¿Han sido los mercados bursátiles eficientes informacionalmente?

  1. Duarte, Juan Benjamín Duarte 1
  2. Pérez-Iñigo, Juan Manuel Mascareñas
  1. 1 Universidad Pedagógica y Tecnológica de Colombia
    info

    Universidad Pedagógica y Tecnológica de Colombia

    Tunja, Colombia

    ROR https://ror.org/04vdmbk59

Revista:
Apuntes del CENES

ISSN: 0120-3053

Año de publicación: 2014

Volumen: 33

Número: 57

Páginas: 117-146

Tipo: Artículo

DOI: 10.19053/22565779.2906 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Otras publicaciones en: Apuntes del CENES

Resumen

En el presente trabajo se estudia la contrastación de la eficiencia demercados bursátiles en los últimos quince años, para ello se acude a la revisión de artículos de la base de datos ScienceDirect caracterizando los resultados de forma porcentual. Se encuentra que el 60 % de los trabajos rechaza la eficiencia del mercado, el 35 % presenta evidencia de eficiencia, y el 5 % restante verifica una mejora progresiva de la eficiencia debida a reformas económicas, mayor velocidad en el flujo de información y el lanzamiento de nuevos productos financieros.

Referencias bibliográficas

  • Ahmed, E., Barkley, J. & Uppal, J. (1999). Evidence of nonlinear speculative bubbles in pacificrim stock markets. The quarterly review of economics and finance, 39, 21-36.
  • Akerlof, G. (1970). The market for “Lemons”: Quality uncertainty and the market mechanism. The Quarterly Journal of Economics, 84(3), 488-500.
  • Al Janabi, M., Hatemi-J, A. & Irandoust, M. (2010). An empirical investigation of the informational efficiency of the GCC equity markets: Evidence from bootstrap simulation. International Review of Financial Analysis, 19(1), 47-54.
  • Alagidede, P. (2011). Return behaviour in Africa’s emerging equity markets. The Quarterly Review of Economics and Finance, 51(2), 133-140.
  • Al-Hajieh, H., Redhead, K. & Rodgers, T. (2011). Investor sentiment and calendar anomaly effects: Acase studyofthe impact ofRamadan on Islamic Middle Eastern markets. Research in International Business and Finance, 25(3), 345-356.
  • Ammermann, P. & Patterson, D. (2003). The cross-sectional and cross-temporal universality of nonlinear serial dependencies: Evidence from world stock indices and the Taiwan Stock Exchange. Pacific-Basin Finance Journal, 11(2), 175-195.
  • Ansari, T., Kumar, M., Shukla, A., Dhar, J. & Tiwari, R. (2010). Sequential combination of statistics, econometrics and Adaptive Neural-Fuzzy Interface for stock market. Expert Systems with Applications, 37(7), 5116-5125.
  • Appiah, J. & Menyah, K. (2003). Return predictability in african stock markets. Review of financial economics, 12(3), 247-270.
  • Aragonés, J. & Mascareñas, J. (1994). La eficiencia y el equilibrio en los mercados de capital. Análisis Financiero, 64, 76-89.
  • Atteberry, W. & Swanson, P. (1997). Equity market integration: The case of North America. The North American Journal of Economics and Finance, 8(1), 23-37.
  • Bachelier, L. (1900). Théorie de la spéculation. Annales scientifiques de l’École Normale Supérieure, 17, 21-86.
  • Badii, M. & Guillen, A. (2009). Decisiones estadísticas: Bases teóricas: (Statistical Decision Making: Theoretical Basis). International Journal of Good Conscience, 5, 185-207.
  • Bastos, J. & Caiado, J. (2011). Recurrence quantification analysis of global stock markets. Physica A: Statistical Mechanics and its Applications, 390(7), 1315-1325.
  • Bekiros, S. (2010). Fuzzy adaptive decision-making for boundedly rational traders in speculative stock markets. European Journal of Operational Research, 202, 285-293.
  • Bley, J. (2011). Are GCC stock markets predictable?Emerging Markets Review, 12(3), 217-237.
  • Brock,W., Lakonishok, J. & LeBaron, B. (1992). Simple technical trading rules and the stochastic: properties of stock returns. Journal of Finance, 47(5), 1731-1764.
  • Buguk, C. &Wade, B. (2003). Testing weak-form market efficiency: Evidence from the Istanbul Stock Exchange. International Review of Financial Analysis, 12(5), 579-590.
  • Busse, J. & Clifton, T. (2002). Market efficiency in real time. Journal of Financial Economics, 65(3), 415-437.
  • Cajueiro, D. & Tabak, B. (2004). Evidence of long range dependence in Asian equitymarkets: the role of liquidity and market restrictions. Physica A: Statistical Mechanics and its Applications, 342(3-4), 656 664.
  • Caraiani, P. (2012). Nonlinear dynamics in CEE stock markets indices. Economics Letters,114(3), 329-331.
  • Cardano, G. (1953). The Book on Games of Chance (Liber de Ludo Aleae). (S. H. Gould, Trad.) Nueva York: Holt, Rinehart and Winston.
  • Coakley, J. & Fuertes, A. (2006). Valuation ratios and price deviations from fundamentals. Journal of Banking and Finance, 30(8), 2325-2346.
  • Couillard, M. & Davison, M. (2005). Acomment on measuring the Hurst exponent of financial time series. Physica A: Statistical Mechanics and its Applications, 348, 404-418.
  • Cowles, A. (1933). Can stock market forecasters forecast? Econometrica, 309-324.
  • Chan, K., McQueen, G. & Thorley, S. (1998). Are there rational speculative bubbles in Asian stock markets? Pacific-Basin Finance Journal, 6(1-2), 125-151.
  • Chang, E., Lima, E. & Tabak, B. (2004). Testing for predictabilityin emerging equitymarkets.Emerging Markets Review, 5(3), 295-316.
  • Charles, A. (2010). The day-of-the-week effects on the volatility: The role of the asymmetry. European Journal of Operational Research, 202(1), 143-152.
  • Chen, C. W., Gerlach, R. & Liu, F.-C. (2011). Detection of structural breaks in a time-varying heteroskedastic regression model. Journal of Statistical Planning and Inference, 141(11), 3367-3381.
  • Chen, C., Huang, C. & Lai, H. (2009). The impact of data snooping on the testing of technical analysis: An empirical study ofAsian stock markets. Journal of Asian Economics, 20(5), 580-591.
  • Cheng, H. & Ying, K. (2009). Testing the significance of solar term effect in the Taiwan stock market. Expert Systems with Applications, 36(3, Part 2), 6140-6144.
  • Chong, T., Lam, T. & Yan, I. (2012). Is the Chinese stock market really inefficient? China Economic Review, 23(1), 122-137.
  • Day, T. & Wang, P. (2002). Dividends, nonsynchronous prices, and the returns from trading the DJIA. Journal of empirical finance, 9(4), 431 454.
  • Del Villar, R., Murillo, J. & Backal, D. (1998). La crisis financiera en Asia: orígenes y evolución en 1997 y 1998. Dirección General de Investigación Económica. Banco de México, 42.
  • DePenya, F. J. & Gil, L. (2007). Serial correlation in the Spanish stock market. Global Finance Journal, 18, 84-103.
  • Dicle, M. & Levendis, J. (2011). Greek market efficiency and its international integration.Journal of International Financial Markets, Institutions and Money, 21(2), 229-246.
  • Dionisio, A., Menezes, R. &Mendes, D. (2004). Mutual information: a measure of dependency for nonlinear time series. Physica A: Statistical Mechanics and its Applications, 344(1- 2), 326-329.
  • Doyle, J. & Chen, C. (2012). Patterns in stock market movements tested as random number generators. European Journal of Operational Research, 227(1), 122 132.
  • Easley, D., Kiefer, N. & O’Hara, M. (1997). The information content of the trading process. Journal of Empirical Finance, 4(2-3), 159-186. Edwards, S. & Susmel, R. (2001). Volatility dependence and contagion in emerging equity markets. Journal of Development Economics, 66(2), 505-532.
  • Ellis, C. & Parbery, S. (2005). Is smarter better? A comparison of adaptive, and simple moving average trading strategies. Research in International Business and Finance, 19(3), 399- 411.
  • Eom, C., Choi, S., Oh, G. & Jung,W. (2008). Hurst exponent and prediction based on weak-form efficient market hypothesis of stock markets. Physica A: Statistical Mechanics and its Applications, 387(18), 4630-4636.
  • Esfahanipour,A. &Mousavi, S. (2011). A genetic programming model to generate risk-adjusted technical trading rules in stock markets. Expert Systems with Applications, 38(7), 8438- 8445.
  • Fama, E. (1965). The behavior of stock-market prices. Journal of business, 38(1), 34-105.
  • Fama, E. (1970). Efficient capital markets: A review of theory and empirical work. Journal Of Finance, 25, 383-417.
  • Fama, E. (1991). Efficient capital markets II. The journal of finance, 46(5), 1575-1617.
  • Fernández, F. & González, C. (2000). Optimización de reglas técnicas en el IGBM usando algoritmos genéticos. Comunicaciones XIV Reunión: Anales de Economía Aplicada.Oviedo.
  • Fernández, L. (2002). Reformas de las empresas estatales y politica de reempleo en China. Revista ICE, 797, 101-117.
  • Ferreira, E. & Brooks, L. (1999). Evidence on equity private placements and going-out-ofbusiness information release. Journal of economics and business, 51(5), 377 394.
  • Fifield, S. & Jetty, J. (2008). Further evidence on the efficiency of the Chinese stock markets: A note. Research in International Business and Finance, 22(3), 351 361.
  • Freitas, F., De Souza, A. & De Almeida, A. (2009). Prediction-based portfolio optimization model using neural networks. Neurocomputing, 72(10-12), 2155 2170.
  • Friedman, M. & Friedman, R. (1980). Free to choose: A personal statement.(C. R. Pujol, Trad.)Nueva York: Ediciones Orbis S.A.
  • Gaunt, C. (2000). Overreaction in theAustralian equitymarket: 1974 1997. Pacific-Basin Finance Journal, 8(3-4), 375-398.
  • Gençay, R. (1998). The predictability of security returns with simple technical trading rules.Journal of Empirical Finance, 5(4), 347-359.
  • Groenewold, N., Kan, S. &Wu, Y. (2003). The efficiency of theChinese stock market and the role of the banks. Journal of Asian Economics, 14(4), 593-609. Grossman, S., y Stiglitz, J. (1980). On the Impossibility ofInformationally Efficient Markets. 70(3), 393-408.
  • Gu, G., Ren, F., Ni, X., Chen, W. & Zhou, W. (2010). Empirical regularities of opening call auction in Chinese stock market. Physica A: Statistical Mechanics and its Applications, 389(2), 278-286.
  • Gupta, R. & Modise, M. (2013). Macroeconomic variables and south african stock return predictability. Economic Modelling, 30, 612-622.
  • Hatgioannides, J. & Mesomeris, S. (2007). On the returns generating process and the profitability of trading rules in emerging capital markets. Journal of International Money and Finance,26(6), 948-973.
  • Hess, M. (2003). What drives Markov regime-switching behavior of stock markets? The Swiss case. International Review of Financial Analysis, 12(5), 527-543.
  • Hoque, H., Kim, J. & Pyun, C. (2007). Acomparison of variance ratio tests of random walk: A case of Asian emerging stock markets. International Review of Economics y Finance, 16(4), 488-502.
  • Hung, J. (2009). Deregulation and liberalization of the Chinese stock market and the improvement of market efficiency. The Quarterly Review of Economics and Finance, 49(3), 843-857.
  • Jayasinghe, P. & Tsui, A. (2008). Exchange rate exposure of sectoral returns and volatilities: Evidence from Japanese industrial sectors. Japan and the World Economy, 20(4), 639- 660.
  • Jiang, J., Ma, K. & Cai, X. (2007). Non-linear characteristics and long range correlations in Asian stock markets. Physica A: Statistical Mechanics and its Applications, 378(2), 399-407.
  • Kaminsky, G. & Schmukler, S. (1999). What triggers market jitters? A chronicle of the Asian crisis. Journal of International Money and Finance, 18, 537"560.
  • Kang, S., Cheong, C. & Yoon, S. (2010). Long memory volatility in Chinese stock markets. Physica A: Statistical Mechanics and its Applications, 389(7), 1425 1433.
  • Kasman, A. & Kasman, S. (2008). The impact of futures trading on volatility of the underlying asset in the Turkish stock market. Physica A: Statistical Mechanics and its Applications, 387(12), 2837-2845.
  • Kasman,A., Kasman, S. &Torun, E. (2009). Dual long memorypropertyin returns and volatility: Evidence from the CEE countries’ stock markets. Emerging Markets Review, 10(2), 122- 139.
  • Kawakatsu, H. & Morey, M. (1999). Financial liberalization and stock market efficiency: an empirical examination of nine emerging market countries. Journal of Multinational Financial Management, 9(3-4), 353-371.
  • Kendall, M. (1953). The analysis of economic time-series-part I: prices. Journal of the Royal Statistical Society. Series A (General), 116, 11-25.
  • Khan,W. & Vieito, J. (2012). Stock exchange mergers and weak form of market efficiency: The case of Euronext Lisbon. International Review of Economics y Finance, 22(1), 173-189.
  • Kiliç, R. (2011). Long memory and nonlinearity in conditional variances: A smooth transition FIGARCH model. Journal of Empirical Finance, 18(2), 368-378.
  • Kim, J., Shamsuddin, A. & Lim, K. (2011). Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data. Journal of Empirical Finance, 18(5), 868-879.
  • Klein, N. (2007). La doctrina del shock: El auge del capitalismo del desastre. Knopf, Canada: Editorial Paidos.
  • Kohers, T., Pandey, V. & Kohers, G. (1997). Using nonlinear dynamics to test for market efficiency among the major U.S. stock exchanges. The Quarterly Review of Economics and Finance, 37(2), 523-545.
  • Lao, P. & Singh, H. (2011). Herding behaviour in the Chinese and Indian stock markets. Journal of Asian Economics, 22(6), 495-506.
  • Lee, C., Lee, J. & Lee, C. (2010). Stock prices and the efficient market hypothesis: Evidence from a panel stationary test with structural breaks. Japan and the World Economy, 22(1), 49-58.
  • Lee, J., Park, J., Jo, H., Yang, J. & Moon, H. (2009). Minimum entropy density method for the time series analysis. Physica A: Statistical Mechanics and its Applications, 388(2-3), 137-144.
  • Lim, K. (2007). Ranking market efficiency for stock markets: A nonlinear perspective. Physica A: Statistical Mechanics and its Applications, 376, 445-454.
  • Lim, K. & Brooks, R. (2009). Price limits and stock market efficiency: Evidence from rolling bicorrelation test statistic. Chaos, Solitons y Fractals, 40(3), 1271-1276.
  • Lim, K., Brooks, R. & Kim, J. (2008). Financial crisis and stock market efficiency: Empirical evidence from Asian countries. International Review of Financial Analysis, 17(3), 571- 591.
  • Liu, S. (2007). International cross-listing and stock pricing efficiency: An empirical study. Emerging Markets Review, 8(4), 251-263.
  • Lobe, S. & Rieks, J. (2011). Short-term market overreaction on the Frankfurt stock exchange. The Quarterly Review of Economics and Finance, 51(2), 113-123.
  • López, I. (2007). El proceso de integración de los mercados financieros en Europa. Escuela de Administración de Negocios, 59, 87-97.
  • Lu, T., Shiu, Y. & Liu, T. (2012). Profitable candlestick trading strategies-The evidence from a new perspective. Review of Financial Economics, 21(2), 63-68.
  • Ludlow, J. (1997). Modelos, pronósticos y volatilidad de las series de tiempo generadas en la bolsa mexicana de valores. Azcapotzalco: Universidad Autónoma Metropolitana Azcapotzalco.
  • Majumder, D. (2012). When the market becomes inefficient: Comparing BRIC markets with markets in the USA. International Review of Financial Analysis, 24, 84-92.
  • Malkiel, B. (1992). Efûcient market hypothesis. En M. M. P. Newman (Ed.), New Palgrave Dictionary of Money and Finance. Londres Macmillan.
  • Mandelbrot, B. (1963). New methods in statistical economics. Journal of Political Economy, 71, 421-440.
  • Mansilla, R. (2001). Algorithmic complexity of real financial markets. Physica A: Statistical Mechanics and its Applications, 301(1-4), 483-492.
  • Marshall, B., Cahan, J., yCahan, R. (2006). Is the CRISMAtechnical trading system profitable? Global Finance Journal, 17(2), 271-281.
  • Marshall, B., Young, M. & Rose, L. (2006). Candlestick technical trading strategies: Can they create value for investors? Journal of Banking y Finance, 30(8), 2303 2323.
  • Martínez, M. (Junio de 2001). Privatizaciones y Reforma del Sector Público en China. Recuperado el Diciembre de 2012, de ICEX: España Exportación e Inversiones: http:// www.icex.es/ ser vici os/ documentaci on/ document osela bor a dos/icex/ pd fs/ privatizaciones%20reformas%20sector%20publico%20china.pdf
  • Mazouz, K. & Bowe, M. (2006). The volatility effect of futures trading: Evidence from LSE traded stocks listed as individual equity futures contracts on LIFFE. International Review of Financial Analysis, 15(1), 1-20.
  • McKenzie, M. (2001). Chaotic behavior in national stock market indices: New evidence from the close returns test. Global Finance Journal, 12(1), 35-53.
  • Metghalchi, M., Chang,Y. &Marcucci, J. (2008). Is the Swedish stock market efficient? Evidence from some simple trading rules. International Review of Financial Analysis, 17(3), 475- 490.
  • Mishra, R., Sehgal, S. & Bhanumurthy, N. (2011). A search for long range dependence and chaotic structure in Indian stock market. Review of Financial Economics, 20(2), 96-104.
  • Moreno, D. & Olmeda, I. (2007). Is the predictability of emerging and developed stock markets really exploitable? European Journal of Operational Research, 182(1), 436-454.
  • Mulligan, R. & Lombardo, G. (2004). Maritime businesses: volatile stock prices and market valuation inefficiencies. The Quarterly Review of Economics and Finance, 44(2), 321- 336.
  • Opong, K., Mulholland, G., Fox, A. & Farahmand, K. (1999). The behaviour of some UK equity indices: An application of Hurst and BDS tests. Journal of Empirical Finance, 6(3), 267- 282.
  • Osborne, M. (1959). Brownian motion in the stock market. Operations Research, 7(2), 145- 733.
  • Parhizgari, A. & Nguyen, D. (2008). ADRs under momentum and contrarian strategies. Global Finance Journal, 19(2), 102-122
  • Peters, E. (1994). Fractal market analysis: Applying chaos theory to investment and economics. Nueva York: Wiley Finance Editions.
  • Porter, M. & Takeuchi, H. (1999). Fixing what really ails japan. Foreign Affairs, 3, 66-81.
  • Potvin, J., Soriano, P. & Vallée, M. (2004). Generating trading rules on the stock markets with genetic programming. Computers and Operations Research, 31(7), 1033-1047.
  • Ratner, M. & Leal, R. (1999). Tests of technical trading strategies in the emerging equity markets of Latin America and Asia. Journal of banking y finance, 23(12), 1887-1905.
  • Raunig, B. (2006). The longer-horizon predictability of German stock market volatility. International Journal of Forecasting, 22(2), 363-372.
  • Roberts, H. (1959). Stock market “patterns” and financial analysis: Methodological suggestions. The Journal of Finance, 14, 1-10.
  • Roberts, H. (1967). Statistical versus clinical prediction of the stock market. Chicago: Unpublished manuscript, University of Chicago.
  • Salm, C. & Schuppli, M. (2010). Positive feedback trading in stock index futures: International evidence. International Review of Financial Analysis, 19(5), 313-322.
  • Samuelson, P. (1965). Proof that properly anticipated prices fluctuate randomly. Industrial Management Review, 6(2), 41-49.
  • Sánchez, M., Trinidad, J. & García, J. (2008). Some comments on Hurst exponent and the long memory processes on capital markets. Physica A: Statistical Mechanics and its Applications, 387(22), 5543-5551.
  • Sarmiento, P., Duarte, J. & Mascareñas, J. (2012). Análisis de causalidad entre mercados bursátiles latinoamericanos Yel Standard y Poor’s. 1er Congreso Global de Contabilidad y Finanzas. Bogotá: Universidad Nacional.
  • Serletis, A. & Shintani, M. (2003). No evidence of chaos but some evidence of dependence in the US stock market. Chaos, Solitons y Fractals, 17(2-3), 449-454.
  • Sharma, S. & Wongbangpo, P. (2002). Long-term trends and cycles in ASEAN stock markets. Review of Financial Economics, 11(4), 299-315.
  • Shleifer, A. (2003). Are financial markets efficient? En A. Shleifer, Inefficient Markets:An Introduction to Behavioral Finance. Oxford: Oxford University Press.
  • Shynkevich, A. (2012). Short-term predictability of equity returns along two style dimensions. Journal of Empirical Finance, 19(5), 675 685.
  • Spence, M. (1973). JobMarket Signaling. The quarterly journal of Economics, 87(3), 355-374.
  • Stiglitz, J. (2010). Freefall: America, free markets, and the sinking of the world economy. Nueva York: W. W. Norton.
  • Stiglitz, J. & Rothschild, M. (1976).Equilibrium in competitive insurance markets: an essay on the economics of imperfect information. The Quarterly Journal of Economics, 90(4), 629- 649.
  • Straßburg, J., González, C. &Alexandrov, V. (2012). Parallel genetic algorithms for stock market trading rules. Procedia Computer Science, 9, 1306-1313.
  • Tabak, B. (2007). Testing for unit root bilinearity in the Brazilian stock market. Physica A: Statistical Mechanics and its Applications, 385(1), 261-269.
  • Torrero,A. (2001). El final de la burbuja especulativa yla crisis económica de Japón. Economiaz, 48(3), 92 - 127.
  • Tse, Y. (1998). International transmission of information: evidence from the Euroyen and Eurodollar futures markets. Journal of International Money and Finance, 17(6), 909- 929.
  • Uribe, J. & Ulloa, I. (2011). Revisando la hipótesis de los mercados eficientes: Nuevos datos, nueva crisis, nuevas estimaciones. Banco de la República. 204. Bogotá: Seminario de economía.
  • Vayanos, D. &Woolley, P. (2013). An institutional theory of momentum and reserval. Review of Financial Studies, 26(5), 1087 1145.
  • Visaltanachoti, N. & Yang, T. (2010). Speed of convergence to market efficiency for NYSElisted foreign stocks. Journal of Banking y Finance, 34(3), 594-605.
  • Wu, P., Huang, C. & Chiu, C. (2011). Effects of structural changes on the risk characteristics of REIT returns. International review of economics y finance, 20(4), 645 653.