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Towards the fundamentals of technical analysis: analysing the information content of High, Low and Close prices

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  • Fiess, Norbert M
  • MacDonald, Ronald

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  • Fiess, Norbert M & MacDonald, Ronald, 2002. "Towards the fundamentals of technical analysis: analysing the information content of High, Low and Close prices," Economic Modelling, Elsevier, vol. 19(3), pages 353-374, May.
    • Handle: RePEc:eee:ecmode:v:19:y:2002:i:3:p:353-374
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    11. Torben G. Andersen & Tim Bollerslev, 1998. "Deutsche Mark-Dollar Volatility: Intraday Activity Patterns, Macroeconomic Announcements, and Longer Run Dependencies," Journal of Finance, American Finance Association, vol. 53(1), pages 219-265, February.
    12. Blume, Lawrence & Easley, David & O'Hara, Maureen, 1994. "Market Statistics and Technical Analysis: The Role of Volume," Journal of Finance, American Finance Association, vol. 49(1), pages 153-181, March.
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    Cited by:

    1. Lyudmila G. Egorova, 2014. "Agent-Based Models of Stock Exchange: Analysis via Computational Simulation," Springer Optimization and Its Applications, in: Valery A. Kalyagin & Panos M. Pardalos & Themistocles M. Rassias (ed.), Network Models in Economics and Finance, edition 127, pages 147-158, Springer.
    2. 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).
    3. Igor Kliakhandler, 2007. "Execution edge of pit traders and intraday price ranges of soft commodities," Applied Financial Economics, Taylor & Francis Journals, vol. 17(5), pages 343-350.
    4. Baruník, Jozef & Dvořáková, Sylvie, 2015. "An empirical model of fractionally cointegrated daily high and low stock market prices," Economic Modelling, Elsevier, vol. 45(C), pages 193-206.
    5. 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.
    6. Chong, Terence Tai Leung & Tang, Alan Tsz Chung & Chan, Kwun Ho, 2016. "An Empirical Comparison of Fast and Slow Stochastics," MPRA Paper 80559, University Library of Munich, Germany.
    7. Molnár, Peter, 2012. "Properties of range-based volatility estimators," International Review of Financial Analysis, Elsevier, vol. 23(C), pages 20-29.
    8. Gehrig, Thomas & Menkhoff, Lukas, 2003. "Technical Analysis in Foreign Exchange - The Workhorse Gains Further Ground," Hannover Economic Papers (HEP) dp-278, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    9. Mazza, Paolo, 2015. "Price dynamics and market liquidity: An intraday event study on Euronext," The Quarterly Review of Economics and Finance, Elsevier, vol. 56(C), pages 139-153.
    10. Javier Arroyo & Rosa Espínola & Carlos Maté, 2011. "Different Approaches to Forecast Interval Time Series: A Comparison in Finance," Computational Economics, Springer;Society for Computational Economics, vol. 37(2), pages 169-191, February.
    11. Mazza, Paolo & Petitjean, Mikael, 2016. "On the usefulness of intraday price ranges to gauge liquidity in cap-based portfolios," Economic Modelling, Elsevier, vol. 54(C), pages 67-81.
    12. Yaya, OlaOluwa S & Gil-Alana, Luis A., 2018. "High and Low Intraday Commodity Prices: A Fractional Integration and Cointegration Approach," MPRA Paper 90518, University Library of Munich, Germany.
    13. Wenyang Huang & Huiwen Wang & Shanshan Wang, 2021. "Dimension reduction of open-high-low-close data in candlestick chart based on pseudo-PCA," Papers 2103.16908, arXiv.org.
    14. Thomas Gehrig & Lukas Menkhoff, 2006. "Extended evidence on the use of technical analysis in foreign exchange," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 11(4), pages 327-338.
    15. Huang, Wenyang & Gao, Tianxiao & Hao, Yun & Wang, Xiuqing, 2023. "Transformer-based forecasting for intraday trading in the Shanghai crude oil market: Analyzing open-high-low-close prices," Energy Economics, Elsevier, vol. 127(PA).
    16. Díaz-Mendoza, Ana-Carmen & Pardo, Angel, 2020. "Holidays, weekends and range-based volatility," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    17. 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.
    18. 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.
    19. Leandro Maciel, 2020. "Technical analysis based on high and low stock prices forecasts: evidence for Brazil using a fractionally cointegrated VAR model," Empirical Economics, Springer, vol. 58(4), pages 1513-1540, April.
    20. 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.
    21. Heinz, Adrian & Jamaloodeen, Mohamed & Saxena, Atul & Pollacia, Lissa, 2021. "Bullish and Bearish Engulfing Japanese Candlestick patterns: A statistical analysis on the S&P 500 index," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 221-244.
    22. BEN OMRANE, Walid & VAN OPPEN, Hervé, 2004. "The predictive success and profitability of chart patterns in the Euro/Dollar foreign exchange market," LIDAM Discussion Papers CORE 2004035, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    23. Caporale, Guglielmo Maria & Gil-Alana, Luis A. & Poza, Carlos, 2020. "High and low prices and the range in the European stock markets: A long-memory approach," Research in International Business and Finance, Elsevier, vol. 52(C).
    24. Paulo M.M. Rodrigues & Nazarii Salish, 2011. "Modeling and Forecasting Interval Time Series with Threshold Models: An Application to S&P500 Index Returns," Working Papers w201128, Banco de Portugal, Economics and Research Department.
    25. Huiwen Wang & Wenyang Huang & Shanshan Wang, 2021. "Forecasting open-high-low-close data contained in candlestick chart," Papers 2104.00581, arXiv.org.

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