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...
- 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
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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 |
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Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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Journal article |
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10.14718/revfinanzpolitecon.v14.n2.2022.5 |
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2011-7663 |
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2248-6046 |
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Núm. 2 , Año 2022 : Vol. 14 Núm. 2 (2022) |
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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. Purankar, S.A., & Singh, V.K. (2020). Dynamic volatility spillover connectedness of sectoral indices of commodity and equity: evidence from India. International Journal of Management Practice, 13(2), 151-177. https://doi.org/10.1504/IJMP.2020.105670 Rai, K., & Garg, B. (2021). Dynamic correlations and volatility spillovers between stock price and exchange rate in BRIICS economies: evidence from the COVID-19 outbreak period. Applied Economics Letters, 29(8), 1-8. https://doi.org/10.1080/13504851.2021.1884835 Rajamohan, S., Sathish, A., & Rahman, A. (2020). Impact of COVID-19 on stock price of NSE in automobile sector. International Journal of Advanced Multidisciplinary Research, 7(7), 24-29. Rakshit, B., & Neog, Y. (2021). Effects of the COVID-19 pandemic on stock market returns and volatilities: evidence from selected emerging economies. Studies in Economics and Finance, 39(4), 549-571. https://doi.org/10.1108/SEF-09-2020-0389 Roy, R.P., & Roy, S.S. (2017). Financial contagion and volatility spillover: An exploration into Indian commodity derivative market. Economic Modelling, 67, 368-380. https://doi.org/10.1016/j.econmod.2017.02.019 Sadiq, M., Hsu, C.C., Zhang, Y., & Chien, F. (2021). COVID-19 fear and volatility index movements: empirical insights from ASEAN stock markets. Environmental Science and Pollution Research, 28, 67167-67184. https://doi.org/10.1007/s11356-021-15064-1 Safitri, H., 2022. Black Swan Event on JCI Value and Sectoral Index for February-April 2020: Effects of COVID-19 in Indonesian Stock Exchange. Journal of Business and Management Studies, 4(1), pp.57-63. Safwan, M.K. (2022). Performance evaluation sectoral indices during COVID 19 pandemic period. A study on NSE India. AIP Conference Proceedings, 2393, 020003. https://doi.org/10.1063/5.0074532 Sharma, S.S. (2020). A note on the Asian market volatility during the COVID-19 pandemic. Asian Economics Letters, 1(2), 1-6. https://doi.org/10.46557/001c.17661 Si, D.K., Li, X.L., Xu, X., & Fang, Y. (2021). The risk spillover effect of the COVID-19 pandemic on energy sector: Evidence from China. Energy Economics, 102, 105498. https://doi.org/10.1016/j.eneco.2021.105498 Verma, D., & Sinha, P. K. (2020). Has COVID 19 infected Indian stock market volatility? Evidence from NSE. AAYAM: AKGIM Journal of Management, 10(1), 25-35. Wei, Z., Luo, Y., Huang, Z., & Guo, K. (2020). Spillover effects of RMB exchange rate among B&R countries: Before and during COVID-19 event. Finance Research Letters, 37, 101782. https://doi.org/10.1016/j.frl.2020.101782 Zakoian, J. M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. https://doi.org/10.1016/0165-1889(94)90039-6 |
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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 |