IDEAS home Printed from https://ideas.repec.org/b/zbw/tuklff/16.html
   My bibliography  Save this book

Fortgeschrittene technische Indikatoren am Aktienmarkt: Eine empirische Analyse

Author

Listed:
  • Hornbach, Christian
  • Hellenkamp, André

Abstract

No abstract is available for this item.

Suggested Citation

  • Hornbach, Christian & Hellenkamp, André, 2011. "Fortgeschrittene technische Indikatoren am Aktienmarkt: Eine empirische Analyse," Studien zum Finanz-, Bank- und Versicherungsmanagement, Technische Universität Kaiserslautern, Lehrstuhl für Finanzdienstleistungen und Finanzmanagement, volume 16, number 16.
    • Handle: RePEc:zbw:tuklff:16
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/107032/1/LFF-Studie_Band_16.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Avanidhar Subrahmanyam, 2008. "Behavioural Finance: A Review and Synthesis," European Financial Management, European Financial Management Association, vol. 14(1), pages 12-29, January.
    2. Gili Yen & Cheng-few Lee, 2008. "Efficient Market Hypothesis (EMH): Past, Present and Future," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 11(02), pages 305-329.
    3. 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.
    4. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    5. Esther Ruiz & Lorenzo Pascual, 2002. "Bootstrapping Financial Time Series," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 271-300, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. Hakan Er & Adnan Hushmat, 2017. "The application of technical trading rules developed from spot market prices on futures market prices using CAPM," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 7(3), pages 313-353, December.
    4. Fong, Tom Pak Wing & Wu, Shui Tang, 2020. "Predictability in sovereign bond returns using technical trading rules: Do developed and emerging markets differ?," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    5. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
    6. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 131-157.
    7. Yamamoto, Ryuichi, 2012. "Intraday technical analysis of individual stocks on the Tokyo Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 3033-3047.
    8. 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.
    9. 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.
    10. Alexeev, Vitali & Tapon, Francis, 2011. "Testing weak form efficiency on the Toronto Stock Exchange," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 661-691, September.
    11. Frömmel, Michael & Lampaert, Kevin, 2016. "Does frequency matter for intraday technical trading?," Finance Research Letters, Elsevier, vol. 18(C), pages 177-183.
    12. Anghel, Dan Gabriel, 2021. "Data Snooping Bias in Tests of the Relative Performance of Multiple Forecasting Models," Journal of Banking & Finance, Elsevier, vol. 126(C).
    13. Urquhart, Andrew & Zhang, Hanxiong, 2019. "The performance of technical trading rules in Socially Responsible Investments," International Review of Economics & Finance, Elsevier, vol. 63(C), pages 397-411.
    14. Alhashel, Bader S. & Almudhaf, Fahad W. & Hansz, J. Andrew, 2018. "Can technical analysis generate superior returns in securitized property markets? Evidence from East Asia markets," Pacific-Basin Finance Journal, Elsevier, vol. 47(C), pages 92-108.
    15. Pedro Godinho, 2012. "Can abnormal returns be earned on bandwidth-bounded currencies? Evidence from a genetic algorithm," Economic Issues Journal Articles, Economic Issues, vol. 17(1), pages 1-26, March.
    16. Taylor, Nick, 2014. "The rise and fall of technical trading rule success," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 286-302.
    17. Shynkevich, Andrei, 2012. "Short-term predictability of equity returns along two style dimensions," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 675-685.
    18. Kearney, Fearghal & Cummins, Mark & Murphy, Finbarr, 2014. "Outperformance in exchange-traded fund pricing deviations: Generalized control of data snooping bias," Journal of Financial Markets, Elsevier, vol. 19(C), pages 86-109.
    19. Valeriy Zakamulin, 2014. "The real-life performance of market timing with moving average and time-series momentum rules," Journal of Asset Management, Palgrave Macmillan, vol. 15(4), pages 261-278, August.
    20. Xiaoye Jin, 2022. "Evaluating the predictive power of intraday technical trading in China's crude oil market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1416-1432, November.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:tuklff:16. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/dekaide.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.