Correo Electrónico
DNINFOA - SIA
Bibliotecas
Convocatorias
Identidad U.N.
Publicado
Será a dinâmica Ichimoku eficiente? Uma evidência nos mercados de ações
IS THE ICHIMOKU METHOD EFFICIENT? EVIDENCE FROM STOCK MARKETS
¿SERÁ LA DINÁMICA ICHIMOKU EFICIENTE? UNA EVIDENCIA EN LOS MERCADOS BURSÁTILES
DOI:
https://doi.org/10.15446/innovar.v32n84.99677Palavras-chave:
análise técnica, chikou span, Ichimoku, índice de Sharpe, mercados de ações (pt)Technical analysis, chikou span, Ichimoku, Sharpe index, stock market (en)
análisis técnico, chikou span, Ichimoku, índice de Sharpe, mercado de acciones (es)
Downloads
este artigo visa contribuir para o aumento do conhecimento do método de negociação Ichimoku, através de evidências teórico-empíricas sobre a capacidade preditiva dessa dinâmica de investimento. Apesar de essa dinâmica de investimento ter aparecido no Japão na década de 1930, só nos últimos anos começou a ganhar relevância para os investidores e académicos fora do Japão, existindo ainda uma lacuna na existência de trabalhos de investigação académica. Na persecução desse objetivo, estudaram-se cinco índices de mercados de capitais de diferentes zonas geográficas, tendo sido analisadas 26.295 cotações diárias, testando-se diferentes estratégias de negociação baseadas nas linhas Ichimoku. As estratégias de negociação produziram um conjunto de 22.083 sinais de negociação, possibilitando avaliar a capacidade preditiva e performance do sistema de negociação Ichimoku. O trabalho permitiu concluir que a dinâmica de negociação Ichimoku fornece sinais de tendências de negociação, sendo que as estratégias implementadas permitem criar valor para os investidores. Conclui-se também que a dinâmica Ichimoku apoia as decisões de investimento e possibilita que os investidores reajam rapidamente no mercado bearish, sendo útil para sinalizar tendências e revertê-las. A estratégia baseada na linha chikou span mostrou ser a mais rentável e a que propicia melhor remuneração por acréscimo de risco.
This paper seeks to contribute to the understanding of the Ichimoku trading method by providing empirical and theoretical evidence on the predictive capacity of this investment dynamics. Although Ichimoku emerged in Japan in the 1930s, it was only until recent years that it began to draw the attention of investors and scholars outside Japan, which explains the existing gap in academic research production on this approach. In an attempt to bridge such a gap, this work studies five capital market indices from different geographical areas. A total of 26,295 daily stock quotes were examined, testing different trading strategies based on the
Ichimoku lines. Reviewed trading strategies produced a set of 22,083 trading signals, which made it possible to evaluate Ichimoku’s predictive
ability and performance. Our findings show that this method provides key signs on commercial trends and that its related strategies allow creating value for investors. It is also concluded that Ichimoku dynamics support investment decisions and enable investors to react quickly in the face of bearing markets, thus being useful to point out trends and reverse them if necessary. In addition, the strategy based on the so-called chikou span line turned out to be the most profitable and the one that provides the best return for greater risk.
El artículo tiene el propósito de aportar al aumento del conocimiento del método de negociación Ichimoku, por medio de evidencia teórico-empírica acerca de la capacidad predictiva de esta dinámica de inversión. Si bien esta dinámica de inversión haya surgido en Japón en la década de 1930, solo en los últimos años los inversionistas y académicos fuera de Japón le han dado relevancia. Para lograr tal objetivo, se estudiaron cinco índices de mercados capitales de diferentes áreas geográficas y se analizaron 26.295 cotizaciones diarias, probándose distintas estrategias de negociación basadas en las líneas Ichimoku. Las estrategias de negociación produjeron un conjunto de 22.083 señales de negociación, lo que posibilita medir la capacidad predictiva y el desempeño del sistema de negociación Ichimoku. El trabajo permitió concluir que la dinámica de negociación Ichimoku brinda señales de tendencias de negociación, siendo
que las estrategias implementadas permiten crear valor para los inversionistas. Se concluye también que la dinámica Ichimoku apoya las decisiones
de inversión y posibilita que los inversionistas actúen rápidamente en el mercado bajista (bearish market), siendo útil para indicar tendencias y revertirlas. La estrategia basada en la línea chikou span (lapso de retraso) mostró ser la más rentable y la que propicia mejor remuneración por aumento
de riesgo.
Referências
Ahmar, A. (2017). Sutte indicator: A technical indicator in stock market. International Journal of Economics and Financial Issues, 7(2), 1-4. https://www.econjournals.com/index.php/ijefi/article/view/3323
Alexander, S. (1964). Price movements in speculative markets: Trends or random walks. Industrial Management Review, 2, 25-46. http://history.technicalanalysis.org.uk/Alex64.pdf
Alhashel, B., Almudhaf, F., & Hansz, J. (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 DOI: https://doi.org/10.1016/j.pacfin.2017.12.005
Al-Jassar, S. (2019). Fundamental and technical trading in the emerging market of an oil-based economy. Review of Pacific Basin Financial Markets and Policies. 22(1). https://doi.org/10.1142/S0219091519500061 DOI: https://doi.org/10.1142/S0219091519500061
Almeida, L. (2020). Technical indicators for rational investing in the technology companies: The evidence of FAANG stocks. Jurnal Pengurusan, 59. http://doi.org/10.17576/pengurusan-2020-59-08
Aloud, M. (2018). Investment opportunities forecasting: A genetic programming-based dynamic portfolio trading system under a directional-change framework. Journal of Computational Finance, 22(1), 1-35. http://doi.org/10.21314/JCF.2018.346 DOI: https://doi.org/10.21314/JCF.2018.346
Bagheri, A., Peyhani, H. & Akbari, M. (2014). Financial forecasting using Anfis networks with quantum-behaved particle swarm optimization. Expert Systems with Applications, 41(14), 6235-6250. https://doi.org/10.1016/j.eswa.2014.04.003 DOI: https://doi.org/10.1016/j.eswa.2014.04.003
Bąk, B. (2017). Investment signals on Polish stock market generated by the Ichimoku technique Against GDP changes. Annales Universitatis Mariae Curie-Skłodowska, sectio H-Oeconomia, 51(1), 19-27. http://doi.org/10.17951/h.2017.51.1.19 DOI: https://doi.org/10.17951/h.2017.51.1.19
Barak, S., Arjmand, A., & Ortobelli, S. (2017). Fusion of multiple diverse predictors in stock market. Information Fusion, 36, 90-102. https://doi.org/10.1016/j.inffus.2016.11.006 DOI: https://doi.org/10.1016/j.inffus.2016.11.006
Bartram, S., & Grinblatt, M. (2018). Agnostic fundamental analysis works. Journal of Financial Economics, 128(1), 125-147. https://doi.org/10.1016/j.jfineco.2016.11.008 DOI: https://doi.org/10.1016/j.jfineco.2016.11.008
Bloomfield, R., O’Hara, M., & Saar, G. (2015). Hidden liquidity: Some new light on dark trading. Journal of Finance, 70(5), 2227-2274. https://doi.org/10.1111/jofi.12301 DOI: https://doi.org/10.1111/jofi.12301
Blume, L., Easley, D., & O’Hara, M. (1994). Market statistics and technical analysis: The role of volume. Journal of Finance, 49(1), 153-181. https://doi.org/10.2307/2329139 DOI: https://doi.org/10.1111/j.1540-6261.1994.tb04424.x
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. https://doi.org/10.2307/2328994 DOI: https://doi.org/10.1111/j.1540-6261.1992.tb04681.x
Brown, S., Goetzmann, W. & Kumar, A. (1998). The Dow Theory: William Peter Hamilton’s track record reconsidered. The Journal of Finance, 53(4), 1311-1333. https://www.jstor.org/stable/117403 DOI: https://doi.org/10.1111/0022-1082.00054
Bulkowski, T. N. (2011). Encyclopedia of chart patterns (v. 225). John Wiley & Sons.
Cahyadi, Y. (2012). Ichimoku Kinko Hyo: Keunikan dan Penerapannya dalam Strategi Perdagangan Valuta Asing (Studi Kasus pada Pergerakan USD/JPY dan EUR/USD). Binus Business Review, 3(1), 480-492. https://doi.org/10.21512/bbr.v3i1.1336 DOI: https://doi.org/10.21512/bbr.v3i1.1336
Cespa, G., & Vives, X. (2015). The beauty contest and short‐term trading. Journal of Finance, 70(5), 2099-2154. https://doi.org/10.1111/jofi.12279 DOI: https://doi.org/10.1111/jofi.12279
Chan, K., Hameed, A., & Tong, W. (2000). Profitability of momentum strategies in the international equity markets. The Journal of Financial and Quantitative Analysis, 35(2), 153-172. https://doi.org/10.2307/2676188 DOI: https://doi.org/10.2307/2676188
Chan, K., Jegadeesh, N., & Lakonishok, J. (1996). Momentum strategies. The Journal of Finance, 51(5), 1681-1713. https://doi.org/10.2307/2329534 DOI: https://doi.org/10.1111/j.1540-6261.1996.tb05222.x
Chang, P., & Osler, C. (1999). Methodical madness: Technical analysis and the irrationality of exchange‐rate forecasts. Economic Journal, 109(458), 636-661. https://doi.org/10.2307/2676188 DOI: https://doi.org/10.1111/1468-0297.00466
Chong, T., Cheng, S., & Wong, E. (2010). A comparison of stock market efficiency of the BRIC countries. Technology and Investment, 1(4), 235. http://doi.org/10.4236/ti.2010.14029 DOI: https://doi.org/10.4236/ti.2010.14029
Cook, J. (2017). Estimating the portion of technical analysts in a market. Applied Economics, 49(41), 4127-4137. https://doi.org/10.1080/00036846.2016.1276274 DOI: https://doi.org/10.1080/00036846.2016.1276274
Corbet, S., Eraslan, V., Lucey, B., & Sensoy, A. (2019). The effectiveness of technical trading rules in cryptocurrency markets. Finance Research Letters, 31, 32-37. https://doi.org/10.1016/j.frl.2019.04.027 DOI: https://doi.org/10.1016/j.frl.2019.04.027
Coutts, J., & Cheung, K.-C. (2000). Trading rules and stock returns: Some preliminary short run evidence from the Hang Seng 1985-1997. Applied Financial Economics, 10(6), 579-586. https://doi.org/10.1080/096031000437935 DOI: https://doi.org/10.1080/096031000437935
Davey, K. (2014). Building winning algorithmic trading systems: A trader’s journey from data mining to Monte Carlo simulation to live trading. John Wiley and Sons. DOI: https://doi.org/10.1002/9781118778944
Deng, S., & Sakurai, A. (2014). Short-term foreign exchange rate trading based on the support/resistance level of Ichimoku Kinkohyo. International Conference on Information Science, Electronics and Electrical Engineering, 1, 337-340. http://doi.org/10.1109/InfoSEEE.2014.6948127 DOI: https://doi.org/10.1109/InfoSEEE.2014.6948127
Deng, S., Yu, H., Wei, C., Yang, T., & Tatsuro, S. (2020). The profitability of Ichimoku Kinkohyo based trading rules in stock markets and FX markets. International Journal of Finance & Economics, 26(4), 5321-5336. https://doi.org/10.1002/ijfe.2067 DOI: https://doi.org/10.1002/ijfe.2067
Elliott, N. (2007). Ichimoku charts: An introduction to Ichimoku kinko clouds. Harriman House Limited.
Fafuła, A., & Drelczuk, K. (2015). Buying stock market winners on Warsaw Stock Exchange-quantitative backtests of a short term trend following strategy. Federated Conference Computer Science and Information Systems. http://doi.org/10.15439/2015F338 DOI: https://doi.org/10.15439/2015F338
Fama, E. (1965). The behavior of stock-market prices. The Journal of Business, 38(1), 34-105. https://www.jstor.org/stable/2350752 DOI: https://doi.org/10.1086/294743
Fama, E. (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 DOI: https://doi.org/10.1111/j.1540-6261.1970.tb00518.x
Fama, E. (1998). Market efficiency, long-term returns, and behavioral finance. Journal of Financial Economics, 49(3), 283-306. https://doi.org/10.1016/S0304-405X(98)00026-9 DOI: https://doi.org/10.1016/S0304-405X(98)00026-9
Fama, E., & Blume, M. (1966). Filter rules and stock market trading profits. The Journal of Business, 39(1, part 2), 226-341. https://www.jstor.org/stable/2351744 DOI: https://doi.org/10.1086/294849
Fama, E., & French, K. (1992). The cross‐section of expected stock returns. The Journal of Finance, 47(2), 427-465. https://doi.org/10.2307/2329112 DOI: https://doi.org/10.1111/j.1540-6261.1992.tb04398.x
Farias, R., Silva, J., Sobreiro, V., & Kimura, H. (2017). A literature review of technical analysis on stock markets. The Quarterly Review of Economics and Finance, 66, 115-126. DOI: https://doi.org/10.1016/j.qref.2017.01.014
Fernández-Rodríguez, F., González-Martel, C., & Sosvilla-Rivero, S. (2000). On the profitability of technical trading rules based on artificial neural networks: Evidence from the Madrid stock market. Economics Letters, 69(1), 89-94. https://doi.org/10.1016/S0165-1765(00)00270-6 DOI: https://doi.org/10.1016/S0165-1765(00)00270-6
García, M. (2006). Are trading rules based on genetic algorithms profitable?. Applied Economics Letters, 13(2), 123-126. https://doi.org/10.1080/13504850500392321 DOI: https://doi.org/10.1080/13504850500392321
Gençay, 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 DOI: https://doi.org/10.1016/S0165-1765(98)00051-2
Gerritsen, D., Bouri, E., Ramezanifar, E., & Roubaud, D. (2020). The profitability of technical trading rules in the Bitcoin market. Finance Research Letters, 34, 101263. https://doi.org/10.1016/j.frl.2019.08.011 DOI: https://doi.org/10.1016/j.frl.2019.08.011
Gold, S. (2015). The viability of six popular technical analysis trading rules in determining effective buy and sell signals: MACD , AROON , RSI , SO , OBV, and ADL. Journal of Applied Financial Research, 2(22), 8 29.
Graham, B., & Dodd, D. (1934). Security analysis. McGraw-Hill.
Granger, C., & Morgenstern, O. (1963). Spectral analysis of New York stock market prices. Kyklos, 16, 1-27. http://www.princeton.edu/~erp/ERParchives/archivepdfs/M45.pdf DOI: https://doi.org/10.1111/j.1467-6435.1963.tb00270.x
Gujarati, D., & Porter, D. (2008). Basic econometrics. (5a ed.). McGraw-Hill.
Harvey, C., Liu, Y., & Zhu, H. (2016). …And the cross-section of expected returns. The Review of Financial Studies, 29(1), 5-68. https://doi.org/10.1093/rfs/hhv059 DOI: https://doi.org/10.1093/rfs/hhv059
Hudson, R., Dempsey, M., & Keasey, K. (1996). A note on weak form of 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 DOI: https://doi.org/10.1016/0378-4266(95)00043-7
Karolyi, G. A. (2016). Home bias, an academic puzzle. Review of Finance, 20(6), 2049-2078. https://doi.org/10.1093/rof/rfw007 DOI: https://doi.org/10.1093/rof/rfw007
Kristjanpoller, 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 DOI: https://doi.org/10.1016/j.eswa.2018.05.011
Kwon, K., & Kish, R. (2002). Technical trading strategies and return predictability: NYSE. Applied Financial Economics, 12(9), 639-653. https://doi.org/10.1080/09603100010016139 DOI: https://doi.org/10.1080/09603100010016139
Lin, 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 DOI: https://doi.org/10.1016/j.finmar.2017.09.003
Linnainmaa, J. T., & Roberts M. R. (2018). The history of the cross‐section of stock returns. Review of Financial Studies, 31(7), 2606-2649. https://doi.org/10.1093/rfs/hhy030 DOI: https://doi.org/10.1093/rfs/hhy030
Linton, D. (2010). Cloud charts: Trading success with the Ichimoku technique. Updata Plc.
Lo, A., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. Journal of Finance, 55(4), 1705-1765. http://doi.org/10.3386/w7613 DOI: https://doi.org/10.1111/0022-1082.00265
Lutey, M., & Rayome, D. (2020). A primer on the Ichimoku cloud indicator. Journal of Marketing Development & Competitiveness, 14(3), 10-20. https://doi.org/10.33423/jmdc.v14i3.3058 DOI: https://doi.org/10.33423/jmdc.v14i3.3058
Luukka, P., Pätäri, E., Fedorova, E., & Garanina, T. (2016). Performance of moving average trading rules in a volatile stock market: The Russian evidence. Emerging Markets Finance and Trade, 52(10), 2434-2450. https://doi.org/10.1080/1540496X.2015.1087785 DOI: https://doi.org/10.1080/1540496X.2015.1087785
Macedo, L., Godinho, P., & Alves, M. (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 DOI: https://doi.org/10.1016/j.eswa.2017.02.033
Mandelbrot, B. (1963). The variation of certain speculative prices. The Journal of Business, 36(4), 394-419. https://www.jstor.org/stable/2350970 DOI: https://doi.org/10.1086/294632
Markowitz, H. (1952). Mean-variance analysis in portfolio choice and capital markets. Journal of Finance, 7, 77-91. DOI: https://doi.org/10.1111/j.1540-6261.1952.tb01525.x
Marshall, B., Nguyen, N., & Visaltanachoti, N. (2017). Time series momentum and moving average trading rules. Quantitative Finance, 17(3), 405-442. https://doi.org/10.1080/14697688.2016.1205209 DOI: https://doi.org/10.1080/14697688.2016.1205209
Mazza, P., & Petitjean, M. (2019). Testing the effect of technical analysis on market quality and order book dynamics. Applied Economics, 51(18), 1947-1976. https://doi.org/10.1080/00036846.2018.1529404 DOI: https://doi.org/10.1080/00036846.2018.1529404
Metghalchi, M., Chang, Y.-H., & Marcucci, J. (2008). 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 DOI: https://doi.org/10.1016/j.irfa.2007.05.001
Metghalchi, M., Chen, C.-P., & Hayes, L. (2015). History of share prices and market efficiency of the Madrid general stock index. International Review of Financial Analysis, 40, 178-184. https://doi.org/10.1016/j.irfa.2015.05.016 DOI: https://doi.org/10.1016/j.irfa.2015.05.016
Metghalchi, M., Hajilee, M., & Hayes, L. (2019). Return predictability and market efficiency: Evidence from the Bulgarian stock market. Eastern European Economics, 57(3), 251-268. DOI: https://doi.org/10.1080/00128775.2018.1542601
Muis, A., & Puji Utami, E. (2020). Analysis of investment decisions of pt. Smartfren telecom TBK post corporate action policy using technical analysis specialising in Ichimoku kinkohyo indicator in 2019. Journal of Accounting and Finance Management, 1(3), 330-341. https://doi.org/10.38035/jafm.v1i3.34
Murphy, J. (1999). Technical analysis of the financial markets: A comprehensive guide to trading methods and applications (2a ed.). New York Institute of Finance.
Nagendra, S., Kumar, S., & Jayashree (2018). Implications and usefulness of fundamental and technical analysis in stock market decision making. Indian Journal of Finance, 12(5), 54-71. http://doi.org/10.17010/ijf/2018/v12i5/123702 DOI: https://doi.org/10.17010/ijf/2018/v12i5/123702
Namdari, A., & Li, Z. (2018). Integrating fundamental and technical analysis of stock market through multi-layer perceptron. 2018 IEEE Technology and Engineering Management Conference. http://doi.org/10.1109/TEMSCON.2018.8488440. DOI: https://doi.org/10.1109/TEMSCON.2018.8488440
Nor, S., & Wickremasinghe, G. (2017). Market efficiency and technical analysis during different market phases: Further evidence from Malaysia. Investment Management and Financial Innovations, 14(2), 359-366. http://doi.org/10.21511/imfi.14(2-2).2017.07 DOI: https://doi.org/10.21511/imfi.14(2-2).2017.07
Osborne, M. (1962). Periodic structure in the Brownian motion of stock prices. Operations Research, 10(3), 345-379. https://www.jstor.org/stable/167679 DOI: https://doi.org/10.1287/opre.10.3.345
Patel, J., Shah, S., Thakkar, P., & Kotecha, K. (2015). Predicting stock and stock price index movement using trend deterministic data preparation and machine learning techniques. Expert Systems with Applications, 42(1), 259-268. https://doi.org/10.1016/j.eswa.2014.07.040 DOI: https://doi.org/10.1016/j.eswa.2014.07.040
Qu, W., Fan, C.-M., & Li, X. (2020). Analysis of an augmented moving least squares approximation and the associated localized method of fundamental solutions. Computers & Mathematics with Applications, 80(1), 13-30. https://doi.org/10.1016/j.camwa.2020.02.015 DOI: https://doi.org/10.1016/j.camwa.2020.02.015
Ready, M. (2002). Profits from technical trading rules. Financial Management, 31(3), 43-61. https://doi.org/10.2307/3666314 DOI: https://doi.org/10.2307/3666314
Sanjin, I. (1969). Ichimoku Kinkohyo. Keizaihendousouken Co.
Selvamuthu, D., Kumar, V., & Mishra, A. (2019). Indian stock market prediction using artificial neural networks on tick data. Financial Innovation, 5(1), 16. https://doi.org/10.1186/s40854-019-0131-7 DOI: https://doi.org/10.1186/s40854-019-0131-7
Shawn, K., Yanyali, S., & Savidge, J. (2016). Do Ichimoku cloud charts work and do they work better in Japan? International Federation of Technical Analysts Journal, 16, 18-24. https://ifta.org/public/files/journal/d_ifta_journal_16.pdf
Souza, M., Ramos, D., Pena, M., Sobreiro, V., & 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 DOI: https://doi.org/10.1186/s40854-018-0087-z
Sweeney, R. (1986). Beating the foreign exchange market. Journal of Finance, 41(1), 163-182. https://doi.org/10.2307/2328350 DOI: https://doi.org/10.1111/j.1540-6261.1986.tb04497.x
Szakmary, A., Davidson, W., & Schwarz, T. (1999). Filter tests in Nasdaq stocks. Financial Review, 34(1), 45-70. https://doi.org/10.1111/j.1540-6288.1999.tb00444.x DOI: https://doi.org/10.1111/j.1540-6288.1999.tb00444.x
Urquhart, A., & Zhang, H. (2019). The performance of technical trading rules in Socially Responsible Investments. International Review of Economics and Finance, 63, 397-411. https://doi.org/10.1016/j.iref.2019.05.002 DOI: https://doi.org/10.1016/j.iref.2019.05.002
Van Horne, J., & Parker, G. (1967). The random walk theory: An empirical test. Financial Analyst Journal, 23, 87-92. https://www.jstor.org/stable/4470248 DOI: https://doi.org/10.2469/faj.v23.n6.87
Walkshäusl, C. (2019). The fundamentals of momentum investing: European evidence on understanding momentum through fundamentals. Accounting and Finance, 59(S1), 831-857. https://doi.org/10.1111/acfi.12462 DOI: https://doi.org/10.1111/acfi.12462
Wang, J., Liu, H.-C., Du, J., & Hsu, Y.-T. (2019). Economic benefits of technical analysis in portfolio management: Evidence from global stock markets. International Journal of Finance and Economics, 24(2), 890-902. https://doi.org/10.1002/ijfe.1697 DOI: https://doi.org/10.1002/ijfe.1697
Yan, X., & Zheng, L. (2017). Fundamental analysis and the cross-section of stock returns: A data-mining approach. Review of Financial Studies, 30(4), 1382-1423. https://doi.org/10.1093/rfs/hhx001 DOI: https://doi.org/10.1093/rfs/hhx001
Zhang, Y., Yang, X., Zhang, Y., Zhang, Y., Wang, M., Ou, J., Zhu, Y., Zeng, H., Wu, J., Lan, C., Zhou, H.-W., Yang, W., & Zhang, Z. (2020). Tools for fundamental analysis functions of TCR repertoires: A systematic comparison. Briefings in bioinformatics, 21(5), 1706-1716. http://doi.org/10.1093/bib/bbz092 DOI: https://doi.org/10.1093/bib/bbz092
Como Citar
APA
ACM
ACS
ABNT
Chicago
Harvard
IEEE
MLA
Turabian
Vancouver
Baixar Citação
Licença
Copyright (c) 2021 Innovar
Este trabalho está licenciado sob uma licença Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Todos os artigos publicados pela Innovar estão disponíveis no mundo inteiro com acesso aberto e sob a licença Creative Commons Atribuição-NãoComercial-SemDerivações 4.0 Internacional (CC BY-NC-ND 4.0).
Assim que os artigos para um número forem selecionados e antes de começar a etapa da produção editorial, os autores devem assinar uma cessão de direitos patrimoniais de sua obra. A Innovar recorre às leis colombianas em matéria de direitos autorais.
O material desta revista pode ser reproduzido ou citado para fins académicos, citando a fonte.
Esta obra está licenciada sob uma Licença Creative Commons:
