IDEAS home Printed from https://ideas.repec.org/p/cui/wpaper/0051.html
   My bibliography  Save this paper

Could this be a fiction? Bitcoin forecasts most tradable currency pairs better than ARFIMA

Author

Listed:
  • Afees A. Salisu

    (Centre for Econometric and Allied Research, University of Ibadan)

  • Lateef O. Akanni

    (Department of Economics, University of Lagos,Akoka, Lagos, Nigeria)

  • Rasheed O. Azeez

    (Department of Economics, University of Ibadan, Nigeria.
    Department of Economics, Fountain University, Nigeria.)

Abstract

In this paper, we attempt to exploit any inherent useful information in Bitcoin to predict the future path of the most tradable currency pairs in the world. We also verify whether the forecast outcomes can compare favourably with the time series model such as the fractionally integrated autoregressive moving average (ARFIMA) model. We follow the Lewellen (2004) and Westerlund and Narayan (2102, 2015) approaches that account for any statistical effect that could bias the regression estimates. Our results suggest that Bitcoin is a good predictor of the selected currency pairs and more importantly, its forecast results outperform the time series model judging by the Diebold and Mariano test regardless of the data sample and forecast horizon. Although, recent evidence in the literature seems to suggest that the Bitcoin bubble will soon burst, its connection with the considered currency pairs may be exploited while it lasts.

Suggested Citation

  • Afees A. Salisu & Lateef O. Akanni & Rasheed O. Azeez, 2018. "Could this be a fiction? Bitcoin forecasts most tradable currency pairs better than ARFIMA," Working Papers 051, Centre for Econometric and Allied Research, University of Ibadan.
    • Handle: RePEc:cui:wpaper:0051
    as

    Download full text from publisher

    File URL: http://cear.org.ng/index.php?option=com_docman&task=doc_download&gid=94&Itemid=29
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bannigidadmath, Deepa & Narayan, Paresh Kumar, 2016. "Stock return predictability and determinants of predictability and profits," Emerging Markets Review, Elsevier, vol. 26(C), pages 153-173.
    2. Makin, Anthony J. & Narayan, Paresh Kumar & Narayan, Seema, 2014. "What expenditure does Anglosphere foreign borrowing fund?," Journal of International Money and Finance, Elsevier, vol. 40(C), pages 63-78.
    3. Westerlund, Joakim & Narayan, Paresh Kumar, 2012. "Does the choice of estimator matter when forecasting returns?," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2632-2640.
    4. Lewellen, Jonathan, 2004. "Predicting returns with financial ratios," Journal of Financial Economics, Elsevier, vol. 74(2), pages 209-235, November.
    5. Elie Bouri & Mahamitra Das & Rangan Gupta & David Roubaud, 2018. "Spillovers between Bitcoin and other assets during bear and bull markets," Applied Economics, Taylor & Francis Journals, vol. 50(55), pages 5935-5949, November.
    6. Moosa, Imad & Burns, Kelly, 2014. "The unbeatable random walk in exchange rate forecasting: Reality or myth?," Journal of Macroeconomics, Elsevier, vol. 40(C), pages 69-81.
    7. Narayan, Paresh Kumar & Gupta, Rangan, 2015. "Has oil price predicted stock returns for over a century?," Energy Economics, Elsevier, vol. 48(C), pages 18-23.
    8. Corbet, Shaen & Meegan, Andrew & Larkin, Charles & Lucey, Brian & Yarovaya, Larisa, 2018. "Exploring the dynamic relationships between cryptocurrencies and other financial assets," Economics Letters, Elsevier, vol. 165(C), pages 28-34.
    9. Baur, Dirk G. & Dimpfl, Thomas & Kuck, Konstantin, 2018. "Bitcoin, gold and the US dollar – A replication and extension," Finance Research Letters, Elsevier, vol. 25(C), pages 103-110.
    10. Dyhrberg, Anne Haubo, 2016. "Bitcoin, gold and the dollar – A GARCH volatility analysis," Finance Research Letters, Elsevier, vol. 16(C), pages 85-92.
    11. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2015. "Are Indian stock returns predictable?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 506-531.
    12. Deepa & Paresh K Narayan, "undated". "Are Indian Stock Returns Predictable?," Working Papers 2015_07, Deakin University, Department of Economics.
    13. Sharma, Susan Sunila, 2016. "Can consumer price index predict gold price returns?," Economic Modelling, Elsevier, vol. 55(C), pages 269-278.
    14. Wali, Muammer & Chan, Felix & Manzur, Meher, 2017. "Nonlinear dependence in exchange rate returns: How do emerging Asian currencies compare with major currencies?," Journal of Asian Economics, Elsevier, vol. 50(C), pages 62-72.
    15. Baur, Dirk G. & Hong, KiHoon & Lee, Adrian D., 2018. "Bitcoin: Medium of exchange or speculative assets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 54(C), pages 177-189.
    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. Isah, Kazeem O. & Raheem, Ibrahim D., 2019. "The hidden predictive power of cryptocurrencies and QE: Evidence from US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).

    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. Afees A. Salisu & Kazeem Isah & Lateef O. Akanni, 2018. "Predicting the stock prices of G7 countries with Bitcoin prices," Working Papers 054, Centre for Econometric and Allied Research, University of Ibadan.
    2. Salisu, Afees A. & Isah, Kazeem & Akanni, Lateef O., 2019. "Improving the predictability of stock returns with Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 857-867.
    3. Salisu, Afees A. & Ademuyiwa, Idris & Isah, Kazeem O., 2018. "Revisiting the forecasting accuracy of Phillips curve: The role of oil price," Energy Economics, Elsevier, vol. 70(C), pages 334-356.
    4. Afees A. Salisu & Ahamuefula Ephraim Ogbonna & Paul Adeoye Omosebi, 2018. "Does the choice of estimator matter for forecasting? A revisit," Working Papers 053, Centre for Econometric and Allied Research, University of Ibadan.
    5. Salisu, Afees A. & Isah, Kazeem O., 2018. "Predicting US inflation: Evidence from a new approach," Economic Modelling, Elsevier, vol. 71(C), pages 134-158.
    6. Isah, Kazeem O. & Raheem, Ibrahim D., 2019. "The hidden predictive power of cryptocurrencies and QE: Evidence from US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    7. repec:idn:journl:v:1:y:2019:i:sp2:p:1-12 is not listed on IDEAS
    8. Elie Bouri & Afees A. Salisu & Rangan Gupta, 2022. "Bitcoin Prices and the Realized Volatility of US Sectoral Stock Returns," Working Papers 202224, University of Pretoria, Department of Economics.
    9. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Tran, Vuong Thao, 2018. "Can economic policy uncertainty predict stock returns? Global evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 134-150.
    10. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2019. "Structural instability and predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    11. Moses Tule & Afees Salisu & Charles Chiemeke, 2020. "Improving Nigeria’s Inflation Forecast with Oil Price: The Role of Estimators," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(1), pages 191-229, March.
    12. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2018. "Is stock return predictability time-varying?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 152-172.
    13. Moses Tule & Afees A. Salisu & Charles Chimeke, 2018. "You are what you eat: The role of oil price in Nigeria inflation forecast," Working Papers 040, Centre for Econometric and Allied Research, University of Ibadan.
    14. Afees A. Salisu & Juncal Cunado & Kazeem Isah & Rangan Gupta, 2020. "Oil Price and Exchange Rate Behaviour of the BRICS for Over a Century," Working Papers 202064, University of Pretoria, Department of Economics.
    15. Salisu, Afees A. & Adekunle, Wasiu & Alimi, Wasiu A. & Emmanuel, Zachariah, 2019. "Predicting exchange rate with commodity prices: New evidence from Westerlund and Narayan (2015) estimator with structural breaks and asymmetries," Resources Policy, Elsevier, vol. 62(C), pages 33-56.
    16. Tule, Moses K. & Salisu, Afees A. & Chiemeke, Charles C., 2019. "Can agricultural commodity prices predict Nigeria's inflation?," Journal of Commodity Markets, Elsevier, vol. 16(C).
    17. Salisu, Afees A. & Raheem, Ibrahim D. & Ndako, Umar B., 2019. "A sectoral analysis of asymmetric nexus between oil price and stock returns," International Review of Economics & Finance, Elsevier, vol. 61(C), pages 241-259.
    18. Afees A. Salisu & Ahamuefula E. Ogbonna & Idris Adediran, 2021. "Stock‐induced Google trends and the predictability of sectoral stock returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 327-345, March.
    19. Salisu, Afees A. & Swaray, Raymond & Oloko, Tirimisiyu F., 2019. "Improving the predictability of the oil–US stock nexus: The role of macroeconomic variables," Economic Modelling, Elsevier, vol. 76(C), pages 153-171.
    20. Kazeem Isah & Ibrahim D. Raheem, 2018. "The Hidden Predictive Power of Cryptocurrencies: Evidence from US Stock Market," Working Papers 056, Centre for Econometric and Allied Research, University of Ibadan.
    21. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2015. "Stock return forecasting: Some new evidence," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 38-51.

    More about this item

    Keywords

    Bitcoin; Exchange rates; Forecast evaluation;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:cui:wpaper:0051. 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: Adeoye Omosebi (email available below). General contact details of provider: https://edirc.repec.org/data/ceuibng.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.