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A Non-Random Walk down Canary Wharf

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  • Canegrati, Emanuele

Abstract

In this paper I perform a panel data analysis to evaluate whether �- nancial technical indicators are able to predict stock market returns. By using a panel of 40 stocks taken from the Financial Times Stock Exchange (FTSE) observed in 2004, I test the ability of 75 amongst the most famous technical indicators used by traders to predict next-day returns. Surpris- ingly, results are robust in demonstrating that many of these are good predictors, supporting the validity of the technical analysis.

Suggested Citation

  • Canegrati, Emanuele, 2008. "A Non-Random Walk down Canary Wharf," MPRA Paper 9871, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:9871
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    File URL: https://mpra.ub.uni-muenchen.de/9871/1/MPRA_paper_9871.pdf
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    References listed on IDEAS

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    Cited by:

    1. Bekiros, Stelios D., 2015. "Heuristic learning in intraday trading under uncertainty," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 34-49.

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    More about this item

    Keywords

    technical analysis; random walk hypothesis; econometrics finance;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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