IDEAS home Printed from https://ideas.repec.org/r/eee/jbfina/v30y2006i8p2303-2323.html
   My bibliography  Save this item

Candlestick technical trading strategies: Can they create value for investors?

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. 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.
  2. Day, Min-Yuh & Ni, Yensen & Huang, Paoyu, 2019. "Trading as sharp movements in oil prices and technical trading signals emitted with big data concerns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 349-372.
  3. Lu, Tsung-Hsun & Chen, Yi-Chi & Hsu, Yu-Chin, 2015. "Trend definition or holding strategy: What determines the profitability of candlestick charting?," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 172-183.
  4. Huang, Wenyang & Wang, Huiwen & Qin, Haotong & Wei, Yigang & Chevallier, Julien, 2022. "Convolutional neural network forecasting of European Union allowances futures using a novel unconstrained transformation method," Energy Economics, Elsevier, vol. 110(C).
  5. Chiang, Mi-Hsiu & Chiu, Hsin-Yu & Kuo, Wei-Yu, 2021. "Predictive ability of similarity-based futures trading strategies," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
  6. 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.
  7. Shangkun Deng & Zhihao Su & Yanmei Ren & Haoran Yu & Yingke Zhu & Chenyang Wei, 2022. "Can Japanese Candlestick Patterns be Profitable on the Component Stocks of the SSE50 Index?," SAGE Open, , vol. 12(3), pages 21582440221, August.
  8. Tsung‐Hsun Lu & Yung‐Ming Shiu & Tsung‐Chi Liu, 2012. "Profitable candlestick trading strategies—The evidence from a new perspective," Review of Financial Economics, John Wiley & Sons, vol. 21(2), pages 63-68, April.
  9. Jun-Hao Chen & Yun-Cheng Tsai, 2020. "Encoding candlesticks as images for pattern classification using convolutional neural networks," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-19, December.
  10. Krzysztof Piasecki & Anna Łyczkowska-Hanćkowiak, 2019. "Representation of Japanese Candlesticks by Oriented Fuzzy Numbers," Econometrics, MDPI, vol. 8(1), pages 1-24, December.
  11. José A. Roldán-Casas & Mª B. García-Moreno García, 2022. "A procedure for testing the hypothesis of weak efficiency in financial markets: a Monte Carlo simulation," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1289-1327, December.
  12. Piyapas Tharavanij & Vasan Siraprapasiri & Kittichai Rajchamaha, 2017. "Profitability of Candlestick Charting Patterns in the Stock Exchange of Thailand," SAGE Open, , vol. 7(4), pages 21582440177, October.
  13. A. Olasolo & M. A. Pérez & V. Ruiz, 2016. "Active investment strategies in the Spanish futures market: a solution to avoid data snooping bias," Applied Economics Letters, Taylor & Francis Journals, vol. 23(9), pages 609-613, June.
  14. Huadong Chang & Guozhi An, 2019. "Will History Repeat Itself? Empirical Research on A-Share Candlesticks in China Based on Matching Method," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(5), pages 1-8.
  15. Kim man Lui & Terence T. L. Chong, 2013. "Do Technical Analysts Outperform Novice Traders: Experimental Evidence," Economics Bulletin, AccessEcon, vol. 33(4), pages 3080-3087.
  16. Tsung-Hsun Lu & Yung-Ming Shiu, 2016. "Can 1-day candlestick patterns be profitable on the 30 component stocks of the DJIA?," Applied Economics, Taylor & Francis Journals, vol. 48(35), pages 3345-3354, July.
  17. Juan Benjamín Duarte Duarte & Juan Manuel Mascare?nas Pérez-Iñigo, 2014. "Comprobación de la eficiencia débil en los principales mercados financieros latinoamericanos," Estudios Gerenciales, Universidad Icesi, November.
  18. Manhwa Wu & Paoyu Huang & Yensen Ni, 2017. "Investing strategies as continuous rising (falling) share prices released," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(4), pages 763-773, October.
  19. Lu, Tsung-Hsun & Shiu, Yung-Ming & Liu, Tsung-Chi, 2012. "Profitable candlestick trading strategies—The evidence from a new perspective," Review of Financial Economics, Elsevier, vol. 21(2), pages 63-68.
  20. 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.
  21. 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.
  22. Shynkevich, Andrei, 2016. "Predictability in bond returns using technical trading rules," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 55-69.
  23. Andreea Röthig & Andreas Röthig & Carl Chiarella, 2015. "On Candlestick-based Trading Rules Profitability Analysis via Parametric Bootstraps and Multivariate Pair-Copula based Models," Research Paper Series 362, Quantitative Finance Research Centre, University of Technology, Sydney.
  24. Ni, Yensen & Wu, Manhwa & Day, Min-Yuh & Huang, Paoyu, 2020. "Do sharp movements in oil prices matter for stock markets?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
  25. Ni, Yensen & Day, Min-Yuh & Huang, Paoyu & Yu, Shang-Ru, 2020. "The profitability of Bollinger Bands: Evidence from the constituent stocks of Taiwan 50," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
  26. Ni, Yensen & Cheng, Yirung & Huang, Paoyu & Day, Min-Yuh, 2018. "Trading strategies in terms of continuous rising (falling) prices or continuous bullish (bearish) candlesticks emitted," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 188-204.
  27. Chu, Jeffrey & Chan, Stephen & Zhang, Yuanyuan, 2020. "High frequency momentum trading with cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 52(C).
  28. Gil Cohen, 2022. "Artificial Intelligence in Trading the Financial Markets," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(1), pages 101-110.
  29. Gil Cohen, 2021. "Optimizing candlesticks patterns for Bitcoin's trading systems," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 1155-1167, October.
  30. Kurita, Takamitsu, 2014. "Dynamic characteristics of the daily yen–dollar exchange rate," Research in International Business and Finance, Elsevier, vol. 30(C), pages 72-82.
  31. Yensen Ni & Min-Yuh Day & Paoyu Huang, 2020. "Trading stocks following sharp movements in the USDX, GBP/USD, and USD/CNY," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-17, December.
  32. Juan Benjamín Duarte Duarte & Juan Manuel Mascareñas Pérez-Iñigo, 2014. "¿Han sido los mercados bursátiles eficientes informacionalmente?," Apuntes del Cenes, Universidad Pedagógica y Tecnológica de Colombia, June.
  33. Yensen Ni & Min-Yuh Day & Yirung Cheng & Paoyu Huang, 2022. "Can investors profit by utilizing technical trading strategies? Evidence from the Korean and Chinese stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
  34. Chiu, Hsin-Yu & Chiang, Mi-Hsiu & Kuo, Wei-Yu, 2018. "Predicative Ability of Similarity-based Futures Trading Strategies," IRTG 1792 Discussion Papers 2018-045, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  35. 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.
  36. Andreas Krause, 2009. "Evaluating the performance of adapting trading strategies with different memory lengths," Papers 0901.0447, arXiv.org.
  37. 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.
  38. Detollenaere, Benoit & Mazza, Paolo, 2014. "Do Japanese candlesticks help solve the trader’s dilemma?," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 386-395.
  39. Paolo Mazza & Mikael Petitjean, 2019. "Testing the effect of technical analysis on market quality and order book dynamics," Applied Economics, Taylor & Francis Journals, vol. 51(18), pages 1947-1976, April.
  40. Tsung-Hsun Lu & Yung-Ming Shiu, 2012. "Tests for Two-Day Candlestick Patterns in the Emerging Equity Market of Taiwan," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 48(0), pages 41-57, January.
  41. Pawel Dlotko & Wanling Qiu & Simon Rudkin, 2022. "Topological Data Analysis Ball Mapper for Finance," Papers 2206.03622, arXiv.org.
  42. Yaohu Lin & Shancun Liu & Haijun Yang & Harris Wu & Bingbing Jiang, 2021. "Improving stock trading decisions based on pattern recognition using machine learning technology," PLOS ONE, Public Library of Science, vol. 16(8), pages 1-25, August.
  43. Stolarczyk, Paulina & Wielechowski, Michał, 2020. "Disabled People On The Labour Market In Poland – Focus On Rural Areas Of The Masovian Voivodship," Roczniki (Annals), Polish Association of Agricultural Economists and Agribusiness - Stowarzyszenie Ekonomistow Rolnictwa e Agrobiznesu (SERiA), vol. 2020(1).
  44. Gil Cohen, 2020. "Best Candlesticks Pattern to Trade Stocks," International Journal of Economics and Financial Issues, Econjournals, vol. 10(2), pages 256-261.
  45. 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.
  46. 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.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.