IDEAS home Printed from https://ideas.repec.org/a/blg/reveco/v69y2017i1p22-28.html
   My bibliography  Save this article

The Development And The Current Status Of The Capital Market Hypotheses: A Few Benchmarks

Author

Listed:
  • BRATIAN Vasile

    (Lucian Blaga University of Sibiu, Romania)

  • BUCUR Amelia

    (Lucian Blaga University of Sibiu, Romania)

Abstract

The capital markets are in continuous development and change, which raises the question whether the market hypotheses are still relevant and statistically valid in the present times. Thus, this paper presents an analysis of the development and the current status of the capital market hypotheses. Moreover, the paper presents a summary of the tests used to assess form efficiency in a developing market, and of the research methods used to detect chaos in a financial time series.

Suggested Citation

  • BRATIAN Vasile & BUCUR Amelia, 2017. "The Development And The Current Status Of The Capital Market Hypotheses: A Few Benchmarks," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 69(1), pages 22-28, April.
    • Handle: RePEc:blg:reveco:v:69:y:2017:i:1:p:22-28
    as

    Download full text from publisher

    File URL: http://economice.ulbsibiu.ro/revista.economica/archive/69102bratian&bucur.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Vasile Radu Bratian & Claudiu Ilie Opreana, 2010. "Testing The Hypothesis Of An Efficient Market In Terms Of Information – The Case Of The Capital Market In Romania During Recession," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 5(3), pages 79-106, December.
    2. A. Corcos & J-P Eckmann & A. Malaspinas & Y. Malevergne & D. Sornette, 2002. "Imitation and contrarian behaviour: hyperbolic bubbles, crashes and chaos," Quantitative Finance, Taylor & Francis Journals, vol. 2(4), pages 264-281.
    3. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    4. Alexandru Todea & Adrian Zoicas-Ienciu, 2008. "Episodic dependencies in Central and Eastern Europe stock markets," Applied Economics Letters, Taylor & Francis Journals, vol. 15(14), pages 1123-1126.
    5. Kyrtsou, Catherine & Terraza, Michel, 2002. "Stochastic chaos or ARCH effects in stock series?: A comparative study," International Review of Financial Analysis, Elsevier, vol. 11(4), pages 407-431.
    6. Chen, Shu-Heng & Lux, Thomas & Marchesi, Michele, 2001. "Testing for non-linear structure in an artificial financial market," Journal of Economic Behavior & Organization, Elsevier, vol. 46(3), pages 327-342, November.
    Full references (including those not matched with items on IDEAS)

    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. Constantinos VORLOW & Antonios ANTONIOU & Catherine KYRTSOU, 2004. "Surrogate Data Analysis and Stochastic Chaotic Modelling: Application to Stock Exchange Returns Series," Computing in Economics and Finance 2004 27, Society for Computational Economics.
    2. Catherine Kyrtsou & Michel Terraza, 2003. "Is it Possible to Study Chaotic and ARCH Behaviour Jointly? Application of a Noisy Mackey–Glass Equation with Heteroskedastic Errors to the Paris Stock Exchange Returns Series," Computational Economics, Springer;Society for Computational Economics, vol. 21(3), pages 257-276, June.
    3. Catherine Kyrtsou & Michel Terraza, 2010. "Seasonal Mackey–Glass–GARCH process and short-term dynamics," Empirical Economics, Springer, vol. 38(2), pages 325-345, April.
    4. Todea, Alexandru & Pleşoianu, Anita, 2013. "The influence of foreign portfolio investment on informational efficiency: Empirical evidence from Central and Eastern European stock markets," Economic Modelling, Elsevier, vol. 33(C), pages 34-41.
    5. Catherine Kyrtsou & Michel Terraza, 2000. "Is It Possible To Study Jointly Chaotic And Arch Behaviour? Application Of A Noisy Mackey-Glass Equation With Heteroskedastic Errors To The Paris Stock Exchange," Computing in Economics and Finance 2000 Z226, Society for Computational Economics.
    6. İşcanoğlu-Çekiç, Ayşegül & Gülteki̇n, Havva, 2019. "Are cross-correlations between Turkish Stock Exchange and three major country indices multifractal or monofractal?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 978-990.
    7. Lavička, Hynek & Kracík, Jiří, 2020. "Fluctuation analysis of electric power loads in Europe: Correlation multifractality vs. Distribution function multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    8. L. Telesca & T. Matcharashvili & T. Chelidze & N. Zhukova & Z. Javakhishvili, 2015. "Investigating the dynamical features of the time distribution of the reservoir-induced seismicity in Enguri area (Georgia)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(1), pages 117-125, May.
    9. Kakinaka, Shinji & Umeno, Ken, 2021. "Exploring asymmetric multifractal cross-correlations of price–volatility and asymmetric volatility dynamics in cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    10. Longfeng Zhao & Wei Li & Andrea Fenu & Boris Podobnik & Yougui Wang & H. Eugene Stanley, 2017. "The q-dependent detrended cross-correlation analysis of stock market," Papers 1705.01406, arXiv.org, revised Jun 2017.
    11. Vitanov, Nikolay K. & Sakai, Kenshi & Dimitrova, Zlatinka I., 2008. "SSA, PCA, TDPSC, ACFA: Useful combination of methods for analysis of short and nonstationary time series," Chaos, Solitons & Fractals, Elsevier, vol. 37(1), pages 187-202.
    12. Ruan, Qingsong & Bao, Junjie & Zhang, Manqian & Fan, Limin, 2019. "The effects of exchange rate regime reform on RMB markets: A new perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 122-134.
    13. Thomas Theobald, 2015. "Agent-based risk management – a regulatory approach to financial markets," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 42(5), pages 780-820, October.
    14. Murguía, J.S. & Rosu, H.C. & Jimenez, A. & Gutiérrez-Medina, B. & García-Meza, J.V., 2015. "The Hurst exponents of Nitzschia sp. diatom trajectories observed by light microscopy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 417(C), pages 176-184.
    15. Wang, Dong-Hua & Yu, Xiao-Wen & Suo, Yuan-Yuan, 2012. "Statistical properties of the yuan exchange rate index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(12), pages 3503-3512.
    16. Wu, Yue & Shang, Pengjian & Chen, Shijian, 2019. "Modified multifractal large deviation spectrum based on CID for financial market system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1331-1342.
    17. Youwei Li & Xue-Zhong He, 2005. "Long Memory, Heterogeneity, and Trend Chasing," Computing in Economics and Finance 2005 113, Society for Computational Economics.
    18. Zhuang, Xiaoyang & Wei, Yu & Ma, Feng, 2015. "Multifractality, efficiency analysis of Chinese stock market and its cross-correlation with WTI crude oil price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 101-113.
    19. Xiao, Di & Wang, Jun, 2021. "Attitude interaction for financial price behaviours by contact system with small-world network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    20. Jovanovic, Tijana & Mejía, Alfonso & Gall, Heather & Gironás, Jorge, 2016. "Effect of urbanization on the long-term persistence of streamflow records," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 208-221.

    More about this item

    Keywords

    market hypothesis; tests; chaos;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C69 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Other

    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:blg:reveco:v:69:y:2017:i:1:p:22-28. 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: Eduard Alexandru Stoica (email available below). General contact details of provider: https://edirc.repec.org/data/feulbro.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.