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Intraday Market Efficiency for a Typical Central and Eastern European Stock Market: The Case of Romania

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  • Dan Gabriel ANGHEL

    (Department of Money and Banking, Bucharest University of Economic Studies)

Abstract

Investors increasingly focus on high frequency data for fine-tuning portfolio management decisions in developed, emerging and frontier markets alike. However, the behavior of intraday price movements in the Central and Eastern European stock markets is insufficiently understood. We obtain a large sample of intraday prices in a typical Central and Eastern European stock market and we thoroughly investigate it for dependencies and economic profit opportunities. We determine that intraday price movements present important deviations from a random walk. Despite this, we find that investors are generally unable to use the dependencies imbedded in the price movements to gain economic profits when using trading strategies derived from three popular technical analysis indicators. Overall, we cannot reject the Efficient Market Hypothesis for intraday price movements in Romania. This implies that, because of the existing market frictions, trading on high frequency data is not feasible in the stock market of Romania, at least when using popular technical analysis indicators.

Suggested Citation

  • Dan Gabriel ANGHEL, 2017. "Intraday Market Efficiency for a Typical Central and Eastern European Stock Market: The Case of Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 88-109, September.
    • Handle: RePEc:rjr:romjef:v::y:2017:i:3:p:88-109
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    Cited by:

    1. Dan Gabriel ANGHEL & Elena Valentina ŢILICĂ & Victor DRAGOTĂ, 2020. "Intraday Patterns in Returns on the Romanian and Bulgarian Stock Markets," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 92-114, July.
    2. Tihana Škrinjarić & Zrinka Orlović, 2020. "Economic Policy Uncertainty and Stock Market Spillovers: Case of Selected CEE Markets," Mathematics, MDPI, vol. 8(7), pages 1-33, July.
    3. Claudiu Tiberiu Albulescu & Aviral Kumar Tiwari & Phouphet Kyophilavong, 2021. "Nonlinearities and Chaos: A New Analysis of CEE Stock Markets," Mathematics, MDPI, vol. 9(7), pages 1-13, March.
    4. Dan Gabriel Anghel, 2020. "What Can Machine Learning Tell Us About Intraday Price Patterns in a Frontier Stock Market?," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 11(5), pages 205-220, October.

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    More about this item

    Keywords

    Bootstrap; Central and Eastern Europe; Efficient Market Hypothesis; Hour of the Day Effect; Random Walk; Romanian Stock Market; Superior Predictive Ability; Technical Analysis;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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