Effect of uncertainty in stock market organizations: a tool for decision-making and organizational intelligence
DOI:
https://doi.org/10.18046/j.estger.2022.162.4689Keywords:
uncertainty, decision making, organizational intelligence, rationality, energy raw materialsAbstract
This article aims to measure the effect of uncertainty in Colombian stock market organizations, using financial information such as the prices of energy raw materials and the exchange rate to increase organizational intelligence for decision-making. The FAVAR model and the financial spillover measurement are used to analyze the impacts and directional volatility of the IMIFE index, which is a proxy for uncertainty. It is found that uncertainty negatively affects the growth of the value of Colombian shares, generating significant impacts of more than 90% in times of high uncertainty, which allows both strategic and financial management decisions.
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Ali, U., Daniel, K. D. y Hirshleifer, D. A. (2017). One brief shining moment (um): Past momentum performance and momentum reversals. Columbia Business School Research Paper, 17-48. http://dx.doi.org/10.2139/ssrn.2956493
Arora, V. y Cerisola, M. (2001). How does US monetary policy influence sovereign spreads in emerging markets? IMF Staff Papers, 48(3), 474-498. https://doi.org/10.2307/4621680
Asness, C. S., Moskowitz, T. J. y Pedersen, L. H. (2013). Value and momentum everywhere. The Journal of Finance, 68(3), 929-985. https://doi.org/10.1111/jofi.12021
Bergstrand, J. H. (1985). The gravity equation in international trade: some microeconomic foundations and empirical evidence. The review of economics and statistics, 474-481. https://doi.org/10.2307/1925976
Bernstein, P. L. (1998). Against the Gods: the remarkable story of Risk. John Wiley & Sons. Inc
Bernanke, B. S., Boivin, J., & Eliasz, P. (2005). Measuring the effects of monetary policy: a factor-augmented vector autoregressive (FAVAR) approach. The Quarterly journal of economics, 120(1), 387-422. https://doi.org/10.1162/0033553053327452
Bloom, N. (2009). The impact of uncertainty shocks. Econometrica, 77(3), 623-685. https://doi.org/10.3982/ECTA6248
Brahmasrene, T., Huang, J. C. y Sissoko, Y. (2014). Crude oil prices and exchange rates: Causality, variance decomposition and impulse response. Energy Economics, 44, 407-412. https://doi.org/10.1016/j.eneco.2014.05.011
Bunge, M. (2000). La investigación científica. Su estrategia y su Filosofía. México: Ariel.
Candelo, J. M. (2018). Impactos indirectos de la tasa de cambio y los precios del petróleo en una economía no petrolera: aproximaciones VECM y VAR para el Valle del Cauca, Colombia. Finanzas y Política Económica, 10(2), 403-436. https://doi.org/10.14718/revfinanzpolitecon.2018.10.2.9
Candelo-Viáfara, J. (2020). La educación y la distribución del tiempo laboral como variables para la selección de personal y la eficiencia organizacional. Revista Escuela de Administración de Negocios, 88, 49-62. https://doi.org/10.21158/01208160.n88.2020.2498
Candelo-Viáfara, J. M. (2021). Índice mensual de incertidumbre financiera y económica (IMIFE) para la economía colombiana. Lecturas de Economía, 95, 85-104. https://doi.org/10.17533/udea.le.n95a343318
Candelo-Viáfara, J. y Oviedo-Gómez, A. (2020). Efecto derrame del mercado internacional en las economías latinoamericanas: los casos de Chile, Brasil, Colombia y México. Apuntes del Cenes, 39(70). 107-138. https://doi.org/10.19053/01203053.v39.n70.2020.10876
Cerda, R., Silva, Á. y Valente, J. (2016). Economic Uncertainty Impact in a Small Open Economy: The Case of Chile. Recuperado de https://negocios.udd.cl/files/2016/12/CerdaSilvaValente_EU_Chile_Paper.pdf
Chenari, H., Nazem, F. y Safari, M. (2013). Modeling Organizational Intelligence Based on Knowledge Management in the Technical and Vocational Training Organization of Tehran. En 14th European Conference on Knowledge Management (pp. 167-173). Kaunas, Lithuania: Kaunas University of Technology.
Coase, R. H. (1988). The Nature of the Firm: Meaning. Journal of Law, Economics, & Organization, 4(1), 19–32. http://www.jstor.org/stable/765012
Daniel, K., Hirshleifer, D., & Subrahmanyam, A. (1998). Investor psychology and security market under-and overreactions. The Journal of Finance, 53(6), 1839-1885. https://doi.org/10.1111/0022-1082.00077
Daniel, K. y Moskowitz, T. J. (2016). Momentum crashes. Journal of Financial Economics, 122(2), 221-247. https://doi.org/10.1016/j.jfineco.2015.12.002
De Truchis, G. y Keddad, B. (2016). On the risk comovements between the crude oil market and US dollar exchange rates. Economic Modelling, 52, 206-215. https://doi.org/10.1016/j.econmod.2014.11.014
Diebold, F. X. y Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57-66. https://doi.org/10.1016/j.ijforecast.2011.02.006
Ercetin, S. y Demirbulak, D. (2002). Action Research… Organizational Intelligence… Curriculum Development. Educational Research Quarterly, 21(1), 41-49.
Frazzini, A. (2006). The disposition effect and underreaction to news. The Journal of Finance, 61(4), 2017-2046. https://doi.org/10.1111/j.1540-6261.2006.00896.x
Fu, C., Chang, W. y Yang, S. (2020). Multiple criteria group decision making based on group satisfaction. Information Sciences, 518, 309-329. https://doi.org/10.1016/j.ins.2020.01.021
Gervais, S., Kaniel, R. y Mingelgrin, D. H. (2001). The high-volume return premium. The Journal of Finance, 56(3), 877-919. https://doi.org/10.1111/0022-1082.00349
Geweke, J. (1977). The dynamic factor analysis of economic time series. En D. J. Aigner & A. S. Goldberger (eds.): Latent Variables in Socioeconomic Models (pp. 365-383). North-Holland Publications.
Glynn, M. A. (1996). Innovative genius: A framework for relating individual and organizational intelligences to innovation. Academy of Management Review, 21(4), 1081-1111. https://doi.org/10.5465/amr.1996.9704071864
Gómez, A. (2012). Statistical-methodological proposal to measure organizational intelligence, based on the fifth discipline by Peter Senge. Negotium, 22(9), 53-83. Recuperado de http://www.revistanegotium.org/pdf/22/art3.pdf
González, S., & Hernández, E. (2016). Impactos indirectos de los precios del petróleo en el crecimiento económico colombiano. Lecturas de Economía, (84), 113-141. https://doi.org/10.17533/udea.le.n84a04
Golub, S. S. (1983). Oil prices and exchange rates. The Economic Journal, 93(371), 576-593. https://doi.org/10.2307/2232396.
Groenewegen, P. (1995). A soaring eagle: Alfred Marshall 1842-1924. Aldershot: Edward Elgar Publishing.
Gulick, L. (1965). Management is a Science. Academy of Management Journal, 8(1), 7-13.
Haddow, A., Hare, C., Hooley, J. y Shakir, T. (2013). Macroeconomic uncertainty: What is it, how can we measure it and why does it matter? Bank of England, 53(2), 100-109.
He, Y., Hu, L., Guan, X., Deng, Y. y Han, D. (2012). New method for measuring the degree of conflict among general basic probability assignments. Science China Information Sciences, 55(2), 312-321. https://doi.org/10.1007/s11432-011-4346-0
Hong, H. y Stein, J. C. (1999). A unified theory of underreaction, momentum trading, and overreaction in asset markets. The Journal of Finance, 54(6), 2143-2184. https://doi.org/10.1111/0022-1082.00184
Jurado, K., Ludvigson, S. C. y Ng, S. (2015). Measuring uncertainty. American Economic Review, 105(3), 1177-1216. https://doi.org/10.1257/aer.20131193
Keynes, J. M. (1921). A treatise on probability. New York: St. Martins Press.
Keynes, J. M. (1939). The League of Nations Professor Tinbergen's Method. The Economic Journal, 49(195), 558-577.
Knight, F. H. (1921). Risk, uncertainty and profit. Boston, MA: Houghton Mifflin Co.
Koop, G., Pesaran, M. H. y Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1), 119-147. https://doi.org/10.1016/0304-4076(95)01753-4
Krugman, P. (1983). Oil shocks and exchange rate dynamics. En Exchange rates and international macroeconomics (pp. 259-284). Chicago: University of Chicago Press. Recuperado de http://www.nber.org/chapters/c11382
León, M., Tejada, G. y Yataco, T. (2003). Las Organizaciones Inteligentes. Industrial Data, 6(2), 82-87.
Lof, M. y Nyberg, H. (2017). Noncausality and the commodity currency hypothesis. Energy Economics, 65, 424-433. https://doi.org/10.1016/j.eneco.2017.05.024
López, I. y Correa, M. (2011). Fuentes de información e inteligencia organizacional en investigación. El caso de la Universidad Tecnológica de Pereira. Cuadernos de Administración, 24(42), 231-252. Recuperado de http://www.scielo.org.co/pdf/cadm/v24n42/v24n42a11.pdf
Lozano, J., y González, C. (2014). Una propuesta para la definición de la inteligencia organizacional. Universidad & Empresa, 16(26), 155-171.
March, J. G. y Olsen, J. P. (1976). Organizational Learning and the Ambiguity of the Past. Ambiguity and Choice in Organizations, 2(1), 54-68.
Mas, A. (2005). Antecedentes y situación actual de los conceptos y métodos para el desarrollo de la inteligencia organizacional. ACIMED, 13(4), 1-25.
Matsuda, T. (1992). Organizational intelligence: Coordination of human intelligence and machine intelligence. En P. Bourgine y B. Walliser (Eds.), Economics and Cognitive Science (pp. 171-180). Oxford: Pergamon.
Mendoza, O. & Vera, D. (2010). The asymmetric effects of oil shocks on an oil-exporting Economy. Cuadernos de Economía, 47(135), 3-1. http://dx.doi.org/10.4067/S0717-68212010000100001
Mintzberg, H. (1993). Structure in fives: Designing effective organizations. Englewood Cliffs, NJ: Prentice-Hall.
Moskowitz, T. J., Ooi, Y. H., & Pedersen, L. H. (2012). Time series momentum. Journal of Financial Economic, 104(2), 228-250. https://doi.org/10.1016/j.jfineco.2011.11.003
Niiniluoto, I. (1984). Is science progressive? Dordrecht: D. Reidel.
Novy-Marx, R. (2012). Is momentum really momentum? Journal of Financial Economics, 103(3), 429-453. https://doi.org/10.1016/j.jfineco.2011.05.003
Nozick, R. (1995). La naturaleza de la racionalidad. Barcelona: Paidós.
Núñez, M. (2002). Organizational change and accounting: The gun-powder monopoly in New Spain, 1757-87. Accounting, Business & Financial History, 12(2), 275-315. https://doi.org/10.1080/09585200210134956
Orozco, E. (1999). La inteligencia organizacional en la industria biofarmacéutica. Ciência da Informação, 28(1), 59-66. http://dx.doi.org/10.1590/S0100-19651999000100008
Ortiz, C. H. (2016). Diversificación productiva y crecimiento económico. Cali: Universidad del Valle.
Oviedo, A. F. y Sierra, L. P. (2019). Importancia de los términos de intercambio en la economía colombiana. CEPAL Review, 128, 125-154. Recuperado de https://repositorio.cepal.org/bitstream/handle/11362/44740/RVE128_Oviedo.pdf?sequence=1&isAllowed=y
Oviedo-Gómez, A. y Candelo-Viáfara, J. M. (2020). Mining and Energy Commodity Price Effects on Colombian Economy. Cuadernos de Administración, 36(67), 3-15. https://doi.org/10.25100/cdea.v36i67.8641
Pesaran, M. H. y Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17-29. https://doi.org/10.1016/S0165-1765(97)00214-0
Poncela, P., Senra, E. & Sierra, L. P. (2016). Long-term links between raw materials prices, real exchange rate and relative de-industrialization in a commodity-dependent economy: empirical evidence of "Dutch disease" in Colombia. Empirical Economics, 52(2), 777-798. https://doi.org/10.1007/s00181-016-1083-7
Ranjbarian, R. y Esgandari, K. (2014). Ranking of Organizational Intelligence Aspects of Chancellors of Islamic Azad Universities. Applied mathematics in Engineering, Management and Technology, 2(2), 1-8.
Reinhart, C. M. (1995). Devaluation, Relative Prices and International Trade: Evidence from Developing Countries. Staff Papers, 42(2), 290-312. https://doi.org/10.2307/3867574
Reza, H., Sabzeparvar, M., Lotfi, M. y Sadat, Z. (2014). Evaluation of the Role of Organizational Intelligence in Organizational Performance Using a Seven Dimensional Model of Albrecht. Journal of Applied Environmental and Biological Sciences, 4(7), 49-54.
Sagi, J. S. y Seasholes, M. S. (2007). Firm-specific attributes and the cross-section of momentum. Journal of Financial Economics, 84(2), 389-434. https://doi.org/10.1016/j.jfineco.2006.02.002
Shafritz, J. M., Ott, J. S. y Jang, Y. S. (2015). Classics of organization theory. Boston, MA: Cengage Learning.
Simon, H. A. (1962). El comportamiento administrativo. Madrid: Aguilar.
Simon, H. A. (1990). Bounded rationality. En J. Eatwell, M. Milgate y P. Newman (Eds.), Utility and probability (pp. 15-18). London: Palgrave Macmillan.
Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 48(1), 1-48.
Stock, J. H. y Watson, M. W. (2005). Implications of dynamic factor models for VAR analysis. National Bureau of Economic Research (Working paper), 11467, 1-67. Recuperado de https://www.nber.org/papers/w11467
Stock, J. H. y Watson, M. W. (2011). Dynamic factor models. Oxford handbook of economic for recasting, 1, 35-59. https://doi.org/10.1093/oxfordhb/9780195398649.013.0003
Tello, C. (2018). El concepto de organización, tan cerca y tan lejos. En Tello Castrillón, C. y Pineda, E. F. (comps.), Conjeturas orga-nizacionales Fundamentos para el estudio de la organización (pp. 79-102). Bogotá: Universidad Nacional de Colombia. Recuperado de https://repositorio.unal.edu.co/handle/unal/68982?show=full
Von Neumann, J. y Morgenstern, O. (1947). Theory of games and economic behavior (2.ª ed.). Princeton, NJ: Princeton University Press.
Wang, Z., Gao, J. M., Wang, R. X., Chen, K., Gao, Z. Y. y Jiang, Y. (2018). Failure mode and effects analysis using Dempster-Shafer theory and TOPSIS method: Application to the gas insulated metal enclosed transmission line (GIL). Applied Soft Computing, 70, 633-647. https://doi.org/10.1016/j.asoc.2018.06.015
Wilensky, H. (1970). Intelligence in Industry: The uses and abuses of experts. The Annals of the American Academy of Political and Social Science, 388, 46-58.
World Bank. (2015). Global Economic Prospects, January 2015. Washington, DC: World Bank.
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