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¿Han sido los mercados bursátiles eficientes informacionalmente?

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.

Palabras clave

Hipótesis del mercado eficiente, mercados financieros. (Efficient market hypothesis, financial markets)

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Referencias

  1. 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.
  2. Akerlof, G. (1970). The market for “Lemons”: Quality uncertainty and the market mechanism. The Quarterly Journal of Economics, 84(3), 488-500.
  3. 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.
  4. Alagidede, P. (2011). Return behaviour in Africa’s emerging equity markets. The Quarterly Review of Economics and Finance, 51(2), 133-140.
  5. 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.
  6. 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.
  7. 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.
  8. Appiah, J. & Menyah, K. (2003). Return predictability in african stock markets. Review of financial economics, 12(3), 247-270.
  9. Aragonés, J. & Mascareñas, J. (1994). La eficiencia y el equilibrio en los mercados de capital. Análisis Financiero, 64, 76-89.
  10. 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.
  11. Bachelier, L. (1900). Théorie de la spéculation. Annales scientifiques de l’École Normale Supérieure, 17, 21-86.
  12. Badii, M. & Guillen, A. (2009). Decisiones estadísticas: Bases teóricas: (Statistical Decision Making: Theoretical Basis). International Journal of Good Conscience, 5, 185-207.
  13. Bastos, J. & Caiado, J. (2011). Recurrence quantification analysis of global stock markets. Physica A: Statistical Mechanics and its Applications, 390(7), 1315-1325.
  14. Bekiros, S. (2010). Fuzzy adaptive decision-making for boundedly rational traders in speculative stock markets. European Journal of Operational Research, 202, 285-293.
  15. Bley, J. (2011). Are GCC stock markets predictable?Emerging Markets Review, 12(3), 217-237.
  16. 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.
  17. 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.
  18. Busse, J. & Clifton, T. (2002). Market efficiency in real time. Journal of Financial Economics, 65(3), 415-437.
  19. 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.
  20. Caraiani, P. (2012). Nonlinear dynamics in CEE stock markets indices. Economics Letters,114(3), 329-331.
  21. Cardano, G. (1953). The Book on Games of Chance (Liber de Ludo Aleae). (S. H. Gould, Trad.) Nueva York: Holt, Rinehart and Winston.
  22. Coakley, J. & Fuertes, A. (2006). Valuation ratios and price deviations from fundamentals. Journal of Banking and Finance, 30(8), 2325-2346.
  23. 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.
  24. Cowles, A. (1933). Can stock market forecasters forecast? Econometrica, 309-324.
  25. 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.
  26. Chang, E., Lima, E. & Tabak, B. (2004). Testing for predictabilityin emerging equitymarkets.Emerging Markets Review, 5(3), 295-316.
  27. 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.
  28. 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.
  29. 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.
  30. 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.
  31. Chong, T., Lam, T. & Yan, I. (2012). Is the Chinese stock market really inefficient? China Economic Review, 23(1), 122-137.
  32. Day, T. & Wang, P. (2002). Dividends, nonsynchronous prices, and the returns from trading the DJIA. Journal of empirical finance, 9(4), 431 454.
  33. 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.
  34. DePenya, F. J. & Gil, L. (2007). Serial correlation in the Spanish stock market. Global Finance Journal, 18, 84-103.
  35. Dicle, M. & Levendis, J. (2011). Greek market efficiency and its international integration.Journal of International Financial Markets, Institutions and Money, 21(2), 229-246.
  36. 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.
  37. Doyle, J. & Chen, C. (2012). Patterns in stock market movements tested as random number generators. European Journal of Operational Research, 227(1), 122 132.
  38. 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.
  39. 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.
  40. 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.
  41. 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.
  42. Fama, E. (1965). The behavior of stock-market prices. Journal of business, 38(1), 34-105.
  43. Fama, E. (1970). Efficient capital markets: A review of theory and empirical work. Journal Of Finance, 25, 383-417.
  44. Fama, E. (1991). Efficient capital markets II. The journal of finance, 46(5), 1575-1617.
  45. Fernández, F. & González, C. (2000). Optimización de reglas técnicas en el IGBM usando algoritmos genéticos. Comunicaciones XIV Reunión: Anales de Economía Aplicada.Oviedo.
  46. Fernández, L. (2002). Reformas de las empresas estatales y politica de reempleo en China. Revista ICE, 797, 101-117.
  47. 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.
  48. 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.
  49. Freitas, F., De Souza, A. & De Almeida, A. (2009). Prediction-based portfolio optimization model using neural networks. Neurocomputing, 72(10-12), 2155 2170.
  50. Friedman, M. & Friedman, R. (1980). Free to choose: A personal statement.(C. R. Pujol, Trad.)Nueva York: Ediciones Orbis S.A.
  51. Gaunt, C. (2000). Overreaction in theAustralian equitymarket: 1974 1997. Pacific-Basin Finance Journal, 8(3-4), 375-398.
  52. Gençay, R. (1998). The predictability of security returns with simple technical trading rules.Journal of Empirical Finance, 5(4), 347-359.
  53. 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.
  54. 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.
  55. Gupta, R. & Modise, M. (2013). Macroeconomic variables and south african stock return predictability. Economic Modelling, 30, 612-622.
  56. 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.
  57. Hess, M. (2003). What drives Markov regime-switching behavior of stock markets? The Swiss case. International Review of Financial Analysis, 12(5), 527-543.
  58. 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.
  59. 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.
  60. 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.
  61. 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.
  62. Kaminsky, G. & Schmukler, S. (1999). What triggers market jitters? A chronicle of the Asian crisis. Journal of International Money and Finance, 18, 537"560.
  63. 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.
  64. 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.
  65. 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.
  66. 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.
  67. Kendall, M. (1953). The analysis of economic time-series-part I: prices. Journal of the Royal Statistical Society. Series A (General), 116, 11-25.
  68. 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.
  69. Kiliç, R. (2011). Long memory and nonlinearity in conditional variances: A smooth transition FIGARCH model. Journal of Empirical Finance, 18(2), 368-378.
  70. 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.
  71. Klein, N. (2007). La doctrina del shock: El auge del capitalismo del desastre. Knopf, Canada: Editorial Paidos.
  72. 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.
  73. Lao, P. & Singh, H. (2011). Herding behaviour in the Chinese and Indian stock markets. Journal of Asian Economics, 22(6), 495-506.
  74. 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.
  75. 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.
  76. Lim, K. (2007). Ranking market efficiency for stock markets: A nonlinear perspective. Physica A: Statistical Mechanics and its Applications, 376, 445-454.
  77. 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.
  78. 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.
  79. Liu, S. (2007). International cross-listing and stock pricing efficiency: An empirical study. Emerging Markets Review, 8(4), 251-263.
  80. 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.
  81. López, I. (2007). El proceso de integración de los mercados financieros en Europa. Escuela de Administración de Negocios, 59, 87-97.
  82. 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.
  83. Ludlow, J. (1997). Modelos, pronósticos y volatilidad de las series de tiempo generadas en la bolsa mexicana de valores. Azcapotzalco: Universidad Autónoma Metropolitana Azcapotzalco.
  84. Majumder, D. (2012). When the market becomes inefficient: Comparing BRIC markets with markets in the USA. International Review of Financial Analysis, 24, 84-92.
  85. Malkiel, B. (1992). Efûcient market hypothesis. En M. M. P. Newman (Ed.), New Palgrave Dictionary of Money and Finance. Londres Macmillan.
  86. Mandelbrot, B. (1963). New methods in statistical economics. Journal of Political Economy, 71, 421-440.
  87. Mansilla, R. (2001). Algorithmic complexity of real financial markets. Physica A: Statistical Mechanics and its Applications, 301(1-4), 483-492.
  88. Marshall, B., Cahan, J., yCahan, R. (2006). Is the CRISMAtechnical trading system profitable? Global Finance Journal, 17(2), 271-281.
  89. 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.
  90. 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
  91. 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.
  92. McKenzie, M. (2001). Chaotic behavior in national stock market indices: New evidence from the close returns test. Global Finance Journal, 12(1), 35-53.
  93. 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.
  94. 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.
  95. 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.
  96. 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.
  97. 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.
  98. Osborne, M. (1959). Brownian motion in the stock market. Operations Research, 7(2), 145- 733.
  99. Parhizgari, A. & Nguyen, D. (2008). ADRs under momentum and contrarian strategies. Global Finance Journal, 19(2), 102-122
  100. Peters, E. (1994). Fractal market analysis: Applying chaos theory to investment and economics. Nueva York: Wiley Finance Editions.
  101. Porter, M. & Takeuchi, H. (1999). Fixing what really ails japan. Foreign Affairs, 3, 66-81.
  102. 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.
  103. 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.
  104. Raunig, B. (2006). The longer-horizon predictability of German stock market volatility. International Journal of Forecasting, 22(2), 363-372.
  105. Roberts, H. (1959). Stock market “patterns” and financial analysis: Methodological suggestions. The Journal of Finance, 14, 1-10.
  106. Roberts, H. (1967). Statistical versus clinical prediction of the stock market. Chicago: Unpublished manuscript, University of Chicago.
  107. Salm, C. & Schuppli, M. (2010). Positive feedback trading in stock index futures: International evidence. International Review of Financial Analysis, 19(5), 313-322.
  108. Samuelson, P. (1965). Proof that properly anticipated prices fluctuate randomly. Industrial Management Review, 6(2), 41-49.
  109. 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.
  110. 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.
  111. 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.
  112. Sharma, S. & Wongbangpo, P. (2002). Long-term trends and cycles in ASEAN stock markets. Review of Financial Economics, 11(4), 299-315.
  113. Shleifer, A. (2003). Are financial markets efficient? En A. Shleifer, Inefficient Markets:An Introduction to Behavioral Finance. Oxford: Oxford University Press.
  114. Shynkevich, A. (2012). Short-term predictability of equity returns along two style dimensions. Journal of Empirical Finance, 19(5), 675 685.
  115. Spence, M. (1973). JobMarket Signaling. The quarterly journal of Economics, 87(3), 355-374.
  116. Stiglitz, J. (2010). Freefall: America, free markets, and the sinking of the world economy. Nueva York: W. W. Norton.
  117. 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.
  118. Straßburg, J., González, C. &Alexandrov, V. (2012). Parallel genetic algorithms for stock market trading rules. Procedia Computer Science, 9, 1306-1313.
  119. Tabak, B. (2007). Testing for unit root bilinearity in the Brazilian stock market. Physica A: Statistical Mechanics and its Applications, 385(1), 261-269.
  120. Torrero,A. (2001). El final de la burbuja especulativa yla crisis económica de Japón. Economiaz, 48(3), 92 - 127.
  121. 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.
  122. 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.
  123. Vayanos, D. &Woolley, P. (2013). An institutional theory of momentum and reserval. Review of Financial Studies, 26(5), 1087 1145.
  124. Visaltanachoti, N. & Yang, T. (2010). Speed of convergence to market efficiency for NYSElisted foreign stocks. Journal of Banking y Finance, 34(3), 594-605.
  125. 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.

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