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Using genetic algorithms to find technical trading rules

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Cited by:

  1. Chong, Terence Tai-Leung & Lam, Tau-Hing & Yan, Isabel Kit-Ming, 2012. "Is the Chinese stock market really inefficient?," China Economic Review, Elsevier, vol. 23(1), pages 122-137.
  2. Serge Hayward, 2005. "The Role of Heterogeneous Agents’ Past and Forward Time Horizons in Formulating Computational Models," Computational Economics, Springer;Society for Computational Economics, vol. 25(1), pages 25-40, February.
  3. Manahov, Viktor & Hudson, Robert & Linsley, Philip, 2014. "New evidence about the profitability of small and large stocks and the role of volume obtained using Strongly Typed Genetic Programming," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 299-316.
  4. repec:eee:quaeco:v:66:y:2017:i:c:p:115-126 is not listed on IDEAS
  5. Kampouridis, Michael & Chen, Shu-Heng & Tsang, Edward, 2012. "Market fraction hypothesis: A proposed test," International Review of Financial Analysis, Elsevier, vol. 23(C), pages 41-54.
  6. Tzu-Wen Kuo & Shu-Heng Chen,, 2003. "Genetic Programming and International Short-Term Capital Flow," Computing in Economics and Finance 2003 74, Society for Computational Economics.
  7. Thomas H. Noe & Michael J. Rebello & Jun Wang, 2006. "The Evolution of Security Designs," Journal of Finance, American Finance Association, vol. 61(5), pages 2103-2135, October.
  8. K. Lam & Wei Li, 2004. "Is the ‘Perfect’ Timing Strategy Truly Perfect?," Review of Quantitative Finance and Accounting, Springer, vol. 22(1), pages 39-51, January.
  9. Vaihekoski, Mika, 2008. "History of finance research and education in Finland : the first thirty years," Research Discussion Papers 18/2008, Bank of Finland.
  10. Cheema, Muhammad A. & Nartea, Gilbert V & Man, Yimei, 2017. "Cross-Sectional and Time-Series Momentum Returns and Market States," MPRA Paper 78989, University Library of Munich, Germany.
  11. Kaucic, Massimiliano, 2010. "Investment using evolutionary learning methods and technical rules," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1717-1727, December.
  12. Noe, Thomas H. & Rebello, Michael & Wang, Jun, 2012. "Learning to bid: The design of auctions under uncertainty and adaptation," Games and Economic Behavior, Elsevier, vol. 74(2), pages 620-636.
  13. Wang, Zi-Mei & Chiao, Chaoshin & Chang, Ya-Ting, 2012. "Technical analyses and order submission behaviors: Evidence from an emerging market," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 109-128.
  14. Cheol-Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, September.
  15. Ülkü, Numan & Prodan, Eugeniu, 2013. "Drivers of technical trend-following rules' profitability in world stock markets," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 214-229.
  16. Marcos Alvarez Díaz & Manuel González Gómez, 2003. "Modelización semiparamétrica y validación teórica del método de valoración contingente. Aplicación de un algoritmo genético," Hacienda Pública Española, IEF, vol. 164(1), pages 29-47, march.
  17. Shynkevich, Andrei, 2013. "Time-series momentum as an intra- and inter-industry effect: Implications for market efficiency," Journal of Economics and Business, Elsevier, vol. 69(C), pages 64-85.
  18. Andreas Krause, 2009. "Evaluating the performance of adapting trading strategies with different memory lengths," Papers 0901.0447, arXiv.org.
  19. Neely, Christopher J. & Weller, Paul A., 2001. "Technical analysis and central bank intervention," Journal of International Money and Finance, Elsevier, vol. 20(7), pages 949-970, December.
  20. Feil, Jan-Henning & Musshoff, Oliver, 2013. "Modelling investment and disinvestment decisions under competition, uncertainty and different market interventions," Economic Modelling, Elsevier, vol. 35(C), pages 443-452.
  21. Gradojevic, Nikola, 2007. "Non-linear, hybrid exchange rate modeling and trading profitability in the foreign exchange market," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 557-574, February.
  22. Terence Tai-Leung Chong & Wing-Kam Ng & Venus Khim-Sen Liew, 2014. "Revisiting the Performance of MACD and RSI Oscillators," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 7(1), pages 1-12, February.
  23. Andriosopoulos, Kostas & Nomikos, Nikos, 2014. "Performance replication of the Spot Energy Index with optimal equity portfolio selection: Evidence from the UK, US and Brazilian markets," European Journal of Operational Research, Elsevier, vol. 234(2), pages 571-582.
  24. Vlad Pavlov & Stan Hurn, 2009. "Testing the Profitability of Technical Analysis as a Portfolio Selection Strategy," NCER Working Paper Series 52, National Centre for Econometric Research.
  25. Liu, Xiaojia & An, Haizhong & Wang, Lijun & Jia, Xiaoliang, 2017. "An integrated approach to optimize moving average rules in the EUA futures market based on particle swarm optimization and genetic algorithms," Applied Energy, Elsevier, vol. 185(P2), pages 1778-1787.
  26. Bernd Brandl & Christian Keber & Matthias Schuster, 2006. "An automated econometric decision support system: forecasts for foreign exchange trades," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 14(4), pages 401-415, December.
  27. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
  28. Hui Qu & Xindan Li, 2014. "Building Technical Trading System with Genetic Programming: A New Method to Test the Efficiency of Chinese Stock Markets," Computational Economics, Springer;Society for Computational Economics, vol. 43(3), pages 301-311, March.
  29. Laura Nuñez, 2004. "Do Moving Average Rules Make Profits? A Study Using The Madrid Stock Market," Working Papers Economia wp04-03, Instituto de Empresa, Area of Economic Environment.
  30. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
  31. Neely, Christopher J., 2003. "Risk-adjusted, ex ante, optimal technical trading rules in equity markets," International Review of Economics & Finance, Elsevier, vol. 12(1), pages 69-87.
  32. Lensberg, Terje & Schenk-Hoppé, Klaus Reiner, 2006. "On the Evolution of Investment Strategies and the Kelly Rule – A Darwinian Approach," Discussion Papers 2006/23, Norwegian School of Economics, Department of Business and Management Science.
  33. Pedro N. Rodríguez & Simón Sosvilla-Rivero, 2006. "Using machine learning algorithms to find patterns in stock prices," Working Papers 2006-12, FEDEA.
  34. Laura Nuñez, 2002. "An Analysis Of The Robustness Of Genetic Algorithm (ga) Methodology In The Design Of Trading System," Working Papers Economia wp02-24, Instituto de Empresa, Area of Economic Environment.
  35. Jukka Ilomäki, 2016. "Risk-Free Rates And Animal Spirits In Financial Markets," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(03), pages 1-18, September.
  36. repec:spt:apfiba:v:7:y:2017:i:6:f:7_6_4 is not listed on IDEAS
  37. Lukas Menkhoff & Mark P. Taylor, 2007. "The Obstinate Passion of Foreign Exchange Professionals: Technical Analysis," Journal of Economic Literature, American Economic Association, vol. 45(4), pages 936-972, December.
  38. Trifan, Emanuela, 2004. "Entscheidungsregeln und ihr Einfluss auf den Aktienkurs," Darmstadt Discussion Papers in Economics 131, Darmstadt University of Technology, Department of Law and Economics.
  39. Friesen, Geoffrey C. & Weller, Paul A. & Dunham, Lee M., 2009. "Price trends and patterns in technical analysis: A theoretical and empirical examination," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1089-1100, June.
  40. Wang, Lijun & An, Haizhong & Liu, Xiaojia & Huang, Xuan, 2016. "Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach," Applied Energy, Elsevier, vol. 162(C), pages 1608-1618.
  41. Gradojevic, Nikola & Gençay, Ramazan, 2013. "Fuzzy logic, trading uncertainty and technical trading," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 578-586.
  42. Eder Oliveira Abensur, 2007. "Genetic Algorithms for Development of New Financial Products," Brazilian Review of Finance, Brazilian Society of Finance, vol. 5(1), pages 59-77.
  43. M. A. H. Dempster & C. M. Jones, 2002. "Can channel pattern trading be profitably automated?," The European Journal of Finance, Taylor & Francis Journals, vol. 8(3), pages 275-301.
  44. Zhu, Yingzi & Zhou, Guofu, 2009. "Technical analysis: An asset allocation perspective on the use of moving averages," Journal of Financial Economics, Elsevier, vol. 92(3), pages 519-544, June.
  45. Bauer, Rob & Derwall, Jeroen & Molenaar, Roderick, 2004. "The real-time predictability of the size and value premium in Japan," Pacific-Basin Finance Journal, Elsevier, vol. 12(5), pages 503-523, November.
  46. Isakov, Dusan & Marti, Didier, 2011. "Technical Analysis with a Long-Term Perspective: Trading Strategies and Market Timing Ability," FSES Working Papers 421, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
  47. Trifan, Emanuela, 2004. "Decision Rules and their Influence on Asset Prices," Darmstadt Discussion Papers in Economics 139, Darmstadt University of Technology, Department of Law and Economics.
  48. Robert Pereira, 1999. "Forecasting Ability but No Profitability: an Empirical Evaluation of Genetic Algorithm-Optimized Technical Trading Rules," Working Papers 1999.06, School of Economics, La Trobe University.
  49. Xue-Zhong He & Kai Li, 2014. "Time Series Momentum and Market Stability," Research Paper Series 341, Quantitative Finance Research Centre, University of Technology, Sydney.
  50. Julián Andrada Félix & Fernando Fernández Rodríguez & María Dolores García Artiles, 2004. "Non-linear trading rules in the New York Stock Exchange," Documentos de trabajo conjunto ULL-ULPGC 2004-05, Facultad de Ciencias Económicas de la ULPGC.
  51. Marshall, Ben R. & Young, Martin R. & Rose, Lawrence C., 2006. "Candlestick technical trading strategies: Can they create value for investors?," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2303-2323, August.
  52. Kozhan, Roman & Salmon, Mark, 2012. "The information content of a limit order book: The case of an FX market," Journal of Financial Markets, Elsevier, vol. 15(1), pages 1-28.
  53. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
  54. Cialenco, Igor & Protopapadakis, Aris, 2011. "Do technical trading profits remain in the foreign exchange market? Evidence from 14 currencies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(2), pages 176-206, April.
  55. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
  56. Paskalis Glabadanidis, 2015. "Market Timing With Moving Averages," International Review of Finance, International Review of Finance Ltd., vol. 15(3), pages 387-425, September.
  57. Marshall, Ben R. & Cahan, Rochester H. & Cahan, Jared M., 2008. "Does intraday technical analysis in the U.S. equity market have value?," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 199-210, March.
  58. Fong, Wai Mun & Yong, Lawrence H. M., 2005. "Chasing trends: recursive moving average trading rules and internet stocks," Journal of Empirical Finance, Elsevier, vol. 12(1), pages 43-76, January.
  59. He, Xue-Zhong & Li, Kai, 2015. "Profitability of time series momentum," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 140-157.
  60. de Menezes, Lilian M. & Nikolaev, Nikolay Y., 2006. "Forecasting with genetically programmed polynomial neural networks," International Journal of Forecasting, Elsevier, vol. 22(2), pages 249-265.
  61. Mika Vaihekoski, 2011. "History of financial research and education in Finland," The European Journal of Finance, Taylor & Francis Journals, vol. 17(5-6), pages 339-354.
  62. Chiarella, Carl & Ladley, Daniel, 2016. "Chasing trends at the micro-level: The effect of technical trading on order book dynamics," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 119-131.
  63. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1770, August.
  64. Ghandar, Adam & Michalewicz, Zbigniew & Zurbruegg, Ralf, 2016. "The relationship between model complexity and forecasting performance for computer intelligence optimization in finance," International Journal of Forecasting, Elsevier, vol. 32(3), pages 598-613.
  65. Andrada-Félix Julián & Fernadez-Rodriguez Fernando & Garcia-Artiles Maria-Dolores & Sosvilla-Rivero Simon, 2003. "An Empirical Evaluation of Non-Linear Trading Rules," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(3), pages 1-32, October.
  66. Auer, Benjamin R., 2016. "On the performance of simple trading rules derived from the fractal dynamics of gold and silver price fluctuations," Finance Research Letters, Elsevier, vol. 16(C), pages 255-267.
  67. Chueh-Yung Tsao, 2010. "Portfolio selection based on the mean-VaR efficient frontier," Quantitative Finance, Taylor & Francis Journals, vol. 10(8), pages 931-945.
  68. Marcos Álvarez-Díaz & Lucy Amigo Dobaño, 2003. "Métodos No-Lineales De Predicción En El Mercado De Valores Tecnológicos En España. Una Verificación De La Hipótesis Débil De Eficiencia," Working Papers 0303, Universidade de Vigo, Departamento de Economía Aplicada.
  69. Nunez-Letamendia, Laura, 2007. "Fitting the control parameters of a genetic algorithm: An application to technical trading systems design," European Journal of Operational Research, Elsevier, vol. 179(3), pages 847-868, June.
  70. Shynkevich, Andrei, 2012. "Performance of technical analysis in growth and small cap segments of the US equity market," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 193-208.
  71. Meredith Beechey & David Gruen & James Vickery, 2000. "The Efficient Market Hypothesis: A Survey," RBA Research Discussion Papers rdp2000-01, Reserve Bank of Australia.
  72. A. Malliaris & Mary Malliaris, 2014. "N-tuple S&P patterns across decades, 1950–2011," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(2), pages 339-353, June.
  73. Paskalis Glabadanidis, 2014. "The Market Timing Power of Moving Averages: Evidence from US REITs and REIT Indexes," International Review of Finance, International Review of Finance Ltd., vol. 14(2), pages 161-202, June.
  74. Manahov, Viktor & Hudson, Robert & Hoque, Hafiz, 2015. "Return predictability and the ‘wisdom of crowds’: Genetic Programming trading algorithms, the Marginal Trader Hypothesis and the Hayek Hypothesis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 37(C), pages 85-98.
  75. Simone Cirillo & Stefan Lloyd & Peter Nordin, 2014. "Evolving intraday foreign exchange trading strategies utilizing multiple instruments price series," Papers 1411.2153, arXiv.org.
  76. Parisi, Franco & Vasquez, Alejandra, 2000. "Simple technical trading rules of stock returns: evidence from 1987 to 1998 in Chile," Emerging Markets Review, Elsevier, vol. 1(2), pages 152-164, September.
  77. Julián Andrada-Félix & Fernando Fernández-Rodríguez, 2008. "Improving moving average trading rules with boosting and statistical learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(5), pages 433-449.
  78. Fernando Fernandez-Rodriguez & Christian Gonzalez-Martel & Simon Sosvilla-Rivero, 2005. "Optimization of technical rules by genetic algorithms: evidence from the Madrid stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 15(11), pages 773-775.
  79. Hsu, Po-Hsuan & Hsu, Yu-Chin & Kuan, Chung-Ming, 2010. "Testing the predictive ability of technical analysis using a new stepwise test without data snooping bias," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 471-484, June.
  80. Dan Anghel, 2013. "How Reliable is the Moving Average Crossover Rule for an Investor on the Romanian Stock Market?," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 5(2), pages 089-115, December.
  81. Manuel Ammann & Christian Zenkner, 2003. "Tactical Asset Allocation mit Genetischen Algorithmen," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 139(I), pages 1-40, March.
  82. Kevin Krieger & Nathan Mauck & Denghui Chen, 2012. "VIX changes and derivative returns on FOMC meeting days," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(3), pages 315-331, September.
  83. repec:bla:irvfin:v:17:y:2017:i:3:p:353-394 is not listed on IDEAS
  84. Jin Zhang & Dietmar Maringer, 2016. "Using a Genetic Algorithm to Improve Recurrent Reinforcement Learning for Equity Trading," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 551-567, April.
  85. Giovanni Ferri & Doris Neuberger, 2014. "The Banking Regulatory Bubble and How to Get out of It," Rivista di Politica Economica, SIPI Spa, issue 2, pages 39-69, April-Jun.
  86. Chen, Chien-Hua & Su, Xuan-Qi & Lin, Jun-Biao, 2016. "The role of information uncertainty in moving-average technical analysis: A study of individual stock-option issuance in Taiwan," Finance Research Letters, Elsevier, vol. 18(C), pages 263-272.
  87. Shangkun Deng & Kazuki Yoshiyama & Takashi Mitsubuchi & Akito Sakurai, 2015. "Hybrid Method of Multiple Kernel Learning and Genetic Algorithm for Forecasting Short-Term Foreign Exchange Rates," Computational Economics, Springer;Society for Computational Economics, vol. 45(1), pages 49-89, January.
  88. Wolbert-Haverkamp, Matthias & Feil, Jan-Henning & Mußhoff, Oliver, 2014. "The value chain of heat production from woody biomass under market competition and different intervention systems: An agent-based real options model," DARE Discussion Papers 1407, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).
  89. Feil, Jan-Henning & Mußhoff, Oliver, 2016. "Analysing investment and disinvestment decisions under uncertainty, firm heterogeneity and tradable output permits," DARE Discussion Papers 1602, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).
  90. Cyril Schoreels & Jonathan M. Garibaldi, 2006. "Comparative study of central decision makers versus groups of evolved agents trading in equity markets," Computing in Economics and Finance 2006 410, Society for Computational Economics.
  91. Sermpinis, Georgios & Stasinakis, Charalampos & Rosillo, Rafael & de la Fuente, David, 2017. "European Exchange Trading Funds Trading with Locally Weighted Support Vector Regression," European Journal of Operational Research, Elsevier, vol. 258(1), pages 372-384.
  92. Shynkevich, Andrei, 2012. "Short-term predictability of equity returns along two style dimensions," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 675-685.
  93. Lee, Chun I & Gleason, Kimberly C. & Mathur, Ike, 2001. "Trading rule profits in Latin American currency spot rates," International Review of Financial Analysis, Elsevier, vol. 10(2), pages 135-156.
  94. Zi-Yu Li & Yuan-Biao Zhang & Jia-Yu Zhong & Xiao-Xu Yan & Xin-Guang Lv, 2017. "Research on Quantitative Trading Strategy Based on Neural Network Algorithm and Fisher Linear Discriminant," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(2), pages 133-141, February.
  95. Wei, Liang-Ying, 2013. "A hybrid model based on ANFIS and adaptive expectation genetic algorithm to forecast TAIEX," Economic Modelling, Elsevier, vol. 33(C), pages 893-899.
  96. Yochanan Shachmurove & Uri BenZion & Paul Klein & Joseph Yagil, 2001. "A Moving Average Comparison of the Tel-Aviv 25 and S&P 500 Stock Indices," Penn CARESS Working Papers 4731f3394c43bebf4d3191c81, Penn Economics Department.
  97. repec:spr:eurasi:v:7:y:2017:i:3:d:10.1007_s40821-016-0056-2 is not listed on IDEAS
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