IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/86617.html
   My bibliography  Save this paper

Modelling heterogeneous speculation in Ghana’s foreign exchange market: Evidence from ARFIMA-FIGARCH and Semi-Parametric methods

Author

Listed:
  • Omane-Adjepong, Maurice
  • Boako, Gidoen
  • Alagidede, Paul

Abstract

In this paper, we explore the weak form efficiency of Ghana’s foreign exchange (FX) market and analyse the existence of speculative activity and correlated shocks in the market. We use high and low frequency data covering May 31, 1999 to November 30, 2017. For robustness, four rigorous methods are employed. Our findings are as follows: First, the efficiency of the FX market is non-homogenous. This gives very little room for speculative trading options, hence, we surmise that speculative activities cannot necessarily account for the self-driven shocks in Ghana’s FX market system. Second, the cedi/dollar market inefficiency is concealed in conditional returns, and toggles between persistence and anti-persistence for the high and low data frequencies respectively. Third, varying significant persistence is detected for the volatility returns for all market series, however, the evidence is more pronounced for daily-, absolute-, and conditional volatility returns. These data dynamics prove useful and should be considered when examining empirical behaviours of asset markets. In summing up, investors and policy makers could rely on the findings and their implications in making decisions on investment and exchange rate control system.

Suggested Citation

  • Omane-Adjepong, Maurice & Boako, Gidoen & Alagidede, Paul, 2018. "Modelling heterogeneous speculation in Ghana’s foreign exchange market: Evidence from ARFIMA-FIGARCH and Semi-Parametric methods," MPRA Paper 86617, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:86617
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/86617/1/MPRA_paper_86617.pdf
    File Function: original version
    Download Restriction: no

    References listed on IDEAS

    as
    1. A. Assaf, 2007. "Fractional integration in the equity markets of MENA region," Applied Financial Economics, Taylor & Francis Journals, vol. 17(9), pages 709-723.
    2. Zeileis, Achim & Kleiber, Christian & Kramer, Walter & Hornik, Kurt, 2003. "Testing and dating of structural changes in practice," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 109-123, October.
    3. Guglielmo Maria Caporale & Luis A. Gil-Alana & Alex Plastun, 2017. "Long Memory and Data Frequency in Financial Markets," Discussion Papers of DIW Berlin 1647, DIW Berlin, German Institute for Economic Research.
    4. Granger, Clive W. J. & Hyung, Namwon, 2004. "Occasional structural breaks and long memory with an application to the S&P 500 absolute stock returns," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 399-421, June.
    5. Smith, Aaron, 2005. "Level Shifts and the Illusion of Long Memory in Economic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 321-335, July.
    6. Arouri, Mohamed El Hedi & Hammoudeh, Shawkat & Lahiani, Amine & Nguyen, Duc Khuong, 2012. "Long memory and structural breaks in modeling the return and volatility dynamics of precious metals," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(2), pages 207-218.
    7. Gil-Alana, Luis A. & Chang, Shinhye & Balcilar, Mehmet & Aye, Goodness C. & Gupta, Rangan, 2015. "Persistence of precious metal prices: A fractional integration approach with structural breaks," Resources Policy, Elsevier, vol. 44(C), pages 57-64.
    8. Christos Floros, 2008. "Long Memory In Exchange Rates: International Evidence," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 2(1), pages 31-39.
    9. Berna Kirkulak Uludag & Zorikto Lkhamazhapov, 2014. "Long memory and structural breaks in the returns and volatility of gold: evidence from Turkey," Applied Economics, Taylor & Francis Journals, vol. 46(31), pages 3777-3787, November.
    10. Adrian Wai-Kong Cheung & Jen-Je Su & Astrophel Kim Choo, 2011. "Are Euro exchange rates markets efficient? New evidence from a large panel," Discussion Papers in Finance finance:201109, Griffith University, Department of Accounting, Finance and Economics.
    11. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    12. Lee, Dongin & Schmidt, Peter, 1996. "On the power of the KPSS test of stationarity against fractionally-integrated alternatives," Journal of Econometrics, Elsevier, vol. 73(1), pages 285-302, July.
    13. Gideon Boako & Maurice Omane-Adjepong & Joseph Magnus Frimpong, 2016. "Stock Returns and Exchange Rate Nexus in Ghana: A Bayesian Quantile Regression Approach," South African Journal of Economics, Economic Society of South Africa, vol. 84(1), pages 149-179, March.
    14. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    15. repec:taf:wjabxx:v:17:y:2016:i:3:p:342-359 is not listed on IDEAS
    16. Carlson, John A. & Osler, C. L., 2000. "Rational speculators and exchange rate volatility1," European Economic Review, Elsevier, vol. 44(2), pages 231-253, February.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Correlogram; FX market returns; Long-memory; Speculative activity; Ghana;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:pra:mprapa:86617. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joachim Winter). General contact details of provider: http://edirc.repec.org/data/vfmunde.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.