IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v13y2015icp74-80.html
   My bibliography  Save this article

Are emerging MENA stock markets mean reverting? A Monte Carlo simulation

Author

Listed:
  • Neaime, Simon

Abstract

We provide further empirical evidence on the mean reversion hypothesis for ten frontier stock markets in the Middle East and North Africa (MENA) using a battery of panel and time series econometric tests including Monte Carlo simulations. Standard unit root and panel unit root tests indicate that stock prices in the MENA region are not mean reverting which is consistent with the weak form efficient market hypothesis. However, Monte Carlo simulations depict mean reversion in the stock markets of Saudi Arabia, Jordan and Bahrain.

Suggested Citation

  • Neaime, Simon, 2015. "Are emerging MENA stock markets mean reverting? A Monte Carlo simulation," Finance Research Letters, Elsevier, vol. 13(C), pages 74-80.
    • Handle: RePEc:eee:finlet:v:13:y:2015:i:c:p:74-80
    DOI: 10.1016/j.frl.2015.03.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S154461231500029X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2015.03.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Myung Jig Kim & Charles R. Nelson & Richard Startz, 1991. "Mean Reversion in Stock Prices? A Reappraisal of the Empirical Evidence," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 515-528.
    2. Richards, Anthony J, 1997. "Winner-Loser Reversals in National Stock Market Indices: Can They Be Explained?," Journal of Finance, American Finance Association, vol. 52(5), pages 2129-2144, December.
    3. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know about Unit Roots," NBER Chapters, in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220, National Bureau of Economic Research, Inc.
    4. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    5. Richardson, Matthew, 1993. "Temporary Components of Stock Prices: A Skeptic's View," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 199-207, April.
    6. Chaudhuri, Kausik & Wu, Yangru, 2003. "Random walk versus breaking trend in stock prices: Evidence from emerging markets," Journal of Banking & Finance, Elsevier, vol. 27(4), pages 575-592, April.
    7. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    8. Neaime, Simon, 2012. "The global financial crisis, financial linkages and correlations in returns and volatilities in emerging MENA stock markets," Emerging Markets Review, Elsevier, vol. 13(3), pages 268-282.
    9. 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.
    10. DeJong, David N. & Nankervis, John C. & Savin, N. E. & Whiteman, Charles H., 1992. "The power problems of unit root test in time series with autoregressive errors," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 323-343.
    11. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    12. Cochrane, John H., 1991. "A critique of the application of unit root tests," Journal of Economic Dynamics and Control, Elsevier, vol. 15(2), pages 275-284, April.
    13. Wayne E. Ferson & Sergei Sarkissian & Timothy T. Simin, 2003. "Spurious Regressions in Financial Economics?," Journal of Finance, American Finance Association, vol. 58(4), pages 1393-1414, August.
    14. Ronald Balvers & Yangru Wu & Erik Gilliland, 2000. "Mean Reversion across National Stock Markets and Parametric Contrarian Investment Strategies," Journal of Finance, American Finance Association, vol. 55(2), pages 745-772, April.
    15. Guyot, Alexis & Lagoarde-Segot, Thomas & Neaime, Simon, 2014. "Foreign shocks and international cost of equity destabilization. Evidence from the MENA region," Emerging Markets Review, Elsevier, vol. 18(C), pages 101-122.
    16. Maddala, G S & Wu, Shaowen, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 631-652, Special I.
    17. Choi, In, 2001. "Unit root tests for panel data," Journal of International Money and Finance, Elsevier, vol. 20(2), pages 249-272, April.
    18. Richardson, Matthew & Stock, James H., 1989. "Drawing inferences from statistics based on multiyear asset returns," Journal of Financial Economics, Elsevier, vol. 25(2), pages 323-348, December.
    19. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    20. Sam Hakim & Simon Neaime, 2000. "Mean-Reversion Across MENA Stock Markets: Implications for Portfolio Allocations," Working Papers 2026, Economic Research Forum, revised 09 2000.
    21. Thomas Lagoarde-Segot & Brian Lucey, 2006. "Financial Contagion in Emerging Markets: Evidence from the Middle East and North Africa," The Institute for International Integration Studies Discussion Paper Series iiisdp114, IIIS.
    22. 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.
    23. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    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. Ali, Sajid & Shahzad, Syed Jawad Hussain & Raza, Naveed & Al-Yahyaee, Khamis Hamed, 2018. "Stock market efficiency: A comparative analysis of Islamic and conventional stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 139-153.
    2. Shahzad, Syed Jawad Hussain & Nor, Safwan Mohd & Mensi, Walid & Kumar, Ronald Ravinesh, 2017. "Examining the efficiency and interdependence of US credit and stock markets through MF-DFA and MF-DXA approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 351-363.
    3. Ramzi Boussaidi, 2017. "The winner-loser effect in the Tunisian stock market: A multidimensional risk-based explanation," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(3), pages 178-189, September.
    4. Boako, Gideon & Alagidede, Paul, 2016. "African stock markets convergence: Regional and global analysis," Finance Research Letters, Elsevier, vol. 18(C), pages 317-321.

    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. Paresh Kumar Narayan & Russell Smyth, 2005. "Are OECD stock prices characterized by a random walk? Evidence from sequential trend break and panel data models," Applied Financial Economics, Taylor & Francis Journals, vol. 15(8), pages 547-556.
    2. Chaudhuri, Kausik & Wu, Yangru, 2003. "Random walk versus breaking trend in stock prices: Evidence from emerging markets," Journal of Banking & Finance, Elsevier, vol. 27(4), pages 575-592, April.
    3. Kim, Hyeongwoo, 2009. "On the usefulness of the contrarian strategy across national stock markets: A grid bootstrap analysis," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 734-744, December.
    4. John Hatgioannides & Spiros Mesomeris, 2005. "Mean Reversion in Equity Prices: the G-7 Evidence," Money Macro and Finance (MMF) Research Group Conference 2005 64, Money Macro and Finance Research Group.
    5. Cunado, J. & Gil-Alana, L.A. & Gracia, Fernando Perez de, 2010. "Mean reversion in stock market prices: New evidence based on bull and bear markets," Research in International Business and Finance, Elsevier, vol. 24(2), pages 113-122, June.
    6. Kim, Hyeongwoo & Kim, Jintae, 2018. "London calling: Nonlinear mean reversion across national stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 265-277.
    7. Hiremath, Gourishankar S & Bandi, Kamaiah, 2010. "Do stock returns in India exhibit a mean reverting tendency? Evidence from multiple structural breaks test," MPRA Paper 46502, University Library of Munich, Germany.
    8. Shu-Ling Chen & Hyeongwoo Kim, 2011. "Nonlinear Mean Reversion across National Stock Markets: Evidence from Emerging Asian Markets," International Economic Journal, Taylor & Francis Journals, vol. 25(2), pages 239-250.
    9. George Halkos & Ilias Kevork, 2005. "A comparison of alternative unit root tests," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(1), pages 45-60.
    10. Narayan, Paresh Kumar & Narayan, Seema & Mishra, Sagarika, 2013. "Has the structural break slowed down growth rates of stock markets?," Economic Modelling, Elsevier, vol. 30(C), pages 595-601.
    11. Gropp, Jeffrey, 2004. "Mean reversion of industry stock returns in the U.S., 1926-1998," Journal of Empirical Finance, Elsevier, vol. 11(4), pages 537-551, September.
    12. Liam Gallagher, 1999. "A multi-country analysis of the temporary and permanent components of stock prices," Applied Financial Economics, Taylor & Francis Journals, vol. 9(2), pages 129-142.
    13. Kim, Hyeongwoo & Ryu, Deockhyun, 2015. "Measuring the speed of convergence of stock prices: A nonparametric and nonlinear approach," Economic Modelling, Elsevier, vol. 51(C), pages 227-241.
    14. Liam A. Gallagher & Mark P. Taylor, 2002. "Permanent and Temporary Components of Stock Prices: Evidence from Assessing Macroeconomic Shocks," Southern Economic Journal, John Wiley & Sons, vol. 69(2), pages 345-362, October.
    15. Wang, Juan & Zhang, Dongxiang & Zhang, Jian, 2015. "Mean reversion in stock prices of seven Asian stock markets: Unit root test and stationary test with Fourier functions," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 157-164.
    16. Eric Hillebrand, 2005. "Mean Reversion Expectations and the 1987 Stock Market Crash: An Empirical Investigation," Finance 0501015, University Library of Munich, Germany.
    17. Peter Farkas & Laszlo Matyas, 2015. "Testing for Unit Roots in Panel Data with Boundary Crossing Counts," CEU Working Papers 2015_5, Department of Economics, Central European University, revised 03 Nov 2015.
    18. Emmanouil Mavrakis & Christos Alexakis, 2018. "Statistical Arbitrage Strategies under Different Market Conditions: The Case of the Greek Banking Sector," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2), pages 159-185, August.
    19. Hyeongwoo Kim & Liliana Stern & Michael Stern, 2009. "Nonlinear mean reversion in the G7 stock markets," Applied Financial Economics, Taylor & Francis Journals, vol. 19(5), pages 347-355.
    20. Narayan, Paresh Kumar & Smyth, Russell, 2007. "Mean reversion versus random walk in G7 stock prices evidence from multiple trend break unit root tests," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 17(2), pages 152-166, April.

    More about this item

    Keywords

    MENA stock markets; Mean reversion; Panel and time series tests;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

    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:eee:finlet:v:13:y:2015:i:c:p:74-80. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    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.