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Market Efficiency of Baltic Stock Markets: A Fractional Integration Approach

Author

Listed:
  • Luis A. Gil-Alana

    (University of Navarra, Faculty of Economics and ICS (NCID), Spain)

  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Olanrewaju I. Shittu

    (Department of Statistics, University of Ibadan, Ibadan, Nigeria)

  • OlaOluwa S. Yaya

    (Department of Statistics, University of Ibadan, Ibadan, Nigeria)

Abstract

We investigate financial market efficiency in the time series of four daily Baltic stock market indices namely Baltic Benchmark Gross Index (OMXBBGI), all share index of Tallin-Lithuanian (OMXT), all share index of Riga (OMXR) and all share index of Vilnius (OMXV), based on historical data from 1 January, 2000 to 22 January 2016. We use fractional integration methods to test the hypothesis of efficiency. Realizing that long-memory estimation could be spurious in the presence of structural breaks, we identify bull and bear market phases from each of the time series. Applying the fractional integration approach, we find that the random walk hypothesis of market efficiency is generally not rejected in the overall and at two bull and one bear sub-samples of the four Baltic stock indices. The volatility at the bear markets of these stocks persists more than the volatility at the bull markets. Our results therefore provide evidence of weak form of efficiency in the Baltic stock markets, with some exceptions.

Suggested Citation

  • Luis A. Gil-Alana & Rangan Gupta & Olanrewaju I. Shittu & OlaOluwa S. Yaya, 2016. "Market Efficiency of Baltic Stock Markets: A Fractional Integration Approach," Working Papers 201617, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201617
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    More about this item

    Keywords

    Baltic stocks; Bull and bear phases; Efficient market hypothesis; Fractional cointegration; Fractional integration; Volatility;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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