IDEAS home Printed from https://ideas.repec.org/a/spr/jecfin/v48y2024i2d10.1007_s12197-024-09668-9.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12197-024-09668-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s12197-024-09668-9?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. 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. 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.
    3. 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.
    4. Breitung, Jörg & Eickmeier, Sandra, 2011. "Testing for structural breaks in dynamic factor models," Journal of Econometrics, Elsevier, vol. 163(1), pages 71-84, July.
    5. 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.
    6. 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.
    7. 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.
    8. Mr. Jun Nagayasu, 2003. "The Efficiency of the Japanese Equity Market," IMF Working Papers 2003/142, International Monetary Fund.
    9. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    10. 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.
    11. repec:ebl:ecbull:v:14:y:2008:i:2:p:1-13 is not listed on IDEAS
    12. Liu, Ming, 2000. "Modeling long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 99(1), pages 139-171, November.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. Ms. Jayasri Dutta, 2002. "Dread of Depreciation: Measuring Real Exchange Rate Interventions," IMF Working Papers 2002/063, International Monetary Fund.
    22. 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.
    23. 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.
    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. Kuttu, Saint, 2018. "Modelling long memory in volatility in sub-Saharan African equity markets," Research in International Business and Finance, Elsevier, vol. 44(C), pages 176-185.
    2. Morana, Claudio & Beltratti, Andrea, 2004. "Structural change and long-range dependence in volatility of exchange rates: either, neither or both?," Journal of Empirical Finance, Elsevier, vol. 11(5), pages 629-658, December.
    3. Ngene, Geoffrey & Tah, Kenneth A. & Darrat, Ali F., 2017. "Long memory or structural breaks: Some evidence for African stock markets," Review of Financial Economics, Elsevier, vol. 34(C), pages 61-73.
    4. Chia-Hsun Hsieh & Shian-Chang Huang, 2012. "Time-Varying Dependency and Structural Changes in Currency Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 48(2), pages 94-127, March.
    5. Al-Shboul, Mohammad & Alsharari, Nizar, 2019. "The dynamic behavior of evolving efficiency: Evidence from the UAE stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 73(C), pages 119-135.
    6. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    7. Abderrazak Ben Maatoug & Rim Lamouchi & Russell Davidson & Ibrahim Fatnassi, 2018. "Modelling Foreign Exchange Realized Volatility Using High Frequency Data: Long Memory versus Structural Breaks," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(1), pages 1-25, March.
    8. Andrés Herrera Aramburú & Gabriel Rodríguez, 2016. "Volatility of stock market and exchange rate returns in Peru: Long memory or short memory with level shifts?," International Journal of Monetary Economics and Finance, Inderscience Enterprises Ltd, vol. 9(1), pages 45-66.
    9. Han Hwa Goh & Kim Leng Tan & Chia Ying Khor & Sew Lai Ng, 2016. "Volatility and Market Risk of Rubber Price in Malaysia: Pre- and Post-Global Financial Crisis," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(2), pages 323-344, December.
    10. Geoffrey Ngene & Kenneth A. Tah & Ali F. Darrat, 2017. "Long memory or structural breaks: Some evidence for African stock markets," Review of Financial Economics, John Wiley & Sons, vol. 34(1), pages 61-73, September.
    11. M. Karanasos & S. Yfanti & A. Christopoulos, 2021. "The long memory HEAVY process: modeling and forecasting financial volatility," Annals of Operations Research, Springer, vol. 306(1), pages 111-130, November.
    12. Jonathan Dark, 2004. "Long memory in the volatility of the Australian All Ordinaries Index and the Share Price Index futures," Monash Econometrics and Business Statistics Working Papers 5/04, Monash University, Department of Econometrics and Business Statistics.
    13. Assaf, Ata, 2015. "Long memory and level shifts in REITs returns and volatility," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 172-182.
    14. Banerjee, Anindya & Urga, Giovanni, 2005. "Modelling structural breaks, long memory and stock market volatility: an overview," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 1-34.
    15. Geoffrey Ngene & Ann Nduati Mungai & Allen K. Lynch, 2018. "Long-Term Dependency Structure and Structural Breaks: Evidence from the U.S. Sector Returns and Volatility," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 1-38, June.
    16. Wang, Lu & Wu, Jianhong, 2022. "Estimation of high-dimensional factor models with multiple structural changes," Economic Modelling, Elsevier, vol. 108(C).
    17. Charfeddine, Lanouar & Ajmi, Ahdi Noomen, 2013. "The Tunisian stock market index volatility: Long memory vs. switching regime," Emerging Markets Review, Elsevier, vol. 16(C), pages 170-182.
    18. Hull, Matthew & McGroarty, Frank, 2014. "Do emerging markets become more efficient as they develop? Long memory persistence in equity indices," Emerging Markets Review, Elsevier, vol. 18(C), pages 45-61.
    19. Duan, Jiangtao & Bai, Jushan & Han, Xu, 2023. "Quasi-maximum likelihood estimation of break point in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 233(1), pages 209-236.
    20. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2016. "Estimation of heterogeneous panels with structural breaks," Journal of Econometrics, Elsevier, vol. 191(1), pages 176-195.

    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

    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:spr:jecfin:v:48:y:2024:i:2:d:10.1007_s12197-024-09668-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.