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Optimal lengths of moving averages for the MACD oscillator for companies listed on the Warsaw Stock Exchange

Author

Listed:
  • Krzysztof Borowski

    (Warsaw School of Economics, Collegium of Finance and Management)

  • Izabela Pruchnicka-Grabias

    (Warsaw School of Economics, Collegium of Socio-Economics)

Abstract

The aim of the paper is to find optimal exponential moving averages for the main technical analysis oscillator MACD (Moving Average Convergence Divergence) which trigger buy and sell signals for companies from the WIG20 index, the mWIG40 and the sWIG80 index, listed on the Warsaw Stock Exchange. The analysis was conducted on the basis of data collected from 17 November 2000 to 31 December 2018, i.e. from the day when the WARSET system was introduced. The optimization was done with the method based on rates of return because they influence the final investment result. It is the first research of this kind on the Polish financial market. It shows that each of the examined companies has its own lengths of moving averages which optimize rates of return, however, for some enterprises these values may be the same. Many research papers on technical analysis apply standard lengths for averages used in MACD. The authors of the present paper find out that investors should not follow them automatically, but rather look for optimal values for each market and each company. Such an opinion stands in sync with research literature which proves a varying efficiency of technical analysis tools, depending on the market development level, its transaction volume or its liquidity.

Suggested Citation

  • Krzysztof Borowski & Izabela Pruchnicka-Grabias, 2019. "Optimal lengths of moving averages for the MACD oscillator for companies listed on the Warsaw Stock Exchange," Bank i Kredyt, Narodowy Bank Polski, vol. 50(5), pages 457-478.
    • Handle: RePEc:nbp:nbpbik:v:50:y:2019:i:5:p:457-478
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    References listed on IDEAS

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    1. Alessio Emanuele Biondo & Alessandro Pluchino & Andrea Rapisarda & Dirk Helbing, 2013. "Are Random Trading Strategies More Successful than Technical Ones?," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-13, July.
    2. Ryan Sullivan & Allan Timmermann & Halbert White, 1999. "Data‐Snooping, Technical Trading Rule Performance, and the Bootstrap," Journal of Finance, American Finance Association, vol. 54(5), pages 1647-1691, October.
    3. R. Rosillo & D. de la Fuente & J. A. L. Brugos, 2013. "Technical analysis and the Spanish stock exchange: testing the RSI, MACD, momentum and stochastic rules using Spanish market companies," Applied Economics, Taylor & Francis Journals, vol. 45(12), pages 1541-1550, April.
    4. 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.
    5. Ming-Ming, Lai & Siok-Hwa, Lau, 2006. "The profitability of the simple moving averages and trading range breakout in the Asian stock markets," Journal of Asian Economics, Elsevier, vol. 17(1), pages 144-170, February.
    6. Alexandru Todea & Adrian Zoicas-Ienciu & Angela-Maria Filip, 2009. "Profitability of the Moving Average Strategy and the Episodic Dependencies: Empirical Evidence from European Stock," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 63-72.
    7. 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.
    8. Hsu, Po-Hsuan & Hsu, Yu-Chin & Kuan, Chung-Ming, 2010. "Testing the predictive ability of technical analysis using a new stepwise test without data snooping bias," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 471-484, June.
    9. Wing-Keung Wong & Meher Manzur & Boon-Kiat Chew, 2003. "How rewarding is technical analysis? Evidence from Singapore stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 13(7), pages 543-551.
    10. Massoud Metghalchi & Juri Marcucci & Yung-Ho Chang, 2012. "Are moving average trading rules profitable? Evidence from the European stock markets," Applied Economics, Taylor & Francis Journals, vol. 44(12), pages 1539-1559, April.
    11. A. E. Biondo & A. Pluchino & A. Rapisarda & D. Helbing, 2013. "Are random trading strategies more successful than technical ones?," Papers 1303.4351, arXiv.org, revised Jul 2013.
    12. Taylor, Nick, 2014. "The rise and fall of technical trading rule success," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 286-302.
    13. 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.
    14. Terence Tai-Leung Chong & Wing-Kam Ng, 2008. "Technical analysis and the London stock exchange: testing the MACD and RSI rules using the FT30," Applied Economics Letters, Taylor & Francis Journals, vol. 15(14), pages 1111-1114.
    15. Suzanne Fifield & David Power & C. Donald Sinclair, 2005. "An analysis of trading strategies in eleven European stock markets," The European Journal of Finance, Taylor & Francis Journals, vol. 11(6), pages 531-548.
    16. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
    17. Dejan Eric & Goran Andjelic & Srdjan Redzepagic, 2009. "Application of MACD and RVI indicators as functions of investment strategy optimization on the financial market," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 27(1), pages 171-196.
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    More about this item

    Keywords

    technical analysis; MACD; moving average;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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