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Analysis of HF data on the WSE in the context of EMH

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  • Strawinski, Pawel
  • Slepaczuk, Robert

Abstract

This paper focuses on one of the heavily tested issue in the contemporary finance, i.e. efficient market hypothesis (EMH). However, we try to find the answers to some fundamental questions basing on the analysis of high frequency (HF) data from the Warsaw Stock Exchange (WSE). We estimate model on daily and 5-minute data for WIG20 index futures trying to verify daily and hourly effects. After implementing the base methodology for such testing, additionally we take into account the results of regression with weights, i.e. robust regression is used that assigns the higher weight the better behaved observations. Our results indicate that we observe the day of the week effect and hour of the day effect in polish data. What is more important is the existence of strong open jump effect for all days except Wednesday and positive day effect for Monday. Considering the hour of the day effect we observe positive, persistent and significant open jump effect and the end of session effect. Aforementioned results confirm our initial hypothesis that Polish stock market is not efficient in the information sense.

Suggested Citation

  • Strawinski, Pawel & Slepaczuk, Robert, 2008. "Analysis of HF data on the WSE in the context of EMH," MPRA Paper 9532, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:9532
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    1. Keim, Donald B & Stambaugh, Robert F, 1984. "A Further Investigation of the Weekend Effect in Stock Returns," Journal of Finance, American Finance Association, vol. 39(3), pages 819-835, July.
    2. Wood, Robert A & McInish, Thomas H & Ord, J Keith, 1985. "An Investigation of Transactions Data for NYSE Stocks," Journal of Finance, American Finance Association, vol. 40(3), pages 723-739, July.
    3. Josef Lakonishok, Seymour Smidt, 1988. "Are Seasonal Anomalies Real? A Ninety-Year Perspective," The Review of Financial Studies, Society for Financial Studies, vol. 1(4), pages 403-425.
    4. Fama, Eugene F & French, Kenneth R, 1988. "Permanent and Temporary Components of Stock Prices," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 246-273, April.
    5. Rozeff, Michael S. & Kinney, William Jr., 1976. "Capital market seasonality: The case of stock returns," Journal of Financial Economics, Elsevier, vol. 3(4), pages 379-402, October.
    6. Rogalski, Richard J, 1984. "A Further Investigation of the Weekend Effect in Stock Returns," Journal of Finance, American Finance Association, vol. 39(3), pages 835-837, July.
    7. Smirlock, Michael & Starks, Laura, 1986. "Day-of-the-week and intraday effects in stock returns," Journal of Financial Economics, Elsevier, vol. 17(1), pages 197-210, September.
    8. Sunil Poshakwale & Victor Murinde, 2001. "Modelling the volatility in East European emerging stock markets: evidence on Hungary and Poland," Applied Financial Economics, Taylor & Francis Journals, vol. 11(4), pages 445-456.
    9. Agrawal, Anup & Tandon, Kishore, 1994. "Anomalies or illusions? Evidence from stock markets in eighteen countries," Journal of International Money and Finance, Elsevier, vol. 13(1), pages 83-106, February.
    10. Kaushik Bhattacharya & Nityananda Sarkar & Debabrata Mukhopadhyay, 2003. "Stability of the day of the week effect in return and in volatility at the Indian capital market: a GARCH approach with proper mean specification," Applied Financial Economics, Taylor & Francis Journals, vol. 13(8), pages 553-563.
    11. Lakonishok, Josef & Maberly, Edwin, 1990. "The Weekend Effect: Trading Patterns of Individual and Institutional Investors," Journal of Finance, American Finance Association, vol. 45(1), pages 231-243, March.
    12. Lakonishok, Josef & Levi, Maurice, 1982. "Weekend Effects on Stock Returns: A Note," Journal of Finance, American Finance Association, vol. 37(3), pages 883-889, June.
    13. Harvey, Campbell R & Huang, Roger D, 1991. "Volatility in the Foreign Currency Futures Market," The Review of Financial Studies, Society for Financial Studies, vol. 4(3), pages 543-569.
    14. Ariel, Robert A., 1987. "A monthly effect in stock returns," Journal of Financial Economics, Elsevier, vol. 18(1), pages 161-174, March.
    15. R. Golinelli & R. Orsi, 2001. "Hungary and Poland," Working Papers 424, Dipartimento Scienze Economiche, Universita' di Bologna.
    16. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    17. Harris, Lawrence, 1986. "A transaction data study of weekly and intradaily patterns in stock returns," Journal of Financial Economics, Elsevier, vol. 16(1), pages 99-117, May.
    18. Poterba, James M. & Summers, Lawrence H., 1988. "Mean reversion in stock prices : Evidence and Implications," Journal of Financial Economics, Elsevier, vol. 22(1), pages 27-59, October.
    19. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
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    More about this item

    Keywords

    high-frequency financial data; ; robust analysis; pre-weighting; efficient market hypothesis; calendar effects; intra-day effects; the open jump effect; the end of session effect; emerging markets;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • 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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