IDEAS home Printed from https://ideas.repec.org/a/rfb/journl/v05y2013i2p089-115.html
   My bibliography  Save this article

How Reliable is the Moving Average Crossover Rule for an Investor on the Romanian Stock Market?

Author

Listed:
  • Dan Anghel

Abstract

Applying a technical analysis trading system based on the moving average crossover rule for companies listed on the Bucharest Stock Exchange does not produce significant profits, but leads to consistent excess returns and lower risk versus the benchmark buy and hold strategy for a potential investor during the 2001-2011 period. Comparing the results with the ones obtained for companies listed on two more developed markets, the United States and South Korea, a significant return surplus on the local market can be identified. The results point out that the local market is less efficient than the two foreign ones but also that the Romanian stock market is not weak form informational efficient.

Suggested Citation

  • Dan Anghel, 2013. "How Reliable is the Moving Average Crossover Rule for an Investor on the Romanian Stock Market?," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 5(2), pages 089-115, December.
    • Handle: RePEc:rfb:journl:v:05:y:2013:i:2:p:089-115
    as

    Download full text from publisher

    File URL: http://www.rfb.ase.ro/articole/ARTICOLI5.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
    2. Salih N. Neftci & Andrew J. Policano, 1984. "Can chartists outperform the market? market efficiency tests for “technical analysis”," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 4(4), pages 465-478, December.
    3. Joseph P. Romano & Michael Wolf, 2005. "Stepwise Multiple Testing as Formalized Data Snooping," Econometrica, Econometric Society, vol. 73(4), pages 1237-1282, July.
    4. repec:bla:jfinan:v:55:y:2000:i:4:p:1705-1770 is not listed on IDEAS
    5. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
    6. 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.
    7. Todea, Alexandru & Zoicas Ienciu, Adrian, 2011. "Technical Analysis and Stochastic Properties of Exchange Rate Movements: Empirical Evidence from the Romanian Currency Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 175-192, March.
    8. 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.
    9. Pele, Daniel Traian & Voineagu, Virgil, 2008. "Testing Market Efficiency Via Decomposition Of Stock Return. Application To Romanian Capital Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 5(3), pages 63-79, September.
    10. Dragota, Victor & Mitrica, Eugen, 2004. "Emergent capital markets' efficiency: The case of Romania," European Journal of Operational Research, Elsevier, vol. 155(2), pages 353-360, June.
    11. Robert J. Shiller, 2003. "From Efficient Markets Theory to Behavioral Finance," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 83-104, Winter.
    12. 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.
    13. Olson, Dennis, 2004. "Have trading rule profits in the currency markets declined over time?," Journal of Banking & Finance, Elsevier, vol. 28(1), pages 85-105, January.
    14. Gunasekarage, Abeyratna & Power, David M., 2001. "The profitability of moving average trading rules in South Asian stock markets," Emerging Markets Review, Elsevier, vol. 2(1), pages 17-33, March.
    15. Po-Hsuan Hsu & Chung-Ming Kuan, 2005. "Reexamining the Profitability of Technical Analysis with Data Snooping Checks," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 606-628.
    16. Victor Dragota & Mihai Caruntu & Andreea Stoian, 2008. "An Analysis of Closed-end Fund Puzzle for Emerging Capital Markets," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 10(10(527)), pages 53-60, October.
    17. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    18. Neftci, Salih N, 1991. "Naive Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of "Technical Analysis."," The Journal of Business, University of Chicago Press, vol. 64(4), pages 549-571, October.
    19. Zhu, Yingzi & Zhou, Guofu, 2009. "Technical analysis: An asset allocation perspective on the use of moving averages," Journal of Financial Economics, Elsevier, vol. 92(3), pages 519-544, June.
    20. Stephen Taylor, 2000. "Stock index and price dynamics in the UK and the US: new evidence from a trading rule and statistical analysis," The European Journal of Finance, Taylor & Francis Journals, vol. 6(1), pages 39-69.
    21. Taylor, Mark P. & Allen, Helen, 1992. "The use of technical analysis in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 11(3), pages 304-314, June.
    22. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    23. Allen, Franklin & Karjalainen, Risto, 1999. "Using genetic algorithms to find technical trading rules," Journal of Financial Economics, Elsevier, vol. 51(2), pages 245-271, February.
    24. Dragota, Victor & Stoian, Andreea & Pele, Daniel Traian & Mitrica, Eugen & Bensafta, Malik, 2009. "The Development of the Romanian Capital Market: Evidences on Information Efficiency," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 6(2), pages 147-160, June.
    25. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dan Gabriel Anghel, 2015. "Market Efficiency and Technical Analysis in Romania," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 6(2), pages 164-177, April.
    2. Andreea Săseanu & Hosney (Harry) Zurub & Gurgen Ohanyan & Natalia Bob, 2014. "The effects of IMF conditionality on Romanian economy: evidence from the Bucharest Stock Exchange," Management & Marketing, Economic Publishing House, vol. 9(3), Autumn.
    3. Victor Dragota & Dragos Stefan Oprea, 2014. "Informational Efficiency Tests on the Romanian Stock Market: A Review of the Literature," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 6(1), pages 015-028, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shynkevich, Andrei, 2012. "Performance of technical analysis in growth and small cap segments of the US equity market," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 193-208.
    2. Taylor, Mark & Hsu, Po-Hsuan, 2014. "Forty Years, Thirty Currencies and 21,000 Trading Rules: A Large-scale, Data-Snooping Robust Analysis of Technical Trading in t," CEPR Discussion Papers 10018, C.E.P.R. Discussion Papers.
    3. Isakov, Dusan & Marti, Didier, 2011. "Technical Analysis with a Long-Term Perspective: Trading Strategies and Market Timing Ability," FSES Working Papers 421, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    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. Hsu, Po-Hsuan & Taylor, Mark P. & Wang, Zigan, 2016. "Technical trading: Is it still beating the foreign exchange market?," Journal of International Economics, Elsevier, vol. 102(C), pages 188-208.
    6. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
    7. Yang, Junmin & Cao, Zhiguang & Han, Qiheng & Wang, Qiyu, 2019. "Tactical asset allocation on technical trading rules and data snooping," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    8. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos, 2021. "Trading the foreign exchange market with technical analysis and Bayesian Statistics," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 230-251.
    9. Kuang, P. & Schröder, M. & Wang, Q., 2014. "Illusory profitability of technical analysis in emerging foreign exchange markets," International Journal of Forecasting, Elsevier, vol. 30(2), pages 192-205.
    10. Shynkevich, Andrei, 2012. "Short-term predictability of equity returns along two style dimensions," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 675-685.
    11. Zarrabi, Nima & Snaith, Stuart & Coakley, Jerry, 2017. "FX technical trading rules can be profitable sometimes!," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 113-127.
    12. Hsu, Po-Hsuan & Taylor, Mark P. & Wang, Zigan & Li, Yan, 2024. "The out-of-sample performance of carry trades," Journal of International Money and Finance, Elsevier, vol. 143(C).
    13. Hung, Chiayu & Lai, Hung-Neng, 2022. "Information asymmetry and the profitability of technical analysis," Journal of Banking & Finance, Elsevier, vol. 134(C).
    14. Kuang, P. & Schröder, M. & Wang, Q., 2014. "Illusory profitability of technical analysis in emerging foreign exchange markets," International Journal of Forecasting, Elsevier, vol. 30(2), pages 192-205.
    15. Jin, Xiaoye, 2022. "Performance of intraday technical trading in China’s gold market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    16. Strobel, Marcus & Auer, Benjamin R., 2018. "Does the predictive power of variable moving average rules vanish over time and can we explain such tendencies?," International Review of Economics & Finance, Elsevier, vol. 53(C), pages 168-184.
    17. Hubert Dichtl, 2020. "Investing in the S&P 500 index: Can anything beat the buy‐and‐hold strategy?," Review of Financial Economics, John Wiley & Sons, vol. 38(2), pages 352-378, April.
    18. 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.
    19. Ioana-Andreea Boboc & Mihai-Cristian Dinică, 2013. "An Algorithm for Testing the Efficient Market Hypothesis," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-11, October.
    20. Psaradellis, Ioannis & Laws, Jason & Pantelous, Athanasios A. & Sermpinis, Georgios, 2023. "Technical analysis, spread trading, and data snooping control," International Journal of Forecasting, Elsevier, vol. 39(1), pages 178-191.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rfb:journl:v:05:y:2013:i:2:p:089-115. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tatu Lucian (email available below). General contact details of provider: https://edirc.repec.org/data/ffasero.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.