IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!)

Citations for "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation"

by Andrew Lo & Harry Mamaysky & Jiang Wang

For a complete description of this item, click here. For a RSS feed for citations of this item, click here.
as in new window

  1. 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.
  2. Xue-Zhong He & Min Zheng, 2010. "Dynamics of Moving Average Rules in a Continuous-time Financial Market Model," Research Paper Series 268, Quantitative Finance Research Centre, University of Technology, Sydney.
  3. Bohm, Volker & Wenzelburger, Jan, 2005. "On the performance of efficient portfolios," Journal of Economic Dynamics and Control, Elsevier, vol. 29(4), pages 721-740, April.
  4. Boainain, Pedro G. & Valls Pereira, Pedro L., 2009. "“Ombro-Cabeça-Ombro”: Testando a Lucratividade do Padrão Gráfico de Análise Técnica no Mercado de Ações Brasileiro
    [Head and Shoulder: testing the profitability of graphic pattern of technical anal
    ," MPRA Paper 15653, University Library of Munich, Germany.
  5. Li-Xin Wang, 2014. "Dynamical Models of Stock Prices Based on Technical Trading Rules Part III: Application to Hong Kong Stocks," Papers 1401.1892, arXiv.org, revised Feb 2016.
  6. Fry, John, 2013. "Bubbles, shocks and elementary technical trading strategies," MPRA Paper 47052, University Library of Munich, Germany.
  7. Bekiros, Stelios D., 2015. "Heuristic learning in intraday trading under uncertainty," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 34-49.
  8. Taylor, Nick, 2014. "The rise and fall of technical trading rule success," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 286-302.
  9. Dejan Eric & Goran Andjelic & Srdjan Redzepagic, 2009. "Application of MACD and RVI indicators as functions of investment strategy optimization on the financial market," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics, vol. 27(1), pages 171-196.
  10. Michael McAleer & John Suen & Wing Keung Wong, 2013. "Profiteering from the Dot-com Bubble, Sub-Prime Crisis and Asian Financial Crisis," KIER Working Papers 869, Kyoto University, Institute of Economic Research.
  11. Walid Omrane & Hervé Oppens, 2006. "The performance analysis of chart patterns: Monte Carlo simulation and evidence from the euro/dollar foreign exchange market," Empirical Economics, Springer, vol. 30(4), pages 947-971, January.
  12. Michel Fliess & C\'edric Join, 2008. "Time Series Technical Analysis via New Fast Estimation Methods: A Preliminary Study in Mathematical Finance," Papers 0811.1561, arXiv.org, revised Nov 2008.
  13. He, Xue-Zhong & Li, Kai, 2015. "Profitability of time series momentum," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 140-157.
  14. Baaquie, Belal E. & Cao, Yang & Lau, Ada & Tang, Pan, 2012. "Path integral for equities: Dynamic correlation and empirical analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1408-1427.
  15. 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.
  16. Charteris, Ailie & Chau, Frankie & Gavriilidis, Konstantinos & Kallinterakis, Vasileios, 2014. "Premiums, discounts and feedback trading: Evidence from emerging markets' ETFs," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 80-89.
  17. Chong, Terence Tai Leung & Poon, Ka-Ho, 2014. "A New Recognition Algorithm for “Head-and-Shoulders” Price Patterns," MPRA Paper 60825, University Library of Munich, Germany.
  18. Andreas Gronlund & Il Gu Yi & Beom Jun Kim, 2012. "Fractal Profit Landscape of the Stock Market," Papers 1205.0505, arXiv.org.
  19. Fischer, Thomas & Riedler, Jesper, 2012. "Prices, debt and market structure in an agent-based model of the financial market," ZEW Discussion Papers 12-045, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  20. Carol L. Osler, 2003. "Currency Orders and Exchange Rate Dynamics: An Explanation for the Predictive Success of Technical Analysis," Journal of Finance, American Finance Association, vol. 58(5), pages 1791-1820, October.
  21. Ni, Yensen & Liao, Yi-Ching & Huang, Paoyu, 2015. "MA trading rules, herding behaviors, and stock market overreaction," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 253-265.
  22. Hüsler, A. & Sornette, D. & Hommes, C.H., 2013. "Super-exponential bubbles in lab experiments: Evidence for anchoring over-optimistic expectations on price," Journal of Economic Behavior & Organization, Elsevier, vol. 92(C), pages 304-316.
  23. Kuang, P. & Schröder, M. & Wang, Q., 2014. "Illusory profitability of technical analysis in emerging foreign exchange markets," International Journal of Forecasting, Elsevier, vol. 30(2), pages 192-205.
  24. Lu, Tsung-Hsun, 2014. "The profitability of candlestick charting in the Taiwan stock market," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 65-78.
  25. Bekiros, Stelios D., 2010. "Heterogeneous trading strategies with adaptive fuzzy Actor-Critic reinforcement learning: A behavioral approach," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1153-1170, June.
  26. Papailias, Fotis & Thomakos, Dimitrios D., 2015. "An improved moving average technical trading rule," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 458-469.
  27. Li-Xin Wang, 2014. "Dynamical Models of Stock Prices Based on Technical Trading Rules Part I: The Models," Papers 1401.1888, arXiv.org, revised Feb 2016.
  28. Gradojevic, Nikola & Gençay, Ramazan, 2013. "Fuzzy logic, trading uncertainty and technical trading," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 578-586.
  29. Frank H. Westerhoff, 2006. "Technical Analysis Based On Price-Volume Signals And The Power Of Trading Breaks," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 227-244.
  30. 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.
  31. Dai, Min & Li, Peifan & Zhang, Jin E., 2010. "A lattice algorithm for pricing moving average barrier options," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 542-554, March.
  32. 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.
  33. BEN OMRANE, Walid & VAN OPPEN, Hervé, 2004. "The predictive success and profitability of chart patterns in the Euro/Dollar foreign exchange market," CORE Discussion Papers 2004035, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  34. Roscoe, Philip & Howorth, Carole, 2009. "Identification through technical analysis: A study of charting and UK non-professional investors," Accounting, Organizations and Society, Elsevier, vol. 34(2), pages 206-221, February.
  35. Zongwu Cai & Jiancheng Jiang & Jingshuang Zhang & Xibin Zhang, 2015. "A new semiparametric test for superior predictive ability," Empirical Economics, Springer, vol. 48(1), pages 389-405, February.
  36. Bertrand Maillet & Thierry Michel, 2005. "Technical analysis profitability when exchange rates are pegged: A note," The European Journal of Finance, Taylor & Francis Journals, vol. 11(6), pages 463-470.
  37. Gao, Yan & Li, Honggang, 2011. "A consolidated model of self-fulfilling expectations and self-destroying expectations in financial markets," Journal of Economic Behavior & Organization, Elsevier, vol. 77(3), pages 368-381, March.
  38. 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.
  39. Bock, David & Andersson, Eva & Frisén, Marianne, 2007. "Similarities and differences between statistical surveillance and certain decision rules in finance," Research Reports 2007:8, Statistical Research Unit, Department of Economics, School of Business, Economics and Law, University of Gothenburg.
  40. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
  41. 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.
  42. James Angel & Douglas McCabe, 2013. "Fairness in Financial Markets: The Case of High Frequency Trading," Journal of Business Ethics, Springer, vol. 112(4), pages 585-595, February.
  43. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, Elsevier.
  44. Horton, Marshall J., 2009. "Stars, crows, and doji: The use of candlesticks in stock selection," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(2), pages 283-294, May.
  45. Gebka, Bartosz & Hudson, Robert S. & Atanasova, Christina V., 2015. "The benefits of combining seasonal anomalies and technical trading rules," Finance Research Letters, Elsevier, vol. 14(C), pages 36-44.
  46. 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.
  47. 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.
  48. Schulmeister, Stephan, 2009. "Profitability of technical stock trading: Has it moved from daily to intraday data?," Review of Financial Economics, Elsevier, vol. 18(4), pages 190-201, October.
  49. K. J. Hong & S. Satchell, 2013. "Time Series Momentum Trading Strategy and Autocorrelation Amplification," Cambridge Working Papers in Economics 1322, Faculty of Economics, University of Cambridge.
  50. Lubnau, Thorben, 2014. "Spread trading strategies in the crude oil futures market," Discussion Papers 353, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
  51. Andrew Clare & James Seaton & Peter N Smith & Stephen Thomas, 2012. "BREAKING INTO THE BLACKBOX: Trend Following, Stop Losses, and the Frequency of Trading: the case of the S&P500," Discussion Papers 12/11, Department of Economics, University of York.
  52. Nikolai Dokuchaev, 2015. "Modelling Possibility of Short-Term Forecasting of Market Parameters for Portfolio Selection," Annals of Economics and Finance, Society for AEF, vol. 16(1), pages 143-161, May.
  53. Batchelor, Roy & Kwan, Tai Yeong, 2007. "Judgemental bootstrapping of technical traders in the bond market," International Journal of Forecasting, Elsevier, vol. 23(3), pages 427-445.
  54. David Goldbaum, 2003. "Profitable technical trading rules as a source of price instability," Quantitative Finance, Taylor & Francis Journals, vol. 3(3), pages 220-229.
  55. Chen, Shi & Bao, Si & Zhou, Yu, 2016. "The predictive power of Japanese candlestick charting in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 148-165.
  56. Günter Franke & Erik Lüders, 2004. "Why Do Asset Prices Not Follow Random Walks?," CoFE Discussion Paper 04-05, Center of Finance and Econometrics, University of Konstanz.
  57. Blanchet-Scalliet, Christophette & Diop, Awa & Gibson, Rajna & Talay, Denis & Tanre, Etienne, 2007. "Technical analysis compared to mathematical models based methods under parameters mis-specification," Journal of Banking & Finance, Elsevier, vol. 31(5), pages 1351-1373, May.
  58. Cars Hommes & Carl Chiarella & Xue-Zhong He, 2004. "A Dynamical Analysis of Moving Average Rules," Computing in Economics and Finance 2004 238, Society for Computational Economics.
  59. Qian, Hang, 2009. "Estimating SUR Tobit Model while errors are gaussian scale mixtures: with an application to high frequency financial data," MPRA Paper 31509, University Library of Munich, Germany.
  60. Wing-Keung Wong & Boon-Kiat Chew & Douglas Sikorsk, 2001. "Can the Forecasts Generated from E/P Ratio and Bond Yield be Used to Beat Stock Markets?," Multinational Finance Journal, Multinational Finance Journal, vol. 5(1), pages 59-86, March.
  61. Vitali Alexeev & Francis Tapon, 2010. "Testing Weak Form Efficiency on the Toronto Stock Exchange," Working Papers 1002, University of Guelph, Department of Economics and Finance.
  62. Suzuki, Tomoya & Ohkura, Yuushi, 2016. "Financial technical indicator based on chaotic bagging predictors for adaptive stock selection in Japanese and American markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 50-66.
  63. 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.
  64. Yin-wong Cheung, 2006. "An Empirical Model of Daily Highs and Lows," Working Papers 072006, Hong Kong Institute for Monetary Research.
  65. Rivera-Castro, Miguel A. & Miranda, José G.V. & Borges, Ernesto P. & Cajueiro, Daniel O. & Andrade, Roberto F.S., 2012. "A top–bottom price approach to understanding financial fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1489-1496.
  66. Carine Brasseur & Marcelo Espinoza & Johan A. K. Suykens & Tony Van Gestel & Bart Baesens & Bart De Moor, 2006. "A Bayesian nonlinear support vector machine error correction model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(2), pages 77-100.
  67. Bekiros, Stelios D., 2013. "Irrational fads, short-term memory emulation, and asset predictability," Review of Financial Economics, Elsevier, vol. 22(4), pages 213-219.
  68. Komáromi, György, 2002. "A hatékony piacok elméletének elméleti és gyakorlati relevanciája
    [The theoretical and practical relevance of the theory of efficient markets]
    ," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(5), pages 377-395.
  69. Michel Fliess & Cédric Join, 2008. "Time Series Technical Analysis via New Fast Estimation Methods: A Preliminary Study in Mathematical Finance," Post-Print inria-00338099, HAL.
  70. Sukanto Bhattacharya & Kuldeep Kumar, 2006. "A Computational Exploration of the Efficacy of Fibonacci Sequences in Technical Analysis and Trading," Annals of Economics and Finance, Society for AEF, vol. 7(1), pages 185-196, May.
  71. Dorfleitner, Gregor & Klein, Christian, 2003. "Technical Analysis as a Method of Risk Management," Arbeitspapiere zur mathematischen Wirtschaftsforschung 184, Universität Augsburg, Institut für Statistik und Mathematische Wirtschaftstheorie.
  72. 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, 09.
  73. Dokuchaev, N. G. & Savkin, Andrey V., 2004. "Universal strategies for diffusion markets and possibility of asymptotic arbitrage," Insurance: Mathematics and Economics, Elsevier, vol. 34(3), pages 409-419, June.
  74. 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.
  75. Chen, Cheng-Wei & Huang, Chin-Sheng & Lai, Hung-Wei, 2009. "The impact of data snooping on the testing of technical analysis: An empirical study of Asian stock markets," Journal of Asian Economics, Elsevier, vol. 20(5), pages 580-591, September.
  76. 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.
  77. Andreas Krause, 2009. "Evaluating the performance of adapting trading strategies with different memory lengths," Papers 0901.0447, arXiv.org.
  78. Rompotis, Gerasimos G., 2011. "Testing weak-form efficiency of exchange traded funds market," MPRA Paper 36020, University Library of Munich, Germany.
  79. Cajueiro, Daniel O. & Tabak, Benjamin M., 2006. "Testing for predictability in equity returns for European transition markets," Economic Systems, Elsevier, vol. 30(1), pages 56-78, March.
  80. Hsu, Po-Hsuan & Taylor, Mark P, 2014. "Forty Years, Thirty Currencies and 21,000 Trading Rules: A Large-scale, Data-Snooping Robust Analysis of Technical Trading in the Foreign Exchange Market," CEPR Discussion Papers 10018, C.E.P.R. Discussion Papers.
  81. 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.
  82. Wing-Keung Wong & Meher Manzur & Boon-Kiat Chew, 2003. "How rewarding is technical analysis? Evidence from Singapore stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 13(7), pages 543-551.
  83. Hudson, Robert S. & Gregoriou, Andros, 2015. "Calculating and comparing security returns is harder than you think: A comparison between logarithmic and simple returns," International Review of Financial Analysis, Elsevier, vol. 38(C), pages 151-162.
  84. Caporin, Massimiliano & Ranaldo, Angelo & Santucci de Magistris, Paolo, 2013. "On the predictability of stock prices: A case for high and low prices," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5132-5146.
  85. Tim Gebbie & Fayyaaz Loonat, 2016. "Learning zero-cost portfolio selection with pattern matching," Papers 1605.04600, arXiv.org.
  86. Guharay, Samar K. & Thakur, Gaurav S. & Goodman, Fred J. & Rosen, Scott L. & Houser, Daniel, 2013. "Analysis of non-stationary dynamics in the financial system," Economics Letters, Elsevier, vol. 121(3), pages 454-457.
  87. Spyros Skouras, 2001. "Decisionmetrics: A Decision-Based Approach to Econometric Modeling," Working Papers 01-11-064, Santa Fe Institute.
  88. Carol L. Osler, 2000. "Support for resistance: technical analysis and intraday exchange rates," Economic Policy Review, Federal Reserve Bank of New York, issue Jul, pages 53-68.
  89. K. J. Hong & S. Satchell, 2015. "Time series momentum trading strategy and autocorrelation amplification," Quantitative Finance, Taylor & Francis Journals, vol. 15(9), pages 1471-1487, September.
  90. Weihong HUANG & Wanying Wang, 2012. "Price-Volume Relations in Financial Market," Economic Growth Centre Working Paper Series 1209, Nanyang Technological University, School of Humanities and Social Sciences, Economic Growth Centre.
  91. Sid Ghoshal & Stephen Roberts, 2016. "Extracting Predictive Information from Heterogeneous Data Streams using Gaussian Processes," Papers 1603.06202, arXiv.org.
  92. Akber, Ushna & Muhammad, Nabeel, 2013. "Is Pakistan Stock Market moving towards Weak-form efficiency? Evidence from the Karachi Stock Exchange and the Random Walk Nature of free-float of shares of KSE 30 Index," MPRA Paper 49128, University Library of Munich, Germany.
  93. Zhu, Min & Atri, Said & Yegen, Eyub, 2016. "Are candlestick trading strategies effective in certain stocks with distinct features?," Pacific-Basin Finance Journal, Elsevier, vol. 37(C), pages 116-127.
  94. Li-Xin Wang, 2014. "Dynamical Models of Stock Prices Based on Technical Trading Rules Part II: Analysis of the Models," Papers 1401.1891, arXiv.org, revised Feb 2016.
  95. Wong, Wing-Keung & Du, Jun & Chong, Terence Tai-Leung, 2005. "Do the technical indicators reward chartists? A study on the stock markets of China, Hong Kong and Taiwan," Review of Applied Economics, Review of Applied Economics, vol. 1(2).
  96. Adrian Pagan, 2013. "Patterns and Their Uses," NCER Working Paper Series 96, National Centre for Econometric Research.
  97. 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.
  98. 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.
  99. Leigh, William & Paz, Noemi & Purvis, Russell, 2002. "Market timing: a test of a charting heuristic," Economics Letters, Elsevier, vol. 77(1), pages 55-63, September.
  100. Giuliano Lorenzoni & Adrian Pizzinga & Rodrigo Atherino & Cristiano Fernandes & Rosane Riera Freire, 2007. "On the Statistical Validation of Technical Analysis," Brazilian Review of Finance, Brazilian Society of Finance, vol. 5(1), pages 3-28.
  101. Günter Franke & Erik Lüders, 2005. "Return Predictability and Stock Market Crashes in a Simple Rational Expectations Model," CoFE Discussion Paper 05-05, Center of Finance and Econometrics, University of Konstanz.
  102. 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.
  103. Fang, Yue & Xu, Daming, 2003. "The predictability of asset returns: an approach combining technical analysis and time series forecasts," International Journal of Forecasting, Elsevier, vol. 19(3), pages 369-385.
  104. Lubnau, Thorben & Todorova, Neda, 2015. "Trading on mean-reversion in energy futures markets," Energy Economics, Elsevier, vol. 51(C), pages 312-319.
  105. 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.
  106. Kaucic, Massimiliano, 2010. "Investment using evolutionary learning methods and technical rules," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1717-1727, December.
  107. Xue-Zhong He & Kai Li, 2014. "Time Series Momentum and Market Stability," Research Paper Series 341, Quantitative Finance Research Centre, University of Technology, Sydney.
  108. Ko, Kuan-Cheng & Lin, Shinn-Juh & Su, Hsiang-Ju & Chang, Hsing-Hua, 2014. "Value investing and technical analysis in Taiwan stock market," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 14-36.
  109. Zolotoy, L., 2008. "Empirical essays on the information transfer between and the informational efficiency of stock markets," Other publications TiSEM 2a2652c6-1060-4622-8721-8, Tilburg University, School of Economics and Management.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.