524601Contessi, S., & De Pace, P. (2021). The international spread of COVID-19 stock market collapses. Finance Research Letters, 42, 101894. https://doi.org/10.1016/j.frl.2020.101894Diebold, F. X., & Yilma, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. The Economic Journal, 119(534), 158-171. https://doi.org/10.1111/j.1468-0297.2008.02208.xEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the Econometric Society, 50(4), 987-1007.Engle, R. F., & Kroner, K. F. (1995). Multivariate simultaneous generalized ARCH. Econometric Theory, 11(1), 122-150. https://doi.org/10.1017/S0266466600009063Faniband, M., & Faniband, T. (2021). Government Bonds and Stock Market: Volatility Spillover Effect. Indian Journal of Research in Capital Markets, 8(1-2), 61-71. https://doi.org/10.17010/ijrcm/2021/v8i1-2/165087Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. The Journal of Finance, 48(5), 1779-1801. https://doi.org/10.1111/j.1540-6261.1993.tb05128.xGupta, K., Das, S., & Gupta, K. (2022). Volatility in Indian Stock Markets During COVID-19: An Analysis of Equity Investment Strategies. International Journal of Business Analytics, 9(1), 1-16. https://doi.org/10.4018/IJBAN.288512Guru, B.K., & Das, A. (2021). COVID-19 and uncertainty spillovers in Indian stock market. MethodsX, 8, 101199. https://doi.org/10.1016/j.mex.2020.101199Iqbal, J., Azher, S., & Ijaz, A. (2010). Predictive ability of Value-at-Risk methods: evidence from the Karachi Stock Exchange-100 Index (No. 18/2010). EERI Research Paper Series. http://hdl.handle.net/10419/142580Just, M., & Echaust, K. (2020). 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Journal of Economic Dynamics and Control, 18(5), 931-955. https://doi.org/10.1016/0165-1889(94)90039-6Runumi Das, Arabinda Debnath - 2022info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.https://creativecommons.org/licenses/by-nc-sa/4.0https://revfinypolecon.ucatolica.edu.co/article/view/4401stockstock indicesspilloverNSETGARCHVAR-BEKKGARCHforeign exchangevolatilityvolatility spilloverbolsa de valoresíndices bursátilescambio de divisasvolatilidadtransmisión de volatilidadNSETGARCHVAR-BEKK-GARCHAnálisis de la influencia de la pandemia de COVID-19 sobre la transmisión de volatilidad en la colaboración de los mercados de valores extranjeros e indiosAnalyzing the COVID-19 Pandemic Volatility Spillover Influence on the Collaboration of Foreign and Indian Stock MarketsArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Textinfo:eu-repo/semantics/articleJournal articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionPublicationOREORE.xmltext/xml2749https://repository.ucatolica.edu.co/bitstreams/e2db5e0a-b722-49fe-9515-7dc4679116cd/downloada5057a96cd65d4ee1da601dae634b0bbMD5110983/29480oai:repository.ucatolica.edu.co:10983/294802023-03-24 17:00:00.858https://creativecommons.org/licenses/by-nc-sa/4.0Runumi Das, Arabinda Debnath - 2022https://repository.ucatolica.edu.coRepositorio Institucional Universidad Católica de Colombia - RIUCaCbdigital@metabiblioteca.com