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Análisis de la efectividad y estabilidad de una combinación de indicadores de Análisis Técnico (Estocástico y el Índice de Fuerza Relativa) en el mercado accionario colombiano en el Período 2009 – 2019

dc.rights.licenseAtribución-NoComercial-SinDerivadas 4.0 Internacional
dc.contributor.advisorVillota Gómez, Andrés Gerardo
dc.contributor.advisorGarcía Molina, Mario
dc.contributor.authorRomero Oses, Juan Sebastian
dc.date.accessioned2021-01-22T17:18:08Z
dc.date.available2021-01-22T17:18:08Z
dc.date.issued2020-10-20
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/78878
dc.description.abstractEl objetivo de la presente investigación es analizar el efecto de una combinación de indicadores técnicos en el mercado accionario colombiano en términos de efectividad y estabilidad durante el periodo 2009-2019. Para tal fin se utilizaron dos indicadores populares y que han demostrado en diversas investigaciones obtener buenos resultados como el Índice de Fuerza Relativa y el Indicador Estocástico para generar un solo indicador, el cual se va a llamar combinación. Las rentabilidades obtenidas fueron comparadas con la estrategia pasiva y los resultados fueron contrastados con la Hipótesis de Mercados Eficientes y la Teoría de la Caminata aleatoria mediante pruebas de robustez y simulación Bootstrapping para validar la significancia estadística de los resultados. La evidencia empírica de la investigación sugiere que, luego de incluir los costos de transacción, tanto la combinación como los indicadores técnicos por separado no superaron de manera efectiva y estable a la estrategia pasiva.
dc.description.abstractThe objective of this research is to analyses the effect of a combination of technical indicators on the Colombian stock market in terms of effectiveness and stability during the 2009-2019 period. For this purpose, two popular indicators were used that have been shown in many researches to obtain good results such as the Relative Strength Index and the Stochastic Indicator to generate a single indicator, this is called combination. The yields obtained were compared with the passive strategy and the results were contrasted with the Efficient-Market Hypothesis and the Theory of the Random Walk through robustness tests and Bootstrapping simulation to validate the statistical significance of the results. Empirical evidence from the research suggests that, after including transaction costs, both the combination and the separate technical indicators do not effectively and stably beat the passive strategy.
dc.format.extent111
dc.format.mimetypeapplication/pdf
dc.language.isospa
dc.rightsDerechos reservados - Universidad Nacional de Colombia
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.ddc330 - Economía::332 - Economía financiera
dc.titleAnálisis de la efectividad y estabilidad de una combinación de indicadores de Análisis Técnico (Estocástico y el Índice de Fuerza Relativa) en el mercado accionario colombiano en el Período 2009 – 2019
dc.typeOtro
dc.rights.spaAcceso abierto
dc.description.additionalLínea de Investigación: Gestión Financiera
dc.type.driverinfo:eu-repo/semantics/other
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dc.publisher.programBogotá - Ciencias Económicas - Maestría en Administración
dc.description.degreelevelMaestría
dc.publisher.departmentEscuela de Administración y Contaduría Pública
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotá
dc.relation.referencesAbbey, B., & A Doukas, J. (2012). Is Technical Analysis Profitable forIndividual Currency Traders? The Journal of Portfolio Management (Vol. 39). https://doi.org/10.3905/jpm.2012.39.1.142
dc.relation.referencesAgudelo Rueda, D. A., & Uribe Estrada, J. H. (2009). ¿Realidad o Sosfisma? Poniendo a Prueba el Análisis Técnico en las Acciones Colombianas. Cuadernos de Administración, 22(38), 189–217. Retrieved from https://www.redalyc.org/articulo.oa?id=20511730010
dc.relation.referencesAhmad, K., Ashraf, S., & Ahmed, S. (2006). Testing Weak Form Efficiency for Indian Stock Markets. Economic and Political Weekly, 41. https://doi.org/10.2307/4417642
dc.relation.referencesAhmadi, E., Jasemi, M., Monplaisir, L., Nabavi, M. A., Mahmoodi, A., & Amini Jam, P. (2018). New efficient hybrid candlestick technical analysis model for stock market timing on the basis of the Support Vector Machine and Heuristic Algorithms of Imperialist Competition and Genetic. Expert Systems with Applications, 94, 21–31. https://doi.org/10.1016/J.ESWA.2017.10.023
dc.relation.referencesAl-Abdulqader, K. A., Hannah, G., & Power, D. M. (2007). The appraisal of ordinary shares by Saudi investors. Research in International Business and Finance, 21(1), 69–86. https://doi.org/10.1016/J.RIBAF.2005.08.004
dc.relation.referencesAlhashel, B. S., Almudhaf, F. W., & Hansz, J. A. (2018). Can technical analysis generate superior returns in securitized property markets? Evidence from East Asia markets. Pacific-Basin Finance Journal, 47, 92–108. https://doi.org/10.1016/J.PACFIN.2017.12.005
dc.relation.referencesAllen, F., & Karjalainen, R. (1999). Using genetic algorithms to find technical trading rules. Journal of Financial Economics, 51(2), 245–271. https://doi.org/10.1016/S0304-405X(98)00052-X
dc.relation.referencesAlmujamed, H. I., Fifield, S., & Power, D. (2013). An investigation of the role of technical analysis in Kuwait. Qualitative Research in Financial Markets, 5(1), 43–64.
dc.relation.referencesAnghel, D. (2017). Intraday market efficiency for a typical central and eastern european stock market: The case of Romania. Romanian Journal of Economic Forecasting, 20, 88–109.
dc.relation.referencesAsad Khan, M. (2016). Technical Analysis: Concept or Reality?, 18, 732–751. Ausloos, M., & Ivanova, K. (2002). Mechanistic approach to generalized technical analysis of share prices and stock market indices. European Physical Journal B (Vol. 27). https://doi.org/10.1140/epjb/e20020144
dc.relation.referencesBaba, N., & Nomura, T. (2005). An Intelligent Utilization of Neural Networks for Improving the Traditional Technical Analysis in the Stock Markets BT - Knowledge-Based Intelligent Information and Engineering Systems. In R. Khosla, R. J. Howlett, & L. C. Jain (Eds.) (pp. 8–14). Berlin, Heidelberg: Springer Berlin Heidelberg.
dc.relation.referencesBallings, M., Van den Poel, D., Hespeels, N., & Gryp, R. (2015). Evaluating multiple classifiers for stock price direction prediction. Expert Systems with Applications, 42(20), 7046–7056. https://doi.org/10.1016/J.ESWA.2015.05.013
dc.relation.referencesBanco de la Republica. (2018). No Title. Retrieved from www.banrep.gov.co
dc.relation.referencesBessembinder, H., & Chan, K. (1995). The profitability of technical trading rules in the Asian stock market. Pacific-Basin Finance Journal (Vol. 3). https://doi.org/10.1016/0927-538X(95)00002-3
dc.relation.referencesBessembinder, H., & Chan, K. (1998). Market Efficiency and the Returns to Technical Analysis. Financial Management, 27(2), 5. https://doi.org/10.2307/3666289
dc.relation.referencesBettman, J., Sault, S., & Schultz, E. (2009). Fundamental and technical analysis: Substitutes or complements? Accounting and Finance (Vol. 49). https://doi.org/10.1111/j.1467-629X.2008.00277.x
dc.relation.referencesBianchi, S., & Pianese, A. (2018). Time-varying Hurst–Hölder exponents and the dynamics of (in)efficiency in stock markets. Chaos, Solitons & Fractals, 109, 64–75. https://doi.org/10.1016/J.CHAOS.2018.02.015
dc.relation.referencesBrock, W., Lakonishok, J., & LeBaron, B. (1992). Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. The Journal of Finance, 47(5), 1731–1764. https://doi.org/10.1111/j.1540-6261.1992.tb04681.x
dc.relation.referencesBruni, R. (2017). Stock Market Index Data and indicators for Day Trading as a Binary Classification problem. Data in Brief, 10, 569–575. https://doi.org/10.1016/j.dib.2016.12.044
dc.relation.referencesBVC. (2008). Bolsa de Valores de Colombia. Retrieved April 3, 2018, from https://www.bvc.com.co/pps/tibco/portalbvc/Home/Empresas/Listado+de+Emisores
dc.relation.referencesCastillo Giraldo, E. M. (2011). Evaluacion de estrategias de inversion utilizando herramientas de analisis tecnico aplicadas al mercado colombiano. Universidad Nacional de Colombia, Sede Medell�����n. Retrieved from http://www.bdigital.unal.edu.co/5137/
dc.relation.referencesCervelló-Royo, R., Guijarro, F., & Michniuk, K. (2015). Stock market trading rule based on pattern recognition and technical analysis: Forecasting the DJIA index with intraday data. Expert Systems with Applications, 42(14). https://doi.org/10.1016/j.eswa.2015.03.017
dc.relation.referencesCervelló Royo, R., Guijarro Martínez, F., & Michniuk, K. (2014). Estrategia de inversión bursátil y reconocimiento gráfico de patrones: aplicación sobre datos intradía del índice Dow Jones . Cuadernos de Administración . scieloco .
dc.relation.referencesChande, T., & Kroll, S. (1994). The New Technical Trader: Boost Your Profit by Plugging into the Latest Indicators. (W. Finance, Ed.).
dc.relation.referencesChang, E. J., Araújo Lima, E. J., & Tabak, B. M. (2004). Testing for predictability in emerging equity markets. Emerging Markets Review, 5(3), 295–316. https://doi.org/10.1016/j.ememar.2004.03.005
dc.relation.referencesChang, E., Lima, E., & Tabak, B. (2004). Testing for predictability in emerging equity markets. Emerging Markets Review, 5(3), 295–316.
dc.relation.referencesChang, H., & An, G. (2019). Will History Repeat Itself? Empirical Research on A-Share Candlesticks in China Based on Matching Method. Journal of Applied Finance & Banking (Vol. 9). online) Scienpress Ltd.
dc.relation.referencesChang, Y., Metghalchi, M., & Chan, C. (2006). Technical trading strategies and cross-national information linkage: the case of Taiwan stock market. Applied Financial Economics, 16(10), 731–743. https://doi.org/10.1080/09603100500426374
dc.relation.referencesCharles, A., Darné, O., & Kim, J. H. (2017). International stock return predictability: Evidence from new statistical tests. International Review of Financial Analysis, 54, 97–113. https://doi.org/10.1016/J.IRFA.2016.06.005
dc.relation.referencesChavarnakul, T., & Enke, D. (2008). Intelligent technical analysis based equivolume charting for stock trading using neural networks. Expert Systems with Applications,34(2), 1004–1017. https://doi.org/10.1016/j.eswa.2006.10.028
dc.relation.referencesChen, C., Huang, C., & Lai, H. (2011). Data Snooping on Technical Analysis: Evidence from the Taiwan Stock Market. Review of Pacific Basin Financial Markets and Policies (RPBFMP), 14, 195–212. https://doi.org/10.1142/S0219091511002238
dc.relation.referencesChen, C. W., Huang, C. S., & Lai, H. W. (2009). The impact of data snooping on the testing of technical analysis: An empirical study of Asian stock markets. Journal of Asian Economics, 20(5), 580–591. https://doi.org/10.1016/j.asieco.2009.07.008
dc.relation.referencesChen, H., Lee, C., & Shih, W. (2016). Technical, fundamental, and combined information for separating winners from losers. Pacific-Basin Finance Journal, 39, 224–242. https://doi.org/10.1016/J.PACFIN.2016.06.008
dc.relation.referencesChen, Y., Chen, Y., Tsao, S., & Hsieh, S. (2016). A novel technical analysis-based method for stock market forecasting. Soft Computing (Vol. 22). https://doi.org/10.1007/s00500-016-2417-2
dc.relation.referencesCheol‐Ho, P., & H., I. S. (2007). What Do We Know About The Profitability Of Technical Analysis? Journal of Economic Surveys, 21(4), 786–826. https://doi.org/10.1111/j.1467-6419.2007.00519.x
dc.relation.referencesCheung, W., Lam, K. S. K., & Yeung, H. (2011). Intertemporal profitability and the stability of technical analysis: evidences from the Hong Kong stock exchange. Applied Economics, 43(15), 1945–1963. https://doi.org/10.1080/00036840902817805
dc.relation.referencesChiang, Y.-C., Ke, M.-C., Liao, T. L., & Wang, C.-D. (2012). Are technical trading strategies still profitable? Evidence from the Taiwan Stock Index Futures Market. Applied Financial Economics, 22(12), 955–965. https://doi.org/10.1080/09603107.2011.631893
dc.relation.referencesChong, T, Lam, T., & Yan, I. (2012). Is the Chinese stock market really inefficient? China Economic Review, 23(1), 122–137. https://doi.org/10.1016/j.chieco.2011.08.003
dc.relation.referencesChong, T, & Ng, W. (2008). Technical analysis and the London stock exchange: testing the MACD and RSI rules using the FT30. Applied Economics Letters, 15(14), 1111–1114. https://doi.org/10.1080/13504850600993598
dc.relation.referencesChong, Terence, & Lam, T. (2013). How to make a profitable trading strategy more profitable? The Singapore Economic Review, 58. https://doi.org/10.1142/S0217590813500197
dc.relation.referencesChong, Terence, Ng, W.-K., & Liew, V. (2014). Revisiting the Performance of MACD and RSI Oscillators. Journal of Risk and Financial Management, 7, 1–12.
dc.relation.referencesCoe, T. S., & Laosethakul, K. (2010). Should Individual Investors Use Technical Trading Rules to Attempt to Beat the Market? American Journal of Economics and Business Administration, 3. https://doi.org/10.3844/ajebasp.2010.201.209
dc.relation.referencesCohen, G., & Cabiri, E. (2015). Can technical oscillators outperform the buy and hold strategy? Applied Economics, 47(30), 3189–3197. https://doi.org/10.1080/00036846.2015.1013609
dc.relation.referencesContreras, O. E., Stein Bronfman, R., & Vecino Arenas, C. E. (2015). Estrategia de inversión optimizando la relación rentabilidad-riesgo: evidencia en el mercado accionario colombiano. Estudios Gerenciales, 31(137), 383–392. https://doi.org/10.1016/J.ESTGER.2015.07.005
dc.relation.referencesDay, T. E., & Wang, P. (2002). Dividends, nonsynchronous prices, and the returns from trading the Dow Jones Industrial Average. Journal of Empirical Finance, 9(4), 431–454. https://doi.org/10.1016/S0927-5398(02)00004-X
dc.relation.referencesDbouk, W., Jamali, I., & Soufani, K. (2014). The Effectiveness of Technical Trading for Arab Stocks. Emerging Markets Finance and Trade, 50(4), 5–25. https://doi.org/10.2753/REE1540-496X500401
dc.relation.referencesde Frutos, J., & Gatón, V. (2017). A spectral method for an Optimal Investment problem with transaction costs under Potential Utility. Journal of Computational and Applied Mathematics, 319, 262–276. https://doi.org/10.1016/J.CAM.2017.01.015
dc.relation.referencesDe Oliveira, F. A., Nobre, C. N., & Zárate, L. E. (2013). Applying Artificial Neural Networks to prediction of stock price and improvement of the directional prediction index - Case study of PETR4, Petrobras, Brazil. Expert Systems with Applications, 40(18), 7596–7606. https://doi.org/10.1016/j.eswa.2013.06.071
dc.relation.referencesde Souza, M. J. S., Ramos, D. G. F., Pena, M. G., Sobreiro, V. A., & Kimura, H. (2018). Examination of the profitability of technical analysis based on moving average strategies in BRICS. Financial Innovation, 4(1), 3. https://doi.org/10.1186/s40854-018-0087-z
dc.relation.referencesDobbs, I., & Atmeh, M. (2006). Technical analysis and the stochastic properties of the Jordanian stock market index return. Studies in Economics and Finance (Vol. 23). https://doi.org/10.1108/10867370610683914
dc.relation.referencesDourra, H., & Siy, P. (2002). Investment using technical analysis and fuzzy logic. Fuzzy Sets and Systems, 127(2), 221–240. https://doi.org/10.1016/S0165-0114(01)00169-
dc.relation.referencesEfron, B., & Tibshirani, R. (1986). Bootstrap Methods for Standard Errors, Confidence Intervals, and Other Measures of Statistical Accuracy. Statistical Science, 1(1), 54–75. Retrieved from http://www.jstor.org/stable/2245500
dc.relation.referencesEfron, B., Tibshirani, R., & Hartigan, J. A. (1986). Bootstrap Methods for Standard Errors, Confidence Intervals, and Other Measures of Statistical Accuracy. Statistical Science, 1(1), 75–77. Retrieved from http://www.jstor.org/stable/2245501
dc.relation.referencesEiamkanitchat, N., Moontuy, T., & Ramingwong, S. (2016). Fundamental analysis and technical analysis integrated system for stock filtration. Cluster Computing (Vol. 20). https://doi.org/10.1007/s10586-016-0694-2
dc.relation.referencesEiamkanitchat, N., Moontuy, T., & Ramingwong, S. (2017). Fundamental analysis and technical analysis integrated system for stock filtration. Cluster Computing, 20(1), 883–894. https://doi.org/10.1007/s10586-016-0694-2
dc.relation.referencesEllis, C. A., & Parbery, S. A. (2005). Is smarter better? A comparison of adaptive, and simple moving average trading strategies. Research in International Business and Finance, 19(3), 399–411. https://doi.org/10.1016/J.RIBAF.2004.12.009
dc.relation.referencesElroy, D., & Massoud, M. (2002). A brief history of market efficiency. European Financial Management, 4(1), 91–103. https://doi.org/10.1111/1468-036X.00056
dc.relation.referencesEric, D., Andjelic, G., & Redzepagic, S. (2009). Application of MACD and RVI indicators as functions of investment strategy optimization on the financial market. Zbornik Radova Ekonomskog Fakultet Au Rijeci, 27.
dc.relation.referencesEspinosa, C., & Gorigoitía, J. (2014). ¿Es útil el análisis técnico en periodos de crisis financiera? Evidencia para el mercado bursátil latinoamericano . El Trimestre Económico . scielomx
dc.relation.referencesFaff, R., & Anderson, J. (2005). Profitability of Trading Rules in Futures Markets. Accounting Research Journal, 18(2), 83–92. https://doi.org/10.1108/10309610580000677
dc.relation.referencesFama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383–417. https://doi.org/10.2307/2325486
dc.relation.referencesFang, J., Qin, Y., & Jacobsen, B. (2014). Technical market indicators: An overview. Journal of Behavioral and Experimental Finance, 4, 25–56. https://doi.org/10.1016/j.jbef.2014.09.001
dc.relation.referencesFang, Y., & Xu, D. (2003). The predictability of asset returns: An approach combining technical analysis and time series forecasts. International Journal of Forecasting, 19(3), 369–385. https://doi.org/10.1016/S0169-2070(02)00013-4
dc.relation.referencesFarias Nazário, R., Lima e Silva, J., Amorim Sobreiro, V., & Kimura, H. (2017). A literature review of technical analysis on stock markets. The Quarterly Review of Economics and Finance, 66, Q. Rev. Econ. Financ.
dc.relation.referencesFong, W. M., & Yong, L. H. M. (2005). Chasing trends: recursive moving average trading rules and internet stocks. Journal of Empirical Finance, 12(1), 43–76. https://doi.org/10.1016/J.JEMPFIN.2003.07.002
dc.relation.referencesFriesen, G. C., Weller, P. A., & Dunham, L. M. (2009). Price trends and patterns in technical analysis: A theoretical and empirical examination. Journal of Banking and Finance, 33(6), 1089–1100. https://doi.org/10.1016/j.jbankfin.2008.12.010
dc.relation.referencesFu, T., Chung, C., & Chung, F. (2013). Adopting genetic algorithms for technical analysis and portfolio management. Computers & Mathematics with Applications, 66(10), 1743–1757. https://doi.org/10.1016/J.CAMWA.2013.08.012
dc.relation.referencesGebka, B., Hudson, R. S., & Atanasova, C. V. (2015). The benefits of combining seasonal anomalies and technical trading rules. Finance Research Letters, 14, 36–44. https://doi.org/10.1016/J.FRL.2015.06.001
dc.relation.referencesGençay, R. (1998). Optimization of technical trading strategies and the profitability in security markets. Economics Letters, 59(2), 249–254. https://doi.org/10.1016/S0165-1765(98)00051-2
dc.relation.referencesGerritsen, D. F. (2016). Are chartists artists? The determinants and profitability of recommendations based on technical analysis. International Review of Financial Analysis, 47, 179–196. https://doi.org/10.1016/J.IRFA.2016.06.008
dc.relation.referencesGilmore, C., & Mcmanus, G. (2001). Random-Walk and Efficiency Tests of Central European Equity Markets. Managerial Finance, 29. https://doi.org/10.2139/ssrn.269510
dc.relation.referencesGoo, Y., Chen, D., & Chang, Y. (2007). The application of Japanese candlestick trading strategies in Taiwan. Investment Management and Financial Innovations, 4, 49–79.
dc.relation.referencesGrinblatt, M., & Keloharju, M. (2000). The investment behavior and performance of various investor types: a study of Finland’s unique data set. Journal of Financial Economics, 55(1), 43–67. https://doi.org/10.1016/S0304-405X(99)00044-6
dc.relation.referencesHájek, J. (2007). Weak-form efficiency test in the Central European capital markets. Politická Ekonomie, 2007.
dc.relation.referencesHambuckers, J., & Heuchenne, C. (2016). Estimating the Out-of-Sample Predictive Ability of Trading Rules: A Robust Bootstrap Approach. Journal of Forecasting, 35(4), 347–372. https://doi.org/10.1002/for.2380
dc.relation.referencesHansen, P. R., & Lunde, A. (2005). A forecast comparison of volatility models: Does anything beat a GARCH(1,1)? Journal of Applied Econometrics, 20(7), 873–889. https://doi.org/10.1002/jae.800
dc.relation.referencesHartigan, J. (1986). [Bootstrap Methods for Standard Errors, Confidence Intervals, and Other Measures of Statistical Accuracy]: Comment. Statistical Science, 1(1), 75–77. Retrieved from http://www.jstor.org/stable/2245501
dc.relation.referencesHarvey, C. R., & Liu, Y. (2014). Evaluating Trading Strategies. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2474755
dc.relation.referencesHatgioannides, 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. https://doi.org/10.1016/J.JIMONFIN.2007.05.005
dc.relation.referencesHudson, R., Dempsey, M., & Keasey, K. (1996). A note on the weak form efficiency of capital markets: The application of simple technical trading rules to UK stock prices - 1935 to 1994. Journal of Banking & Finance, 20(6), 1121–1132. https://doi.org/10.1016/0378-4266(95)00043-7
dc.relation.referencesJaaman, S. H., Shamsuddin, S. M., Yusob, B., & Ismail, I. (2009). A predictive model construction applying rough set methodology for Malaysian stock market returns, 30.
dc.relation.referencesJensen, M., & Benington, G. (2018). RANDOM WALKS AND TECHNICAL THEORIES: SOME ADDITIONAL EVIDENCE. The Journal of Finance, 25(2), 469–482. https://doi.org/10.1111/j.1540-6261.1970.tb00671.x
dc.relation.referencesJiao, Y., Ma, C., Scotti, S., & Sgarra, C. (2018). A Branching Process Approach to Power Markets. Energy Economics. https://doi.org/10.1016/j.eneco.2018.03.002
dc.relation.referencesJunjun, M., Xiong, X., Feng, H., & Zhang, W. (2017). Volatility measurement with directional change in Chinese stock market: Statistical property and investment strategy. Physica A, 471, 169–180.
dc.relation.referencesKakani, R., & Sundhar, S. (2006). Profiting from Technical Analysis in Indian Equity Markets: Using Moving Averages. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.889515
dc.relation.referencesKnez, P. J., & Ready, M. J. (1996). Estimating the Profits from Trading Strategies. The Review of Financial Studies, 9(4), 1121–1163. Retrieved from http://www.jstor.org/stable/2962225
dc.relation.referencesKo, K. C., Lin, S. J., Su, H. J., & Chang, H. H. (2014). Value investing and technical analysis in Taiwan stock market. Pacific Basin Finance Journal, 26. https://doi.org/10.1016/j.pacfin.2013.10.004
dc.relation.referencesKorajczyk, R. A., & Sadka, R. (2004). Are Momentum Profits Robust to Trading Costs? The Journal of Finance, 59(3), 1039–1082. https://doi.org/10.1111/j.1540-6261.2004.00656.x
dc.relation.referencesKrausz, J., Lee, S.-Y., & Nam, K. (2009). Profitability of Nonlinear Dynamics Under Technical Trading Rules: Evidence from Pacific Basin Stock Markets. Emerging Markets Finance and Trade, 45(4), 13–35. https://doi.org/10.2753/REE1540-496X450402
dc.relation.referencesKristjanpoller, W., & Minutolo, M. C. (2018). A hybrid volatility forecasting framework integrating GARCH, artificial neural network, technical analysis and principal components analysis. Expert Systems with Applications, 109, 1–11. https://doi.org/10.1016/j.eswa.2018.05.011
dc.relation.referencesLahmiri, S. (2014). Entropy-Based Technical Analysis Indicators Selection for International Stock Markets Fluctuations Prediction Using Support Vector Machines. Fluctuation and Noise Letters, 13(02), 1450013. https://doi.org/10.1142/S0219477514500138
dc.relation.referencesLai, H., Chen, C., & Huang, C. (2010). Technical Analysis, Investment Psychology, and Liquidity Provision: Evidence from the Taiwan Stock Market. Emerging Markets Finance and Trade, 46(5), 18–38. https://doi.org/10.2753/REE1540-496X460502
dc.relation.referencesLakonishok, J., & Smidt, S. (1988). Are Seasonal Anomalies Real? A Ninety-Year Perspective. The Review of Financial Studies, 1(4), 403–425. Retrieved from http://www.jstor.org/stable/2962097
dc.relation.referencesLam, M. (2004). Neural network techniques for financial performance prediction: Integrating fundamental and technical analysis. Decision Support Systems, 37(4), 567–581. https://doi.org/10.1016/S0167-9236(03)00088-5
dc.relation.referencesLento, Camillo. (2008). Tests of Technical Trading Rules in the Asian-Pacific Equity Markets: A Bootstrap Approach. Academy of Accounting & Financial Studies Journal (Vol. 11).
dc.relation.referencesLento, Camillo. (2013). A Synthesis of Technical Analysis and Fractal Geometry: Evidence from the Components of the Dow Jones Industrial Average. Journal of Technical Analysis, (67), 25–45. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=89540286&lang=es&site=ehost-live
dc.relation.referencesLento, Camillo, & Gradojevic, N. (2007). The Profitability Of Technical Trading Rules: A Combined Signal Approach. Journal of Applied Business Research (Vol. 23). https://doi.org/10.19030/jabr.v23i1.1405
dc.relation.referencesLento, Camilo. (2009). Combined signal approach: Evidence from the Asian–Pacific equity markets. Applied Economics Letters, 16(7), 749–753. https://doi.org/10.1080/17446540802260886
dc.relation.referencesLevich, R. M., & Thomas, L. R. (1993). The significance of technical trading-rule profits in the foreign exchange market: a bootstrap approach. Journal of International Money and Finance, 12(5), 451–474. https://doi.org/10.1016/0261-5606(93)90034-9
dc.relation.referencesLi, D., Nishimura, Y., & Men, M. (2016). The long memory and the transaction cost in financial markets. Physica A: Statistical Mechanics and Its Applications, 442, 312–320. https://doi.org/10.1016/J.PHYSA.2015.09.015
dc.relation.referencesLi, X., Chen, K., Li, X., & Chen, K. (2006). Is technical analysis useful for stock trades in China? Evidence from the SZSE Component A-Share Index. Pacific Economic Review (Vol. 11). https://doi.org/10.1111/j.1468-0106.2006.00329.x
dc.relation.referencesLin, Q. (2018). Technical analysis and stock return predictability: An aligned approach. Journal of Financial Markets, 38, 103–123. https://doi.org/10.1016/J.FINMAR.2017.09.003
dc.relation.referencesLin, X., Yang, Z., & Song, Y. (2011). Intelligent stock trading system based on improved technical analysis and Echo State Network. Expert Systems with Applications, 38(9), 11347–11354. https://doi.org/10.1016/j.eswa.2011.03.001
dc.relation.referencesLiu, W., & Zheng, W. A. (2011). Stochastic volatility model and technical analysis of stock price. Acta Mathematica Sinica, English Series, 27(7), 1283. https://doi.org/10.1007/s10114-011-9468-1
dc.relation.referencesLo, A. W., Mamaysky, H., & Wang, J. (2002). Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation. The Journal of Finance, 55(4), 1705–1765. https://doi.org/10.1111/0022-1082.00265
dc.relation.referencesLobão, J., & Couto, M. (2019). Are there Psychological Barriers in Asian Stock Markets? Asian Academy of Management Journal of Accounting and Finance, 15, 83–106.
dc.relation.referencesLu, T. H., Chen, Y. C., & Hsu, Y. C. (2015). Trend definition or holding strategy: What determines the profitability of candlestick charting? Journal of Banking and Finance, 61, 172–183. https://doi.org/10.1016/j.jbankfin.2015.09.009
dc.relation.referencesLu, T., & Shiu, Y. (2012). Tests for Two-Day Candlestick Patterns in the Emerging Equity Market of Taiwan. Emerging Markets Finance and Trade, 48(sup1), 41–57. https://doi.org/10.2753/REE1540-496X4801S104
dc.relation.referencesMacedo, L. L., Godinho, P., & Alves, M. J. (2017). Mean-semivariance portfolio optimization with multiobjective evolutionary algorithms and technical analysis rules. Expert Systems with Applications, 79, 33–43. https://doi.org/10.1016/J.ESWA.2017.02.033
dc.relation.referencesMahmoud, M., & Mandouh, R. (2012). Maximum likelihood estimation of two unknown parameters of Beta-Weibull distribution under type II censored samples. Applied Mathematical Sciences (Ruse), 6.
dc.relation.referencesMalkiel, B. (2007). A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing. (Norton, Ed.). New York, NY.
dc.relation.referencesManahov, V., Hudson, R., & Gebka, B. (2014). Does high frequency trading affect technical analysis and market efficiency? And if so, how? Journal of International Financial Markets, Institutions and Money, 28, 131–157. https://doi.org/10.1016/J.INTFIN.2013.11.002
dc.relation.referencesMarshall, B. R., & Cahan, R. H. (2005). Is technical analysis profitable on a stock market which has characteristics that suggest it may be inefficient? Research in International Business and Finance, 19(3), 384–398. https://doi.org/10.1016/j.ribaf.2005.05.001
dc.relation.referencesMarshall, B. R., Cahan, R. H., & Cahan, J. M. (2008). Does intraday technical analysis in the U.S. equity market have value? Journal of Empirical Finance, 15(2), 199–210. https://doi.org/10.1016/J.JEMPFIN.2006.05.003
dc.relation.referencesMarshall, B. R., Young, M. R., & Rose, L. C. (2006). Candlestick technical trading strategies: Can they create value for investors? Journal of Banking and Finance, 30(8), 2303–2323. https://doi.org/10.1016/j.jbankfin.2005.08.001
dc.relation.referencesMasteika, S., & Simutis, R. (2006). Stock Trading System Based on Formalized Technical Analysis and Ranking Technique BT - Computational Science – ICCS 2006. In V. N. Alexandrov, G. D. van Albada, P. M. A. Sloot, & J. Dongarra (Eds.) (pp. 332–339). Berlin, Heidelberg: Springer Berlin Heidelberg.
dc.relation.referencesMeghwani, S. S., & Thakur, M. (2018). Multi-objective heuristic algorithms for practical portfolio optimization and rebalancing with transaction cost. Applied Soft Computing, 67, 865–894. https://doi.org/10.1016/J.ASOC.2017.09.025
dc.relation.referencesMéndez, C., & Gorigoitia, J. (2014). Es útil el análisis técnico en periodos de crisis financiera?: Evidencia para el mercado bursátil latinoamericano. El Trimestre Económico, LXXXI, 595–618.
dc.relation.referencesMeric, I., Ratner, M., Nygren, L. M., & Meric, G. (2008). Co-Movements of Latin American Equity Markets Before and After September 11, 2001. Latin American Business Review, 8(3), 54–74. https://doi.org/10.1080/10978520802035422
dc.relation.referencesMetghalchi, M. (2013). Market Efficiency and Profitability of Technical Trading Rules: Evidence from Vietnam. The Journal of Prediction Markets, 7(2), 11–27. https://doi.org/10.5750/JPM.V7I2.632
dc.relation.referencesMetghalchi, M. (2015). LOST DECADE, MARKET EFFICIENCY AND TECHNICAL TRADING RULES: EVIDENCE FROM GREECE. Journal of Prediction Markets, 9(1), 15–32. Retrieved from http://ezproxy.unal.edu.co/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=117540850&lang=es&site=eds-live
dc.relation.referencesMetghalchi, M., Chang, Y.-H., & Marcucci, J. (2008a). Is the Swedish stock market efficient? Evidence from some simple trading rules. International Review of Financial Analysis, 17(3), 475–490. https://doi.org/10.1016/J.IRFA.2007.05.001
dc.relation.referencesMetghalchi, M., Chang, Y. H., & Marcucci, J. (2008b). Is the Swedish stock market efficient? Evidence from some simple trading rules. International Review of Financial Analysis, 17(3), 475–490. https://doi.org/10.1016/j.irfa.2007.05.001
dc.relation.referencesMetghalchi, M., Hayes, L. A., & Niroomand, F. (2019). A technical approach to equity investing in emerging markets. Review of Financial Economics, 37(3), 389–403. https://doi.org/10.1002/rfe.1041
dc.relation.referencesMILA. (2018). MILA. Retrieved April 3, 2018, from https://www.mercadomila.com/home/quehacemos
dc.relation.referencesMilionis, A. E., & Papanagiotou, E. (2011). A test of significance of the predictive power of the moving average trading rule of technical analysis based on sensitivity analysis: application to the NYSE, the Athens Stock Exchange and the Vienna Stock Exchange. Implications for weak-form market effi. Applied Financial Economics, 21(6), 421–436. https://doi.org/10.1080/09603107.2010.532105
dc.relation.referencesMiner, R. C. (2009). High Probability Trading Strategies. Entry to Exit Tactics for the Forex, Futures, and Stock Markets. Wiley. Retrieved from https://www.wiley.com/WileyCDA/WileyTitle/productCd-0470181664,miniSiteCd-WILEYTRADING.html
dc.relation.referencesMing-Ming, L., & Siok-Hwa, L. (2006). The profitability of the simple moving averages and trading range breakout in the Asian stock markets. Journal of Asian Economics, 17(1), 144–170. https://doi.org/10.1016/J.ASIECO.2005.12.001
dc.relation.referencesMitra, S. K. (2011). How rewarding is technical analysis in the Indian stock market? Quantitative Finance, 11(2), 287–297. https://doi.org/10.1080/14697680903493581
dc.relation.referencesMohd Nor, S., & Wickremasinghe, G. (2014). The profitability of MACD and RSI trading rules in the Australian stock market. Investment Management and Financial Innovations, 11, 194–199.
dc.relation.referencesMoosa, I., & Li, L. (2011). Technical and Fundamental Trading in the Chinese Stock Market: Evidence Based on Time-Series and Panel Data. Emerging Markets Finance and Trade, 47(sup1), 23–31. https://doi.org/10.2753/REE1540-496X4701S103
dc.relation.referencesMurphy, J. (2007). Análisis técnico de los mercados financieros. (G. 2000, Ed.).
dc.relation.referencesNedeltcheva, G. (2015). Forecasting Stock Market Trends. Economic Quality Control, 0. https://doi.org/10.1515/eqc-2015-6003
dc.relation.referencesNi, Y., Liao, Y.-C., & Huang, P. (2015). Momentum in the Chinese Stock Market: Evidence from Stochastic Oscillator Indicators. Emerging Markets Finance and Trade, 51(sup1), S99–S110. https://doi.org/10.1080/1540496X.2014.998916
dc.relation.referencesNti, I., Adekoya, A., & Weyori, B. (2020). A systematic review of fundamental and technical analysis of stock market predictions. Artificial Intelligence Review, 53(4), 3007–3057. https://doi.org/10.1007/s10462-019-09754-z
dc.relation.referencesOkunev, J., & White, D. (2003). Do Momentum-Based Strategies Still Work in Foreign Currency Markets? The Journal of Financial and Quantitative Analysis, 38(2), 425–447. https://doi.org/10.2307/4126758
dc.relation.referencesOlasolo, A., Pérez, M. A., & Ruiz, V. (2016). Active investment strategies in the Spanish futures market: a solution to avoid data snooping bias. Applied Economics Letters, 23(9). https://doi.org/10.1080/13504851.2015.1093075
dc.relation.referencesOlson, D. (2004). Have trading rule profits in the currency markets declined over time? Journal of Banking & Finance, 28(1), 85–105. https://doi.org/10.1016/S0378-4266(02)00399-0
dc.relation.referencesOmar Farooq, M., & Hasib Reza, M. (2014). Dow Jones Islamic Market US Index: Applying technical analysis from a comparative perspective. International Journal of Islamic and Middle Eastern Finance and Management, 7(4), 395–420. https://doi.org/10.1108/IMEFM-12-2013-0134
dc.relation.referencesOzun, A., Hanias, M., & Curtis, P. (2010). A chaos analysis for Greek and Turkish equity markets. Euromed Journal of Business, 5, 101–118. https://doi.org/10.1108/14502191011043189
dc.relation.referencesPapadamou, S., & Tsopoglou, S. (2001). Investigating the profitability of technical analysis systems on foreign exchange markets. Managerial Finance, 27(8), 63–78. https://doi.org/10.1108/03074350110767349
dc.relation.referencesParisi, A. (2019). Análisis Tecnico: Un estudio de la eficiencia de diferentes técnicas aplicadas sobre acciones pertenecientes a los índices bursatiles...
dc.relation.referencesPark, C., & Scott, I. (2009). A reality check on technical trading rule profits in the U.S. futures markets. Journal of Futures Markets, 30(7), 633–659. https://doi.org/doi:10.1002/fut.20435
dc.relation.referencesPavlov, V., & Hurn, S. (2012). Testing the profitability of moving-average rules as a portfolio selection strategy. Pacific-Basin Finance Journal, 20(5), 825–842. https://doi.org/10.1016/J.PACFIN.2012.04.003
dc.relation.referencesPesaran, M. H., & Timmermann, A. (1995). Predictability of Stock Returns: Robustness and Economic Significance. The Journal of Finance, 50(4), 1201–1228. https://doi.org/10.1111/j.1540-6261.1995.tb04055.x
dc.relation.referencesPike, R., Meerjanssen, J., & Chadwick, L. (1993). The Appraisal of Ordinary Shares by Investment Analysts in the UK and Germany. Accounting and Business Research, 23(92), 489–499. https://doi.org/10.1080/00014788.1993.9729893
dc.relation.referencesProrokowski, L. (2011). Trading strategies of individual investors in times of financial crisis: An example from the Central European emerging stock market of Poland. Qualitative Research in Financial Markets, 3, 34–50. https://doi.org/10.1108/17554171111124603
dc.relation.referencesQin, Y., Pan, G., & Bai, M. (2020). Improving market timing of time series momentum in the Chinese stock market. Applied Economics, 1–15. https://doi.org/10.1080/00036846.2020.1740160
dc.relation.referencesRahman, M., M Simon, H., & Hossain, M. (2016). An Empirical Analysis of Weak Form Market Efficiency: Evidence from Chittagong Stock Exchange (CSE) of Bangladesh.
dc.relation.referencesRatner, M., & Leal, R. (1999). Tests of technical trading strategies in the emerging equity markets of Latin America and Asia. Journal of Banking & Finance, 23(12), 1887–1905. https://doi.org/10.1016/S0378-4266(99)00042-4
dc.relation.referencesReady, M. J. (2002). Profits from Technical Trading Rules. Financial Management, 31(3), 43–61. https://doi.org/10.2307/3666314
dc.relation.referencesReschenhofer, E., Mangat, M. K., Zwatz, C., & Guzmics, S. (2020). Evaluation of current research on stock return predictability. Journal of Forecasting, 39(2), 334–351. https://doi.org/10.1002/for.2629
dc.relation.referencesRestrepo Mejía, F. (2009). Evaluación de estrategias de gestión activa de portafolios en el mercado accionario colombiano. Universidad EIA. Retrieved from http://repository.eia.edu.co/handle/11190/1646
dc.relation.referencesRosillo, R., de la Fuente, D., & Brugos, J. A. L. (2013). Technical analysis and the Spanish stock exchange: testing the RSI, MACD, momentum and stochastic rules using Spanish market companies. Applied Economics, 45(12), 1541–1550. https://doi.org/10.1080/00036846.2011.631894
dc.relation.referencesSaacke, P. (2002). Technical analysis and the effectiveness of central bank intervention. Journal of International Money and Finance, 21(4), 459–479. https://doi.org/10.1016/S0261-5606(02)00009-8
dc.relation.referencesSabbaghi, O., & Sabbaghi, N. (2018). Market efficiency and the global financial crisis: evidence from developed markets. Studies in Economics and Finance, 35. https://doi.org/10.1108/SEF-01-2014-0022
dc.relation.referencesSamuelson, P. A. (2013). Proof that Properly Anticipated Prices Fluctuate Randomly. In The World Scientific Handbook of Futures Markets (Vol. Volume 5, pp. 25–38). WORLD SCIENTIFIC. https://doi.org/doi:10.1142/9789814566926_0002
dc.relation.referencesSavin, G., Weller, P., & Zvingelis, J. (2007). The Predictive Power of “Head-and-Shoulders ” Price Patterns in the U.S. Stock Market Gene Savin. Journal of Financial Econometrics, 5. https://doi.org/10.1093/jjfinec/nbl012
dc.relation.referencesShynkevich, A. (2012). Performance of technical analysis in growth and small cap segments of the US equity market. Journal of Banking and Finance, 36(1), 193–208. https://doi.org/10.1016/j.jbankfin.2011.07.001
dc.relation.referencesShynkevich, A. (2016). Predictability of equity returns during a financial crisis. Applied Economics Letters, 23(17), 1201–1205. https://doi.org/10.1080/13504851.2016.1145339
dc.relation.referencesShynkevich, A. (2017). Return predictability in emerging equity market sectors. Applied Economics, 49(5), 433–445. https://doi.org/10.1080/00036846.2016.1200182
dc.relation.referencesSmith, D., Wang, N., Wang, Y., & J. Zychowicz, E. (2016). Sentiment and the Effectiveness of Technical Analysis: Evidence from the Hedge Fund Industry. Journal of Financial and Quantitative Analysis. https://doi.org/10.2139/ssrn.2457289
dc.relation.referencesSobreiro, V., Costa, T. R., Nazário, R., Silva, J., Moreira, E., Filho, M., … Arismendi Zambrano, J. (2016). The profitability of moving average trading rules in BRICS and emerging stock markets. The North American Journal of Economics and Finance, 38, 86–101. https://doi.org/10.1016/j.najef.2016.08.003
dc.relation.referencesSturm, R. (2013). Market Efficiency and Technical Analysis: Can They Coexist? Research in Applied Economics, 5, 3. https://doi.org/10.5296/rae.v5i3.4049
dc.relation.referencesTalwar, S., Pranav, S., & Utkarsh, S. (2019). Picking Buy-Sell Signals: A Practitioner’s Perspective on Key Technical Indicators for Selected Indian Firms. Studies in Business and Economics, 14, 205–219. https://doi.org/10.2478/sbe-2019-0054
dc.relation.referencesTan, S. H., Lai, M. M., Tey, E. X., & Chong, L. L. (2020). Testing the performance of technical analysis and sentiment-TAR trading rules in the Malaysian stock market. North American Journal of Economics and Finance, 51, 100895. https://doi.org/10.1016/j.najef.2018.12.007
dc.relation.referencesTaylor, S. J. (2000). Stock index and price dynamics in the UK and the US: new evidence from a trading rule and statistical analysis. The European Journal of Finance, 6(1), 39–69. https://doi.org/10.1080/135184700336955
dc.relation.referencesTeixeira, L. A., & De Oliveira, A. L. I. (2010). A method for automatic stock trading combining technical analysis and nearest neighbor classification. Expert Systems with Applications, 37(10), 6885–6890. https://doi.org/10.1016/j.eswa.2010.03.033
dc.relation.referencesThaler, R. H. (2018). Economia del comportamiento: pasado, presente y futuro. Revista de Economia Institucional, 20, 9–43. Retrieved from http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0124-59962018000100009&nrm=iso
dc.relation.referencesTharavanij, P., Siraprapasiri, V., & Rajchamaha, K. (2015). Performance of technical trading rules: evidence from Southeast Asian stock markets. SpringerPlus (Vol. 4). https://doi.org/10.1186/s40064-015-1334-7
dc.relation.referencesTian, G. G., Wan, G. H., & Guo, M. (2002). Market Efficiency and the Returns to Simple Technical Trading Rules: New Evidence from U.S. Equity Market and Chinese Equity Markets. Asia-Pacific Financial Markets, 9(3), 241–258. https://doi.org/10.1023/A:1024181515265
dc.relation.referencesTijjani, B., Fifield, S., & Power, D. (2009). The appraisal of equity investments by Nigerian investors. Qualitative Research in Financial Markets (Vol. 1). https://doi.org/10.1108/17554170910939937
dc.relation.referencesTsaih, R., Hsu, Y., & Lai, C. C. (1998). Forecasting S&P 500 stock index futures with a hybrid AI system. Decision Support Systems, 23(2), 161–174. https://doi.org/10.1016/s0167-9236(98)00028-1
dc.relation.referencesUmaña H., B., & Romo M., R. (2007). Herramientas de Análisis Técnico para Carteras de Inversiones Bursátiles: Aplicación al Mercado Bursátil Chileno. Panorama Socioeconómico, 25(34), 48–59. Retrieved from https://www.redalyc.org/articulo.oa?id=39903405
dc.relation.referencesUribe Gil, J. M., & Mosquera López, S. (2014). Efectos del MILA en la eficiencia de portafolio de los mercados de acciones colombiano, peruano y chileno. Cuadernos de Administración, 30.
dc.relation.referencesValderrama, A., & Gonzalez, C. (2016). Mercado de Deuda Privada en Colombia. BVC. Retrieved from http://www.bvc.com.co/pps/tibco/portalbvc/Home/IE/Estudio_Diagnostico?com.tibco.ps.pagesvc.action=updateRenderState&rp.currentDocumentID=-698351ae_14f2bdddcc4_3a6f0a0a600b&rp.attachmentPropertyName=Attachment&com.tibco.ps.pagesvc.targetPage=1f9a1c33_13204
dc.relation.referencesVasileiou, E. (2014). Is Technical Analysis Profitable Even for an Amateur Investor? Evidence from the Greek Stock Market (2002-12). SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2468868
dc.relation.referencesVelásquez, J., & Zuluaga, M. (2007). Selección de indicadores técnicos para la negociación en el mercado cambiario colombiano II: Combinaciones y filtros (vhf y adx). Dyna, 74, 21–37.
dc.relation.referencesWang, F., Yu, P. L. H., & Cheung, D. W. (2014). Combining technical trading rules using particle swarm optimization. Expert Systems with Applications, 41(6), 3016–3026. https://doi.org/10.1016/J.ESWA.2013.10.032
dc.relation.referencesWang, H., & Pandey, R. B. (2004). A momentum trading approach to technical analysis of Dow Jones industrials. Physica A-statistical Mechanics and Its Applications - PHYSICA A (Vol. 331). North-Holland. https://doi.org/10.1016/j.physa.2003.08.037
dc.relation.referencesWang, J., & Chan, S. (2007). Stock market trading rule discovery using pattern recognition and technical analysis. Expert Systems with Applications, 33(2), 304–315. https://doi.org/10.1016/j.eswa.2006.05.002
dc.relation.referencesWang, J., Liu, H., Du, J., & Hsu, Y. (2019). Economic benefits of technical analysis in portfolio management: Evidence from global stock markets. International Journal of Finance & Economics, 24(2), 890–902. https://doi.org/10.1002/ijfe.1697
dc.relation.referencesWang, Q., Xu, W., & Zheng, H. (2018). Combining the wisdom of crowds and technical analysis for financial market prediction using deep random subspace ensembles. Neurocomputing, 299, 51–61. https://doi.org/10.1016/J.NEUCOM.2018.02.095
dc.relation.referencesWang, S., Jiang, Z. Q., Li, S. P., & Zhou, W. X. (2015). Testing the performance of technical trading rules in the Chinese markets based on superior predictive test. Physica A: Statistical Mechanics and Its Applications, 439. https://doi.org/10.1016/j.physa.2015.07.029
dc.relation.referencesWeber, E. U., Blais, A.-R., & Betz, N. E. (2002). A domain-specific risk-attitude scale: measuring risk perceptions and risk behaviors. Journal of Behavioral Decision Making, 15(4), 263–290. https://doi.org/10.1002/bdm.414
dc.relation.referencesWhite, H. (2003). A Reality Check for Data Snooping. Econometrica, 68(5), 1097–1126. https://doi.org/10.1111/1468-0262.00152
dc.relation.referencesWing-Shing Lam, V., Chong, T. T.-L., & Wong, W.-K. (2007). Profitability of intraday and interday momentum strategies. Applied Economics Letters, 14(15), 1103–1108. https://doi.org/10.1080/13504850600606067
dc.relation.referencesWitkowska, D., & Marcinkiewicz, E. (2005). Construction and Evaluation of Trading Systems: Warsaw Index Futures. International Advances in Economic Research, 11(1), 83–92. https://doi.org/10.1007/s11294-004-7496-7
dc.relation.referencesWong, W.-K., & Kung, J. (2009). Profitability of Technical Analysis in the Singapore Stock Market: before and after the Asian Financial Crisis. Journal of Economic Integration, 24, 135–150. https://doi.org/10.11130/jei.2009.24.1.135
dc.relation.referencesWong, W.-K., Manzur, M., & Chew, B.-K. (2003). How Rewarding Is Technical Analysis? Evidence from Singapore Stock Market. Applied Financial Economics, 13, 543–551. https://doi.org/10.1080/0960310022000020906
dc.relation.referencesWoodside-Oriakhi, M., Lucas, C., & Beasley, J. E. (2013). Portfolio rebalancing with an investment horizon and transaction costs. Omega, 41(2), 406–420. https://doi.org/10.1016/J.OMEGA.2012.03.003
dc.relation.referencesXie, H., Bian, J., Wang, M., & Qiao, H. (2014). Is technical analysis informative in UK stock market? Evidence from decomposition-based vector autoregressive (DVAR) model. Journal of Systems Science and Complexity, 27(1), 144–156. https://doi.org/10.1007/s11424-014-3280-9
dc.relation.referencesYamamoto, R. (2012). Intraday technical analysis of individual stocks on the Tokyo Stock Exchange. Journal of Banking & Finance, 36(11), 3033–3047. https://doi.org/10.1016/J.JBANKFIN.2012.07.006
dc.relation.referencesYan, I., Chong, T., & Lam, T.-H. (2011). Is the Chinese Stock Market Really Efficient.
dc.relation.referencesYen, S., & Hsu, Y. (2010). Profitability of technical analysis in financial and commodity futures markets - A reality check. Decision Support Systems, 50(1), 128–139. https://doi.org/10.1016/j.dss.2010.07.008
dc.relation.referencesYoung, M., Marshall, B., & Cahan, R. (2008). Are candlestick technical trading strategies profitable in the Japanese equity market? Review of Quantitative Finance and Accounting, 31, 191–207. https://doi.org/10.1007/s11156-007-0068-1
dc.relation.referencesYoung, M., Marshall, B., & Qian, S. (2009). Is technical analysis profitable on US stocks with certain size, liquidity or industry characteristics? Applied Financial Economics, 19, 1213–1221. https://doi.org/10.2139/ssrn.929954
dc.relation.referencesZapranis, A., & Tsinaslanidis, P. E. (2012). Identifying and evaluating horizontal support and resistance levels: an empirical study on US stock markets. Applied Financial Economics, 22(19), 1571–1585. https://doi.org/10.1080/09603107.2012.663469
dc.relation.referencesZarrabi, N., Snaith, S., & Coakley, J. (2017). FX technical trading rules can be profitable sometimes! International Review of Financial Analysis, 49, 113–127. https://doi.org/10.1016/J.IRFA.2016.12.010
dc.relation.referencesZhu, H., Jiang, Z., Li, S., & Zhou, W. (2015). Profitability of simple technical trading rules of Chinese stock exchange indexes. Physica A: Statistical Mechanics and Its Applications, 439, 75–84. https://doi.org/10.1016/J.PHYSA.2015.07.032
dc.relation.referencesZuluaga, M., & Velasquez, J. (2007). Selección de indicadores técnicos para la negociación en el mercado cambiario colombiano I: Comportamientos individuales. Dyna, 74(152), 9–20. Retrieved from http://www.redalyc.org/articulo.oa?id=49615203
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.subject.proposalAnálisis Técnico
dc.subject.proposalTechnical Analysis
dc.subject.proposalEfectividad
dc.subject.proposalEffectiveness
dc.subject.proposalStability
dc.subject.proposalEstabilidad
dc.subject.proposalCombinación de Indicadores
dc.subject.proposalCombined Indicators
dc.subject.proposalMercado accionario
dc.subject.proposalStock Market
dc.subject.proposalColombia
dc.subject.proposalColombia
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dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.contentText
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2


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Atribución-NoComercial-SinDerivadas 4.0 InternacionalEsta obra está bajo licencia internacional Creative Commons Reconocimiento-NoComercial 4.0.Este documento ha sido depositado por parte de el(los) autor(es) bajo la siguiente constancia de depósito