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Long memory in volatility in foreign exchange markets: evidence from selected countries in Africa

Author

Listed:
  • Saint Kuttu

    (University of Ghana, University of Ghana)

  • Joshua Yindenaba Abor

    (University of Ghana, University of Ghana)

  • Godfred Amewu

    (University of Ghana, University of Ghana)

Abstract

This study examines the long memory properties in the volatility of the foreign exchange markets of Egypt, Ghana, Kenya, Nigeria and South Africa. Applying the FIEGARCH model to daily data from June 2, 1997, to December 31, 2021, we find long memory in the second moment of return innovations across all five countries' foreign exchange markets and significant first-order positive autocorrelation. To isolate spurious long memory, we perform a structural break test and find that structural breaks in all five foreign exchange markets do not affect long memory. The findings may have implications for risk management. Historical volatility-based investment methods can generate risk-adjusted returns innovations. Long memory may indicate unexploited profit for risk-seeking speculators and international investors in these countries' financial assets. Also, official intervention should be random and rule-changing to reduce currency market predictability.

Suggested Citation

  • Saint Kuttu & Joshua Yindenaba Abor & Godfred Amewu, 2024. "Long memory in volatility in foreign exchange markets: evidence from selected countries in Africa," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 48(2), pages 462-482, June.
    • Handle: RePEc:spr:jecfin:v:48:y:2024:i:2:d:10.1007_s12197-024-09668-9
    DOI: 10.1007/s12197-024-09668-9
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    as
    1. C. May & G Farrell, 2018. "Modelling Exchange Rate Volatility Dynamics: Empirical Evidence From South Africa," Studies in Economics and Econometrics, Taylor & Francis Journals, vol. 42(3), pages 71-114, December.
    2. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    3. Tobias Rydén & Timo Teräsvirta & Stefan Åsbrink, 1998. "Stylized facts of daily return series and the hidden Markov model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(3), pages 217-244.
    4. Sadique, Shibley & Silvapulle, Param, 2001. "Long-Term Memory in Stock Market Returns: International Evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 6(1), pages 59-67, January.
    5. Calvo, Guillermo A. & Reinhart, Carmen M. & Vegh, Carlos A., 1995. "Targeting the real exchange rate: theory and evidence," Journal of Development Economics, Elsevier, vol. 47(1), pages 97-133, June.
    6. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
    7. Breitung, Jörg & Eickmeier, Sandra, 2011. "Testing for structural breaks in dynamic factor models," Journal of Econometrics, Elsevier, vol. 163(1), pages 71-84, July.
    8. 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.
    9. Alexander Boateng & Gloria Claudio-Quiroga & Luis A. Gil-Alana, 2020. "Exchange rate dynamics in South Africa," Applied Economics, Taylor & Francis Journals, vol. 52(22), pages 2339-2352, May.
    10. M. S. Mohanty & Marc Klau, 2005. "Monetary Policy Rules in Emerging Market Economies: Issues and Evidence," Springer Books, in: Rolf J. Langhammer & Lúcio Vinhas Souza (ed.), Monetary Policy and Macroeconomic Stabilization in Latin America, pages 205-245, Springer.
    11. Sifunjo E. Kisaka & Wainaina Gituro & Pokhariyal Ganesh & Ngugi W. Rose, 2008. "An analysis of the efficiency of the foreign exchange market in Kenya," Economics Bulletin, AccessEcon, vol. 14(2), pages 1-13.
    12. P Thupayagale & K Jefferis, 2011. "Real Versus Spurious Long-Memory Volatility In Foreign Exchange Data: Evidence From The Rand Against The G4 Currencies," Studies in Economics and Econometrics, Taylor & Francis Journals, vol. 35(2), pages 71-94, August.
    13. Chkili, Walid & Aloui, Chaker & Nguyen, Duc Khuong, 2012. "Asymmetric effects and long memory in dynamic volatility relationships between stock returns and exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(4), pages 738-757.
    14. Lasfer, M. Ameziane & Melnik, Arie & Thomas, Dylan C., 2003. "Short-term reaction of stock markets in stressful circumstances," Journal of Banking & Finance, Elsevier, vol. 27(10), pages 1959-1977, October.
    15. Mr. Jun Nagayasu, 2003. "The Efficiency of the Japanese Equity Market," IMF Working Papers 2003/142, International Monetary Fund.
    16. Iyke, Bernard Njindan & Ho, Sin-Yu, 2021. "Exchange rate exposure in the South African stock market before and during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 43(C).
    17. Ayogu, Melvin D, 1997. "Return Predictability: Evidence from Nigeria's Foreign Exchange Parallel Market," Journal of African Economies, Centre for the Study of African Economies, vol. 6(2), pages 296-313, July.
    18. repec:ebl:ecbull:v:14:y:2008:i:2:p:1-13 is not listed on IDEAS
    19. Liu, Ming, 2000. "Modeling long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 99(1), pages 139-171, November.
    20. 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.
    21. Bollerslev, Tim & Wright, Jonathan H., 2000. "Semiparametric estimation of long-memory volatility dependencies: The role of high-frequency data," Journal of Econometrics, Elsevier, vol. 98(1), pages 81-106, September.
    22. 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.
    23. Ms. Jayasri Dutta, 2002. "Dread of Depreciation: Measuring Real Exchange Rate Interventions," IMF Working Papers 2002/063, International Monetary Fund.
    24. Aron, Janine & Ayogu, Melvin, 1997. "Foreign Exchange Market Efficiency Tests in Sub-Saharan Africa," Journal of African Economies, Centre for the Study of African Economies, vol. 6(3), pages 150-192, Supplemen.
    25. Y. K. Tse, 1998. "The conditional heteroscedasticity of the yen-dollar exchange rate," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(1), pages 49-55.
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    More about this item

    Keywords

    Long memory; FIEGARCH; Structural break; Foreign Exchange Market; Africa;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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