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Testing Market Efficiency Via Decomposition Of Stock Return. Application To Romanian Capital Market

Author

Listed:
  • Pele, Daniel Traian

    (Bucharest University of Economics, Department of Statistics and Econometrics)

  • Voineagu, Virgil

    (Bucharest University of Economics, Department of Statistics and Econometrics, President of National Institute of Statistics)

Abstract

In this paper we are investigating the market efficiency using a model which decomposes the stock return into two components: a stochastic trend and a white noise component. This model is tested for the Romanian Capital Market, considering the time series of BET (Bucharest Exchange Trade) Index. The conclusion is that for our data sample we cannot reject the efficient market hypothesis for Romanian Capital Market. Classificaefficient market hypothesis, random walk, stochastic trend, ARIMA models, Romanian Capital Market, BET.tion-JEL: C42, G14

Suggested Citation

  • 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.
    • Handle: RePEc:rjr:romjef:v:5:y:2008:i:3:p:63-79
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    References listed on IDEAS

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    Cited by:

    1. Erdas Mehmet Levent, 2019. "Validity of Weak-Form Market Efficiency in Central and Eastern European Countries (CEECs): Evidence from Linear and Nonlinear Unit Root Tests," Review of Economic Perspectives, Sciendo, vol. 19(4), pages 399-428, December.
    2. Amin Aminimehr & Ali Raoofi & Akbar Aminimehr & Amirhossein Aminimehr, 2022. "A Comprehensive Study of Market Prediction from Efficient Market Hypothesis up to Late Intelligent Market Prediction Approaches," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 781-815, August.
    3. Victor Dragotă & Elena Ţilică, 2014. "Market efficiency of the Post Communist East European stock markets," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(2), pages 307-337, June.
    4. Panait, Iulian & Diaconescu, Tiberiu, 2012. "Particularități ale aplicării teoriei moderne a portofoliului in cazul acțiunilor listate la Bursa de Valori București [Particularities of applying Modern Portfolio Theory on the Romanian capital m," MPRA Paper 44248, University Library of Munich, Germany.
    5. Valentin BURCA, 2014. "Implications of IFRS Adoption on Balance-Sheet vs Income Statement Figures," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 3, pages 33-42.
    6. Naimat U Khan & Sajjad Khan, 2016. "Weak Form of Efficient Market Hypothesis: Evidence from Pakistan," Business & Economic Review, Institute of Management Sciences, Peshawar, Pakistan, vol. 8(SE), pages 1-18, March.
    7. Bogdan Dima & Laura Raisa MiloÅŸ, 2009. "Testing The Efficiency Market Hypothesis For The Romanian Stock Market," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 1(11), pages 1-41.
    8. Victor DRAGOTA & Carmen LIPARA & Radu CIOBANU, 2013. "Agency Problems and Synergistic Effects in Romania: The Determinants of the Control Premium," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(2), pages 197-219, May.
    9. Viorica CHIRILA & Ciprian CHIRILA, 2015. "The Steel European Stock Market Efficiency," CES Working Papers, Centre for European Studies, Alexandru Ioan Cuza University, vol. 7(4), pages 873-880, December.
    10. 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.
    11. Camelia Oprean, 2012. "Testing the financial market informational efficiency in emerging states," Review of Applied Socio-Economic Research, Pro Global Science Association, vol. 4(2), pages 181-190, Decembre.
    12. Ferreira, Paulo, 2018. "Long-range dependencies of Eastern European stock markets: A dynamic detrended analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 454-470.
    13. Cristiana Tudor, 2021. "Investors’ Trading Activity and Information Asymmetry: Evidence from the Romanian Stock Market," Risks, MDPI, vol. 9(8), pages 1-19, August.
    14. Mihaela Ionascu & Ion Ionascu & Marian Sacarin & Mihaela Minu, 2018. "Benefits of global financial reporting models for developing markets: The case of Romania," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-24, November.
    15. Drags Mînjina & Petre Brezeanu, 2013. "Testing the Efficient Markets Hypothesis on the Romanian Capital Market," Finante - provocarile viitorului (Finance - Challenges of the Future), University of Craiova, Faculty of Economics and Business Administration, vol. 1(15), pages 151-158, December.
    16. 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.
    17. CHIRILA, Viorica & CHIRILA, Ciprian, 2014. "Testing Stock Markets’ Integration From Central And Eastern European Countries Within Euro Zone," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 18(3), pages 76-88.
    18. Deniz Erer & Elif Erer & Selim Güngör, 2023. "The aggregate and sectoral time-varying market efficiency during crisis periods in Turkey: a comparative analysis with COVID-19 outbreak and the global financial crisis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-25, December.

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    More about this item

    JEL classification:

    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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