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The Effect of Exchange Rates on Nigerians Currency and Projecting the Naira for the Year 2025

Received: 2 March 2019     Accepted: 2 April 2019     Published: 26 April 2019
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Abstract

Exchange rate instability is a good pointer for monitoring Nigerian currency and it has always been a key economic indicator to sustain Nigeria and her economic growth. Linear regression is a great statistical tool used to find, predict and also to assess whether there is an undeviating correlation and dependences between numerical variables. This study investigates the instabilities in exchange rate of five countries’ currencies which includes European Euro, United Kingdom Pounds, Saudi Arabian Riyal, Switzerland swissf and the Nigerian Naira with key interest on Naira. This was done to ascertain whether changes in other countries will affect the exchange rate of Naira. The stable and fluctuating exchange rate of these countries were examined and used to plot a digital signal structure. Data used for this study is the daily exchange rate of five countries’ currencies (Euro, Pounds, Riyal, Swissf and Naira) from 12th October, 2005 to 2nd October, 2018 obtained from https://www.cbn.gov.ng/rates/exchratebycurrency.asp. We applied linear regression tool on our source data and also applied the equation for prediction on our coefficients so we were able to predict the exchange for Naira come year 2025 which gave us N311.076. The rate of accuracy (R2) and the coefficient of our model were used in predicting Nigerians exchange rate for year 2025. The 99% rate of accuracy of our model reveals that our model is perfect and the impression from this study is that the exchange rate of other countries affects Naira.

Published in American Journal of Data Mining and Knowledge Discovery (Volume 4, Issue 1)
DOI 10.11648/j.ajdmkd.20190401.13
Page(s) 15-18
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Exchange Rate, Machine Learning, Linear Regression, Digital Signal Processing, Supervised Machine Learning, Unsupervised Machine Learning

References
[1] A. I. Lawal, I. O. Atunde V. Ahmed and A. Abiola (2016). Exchange Rate Fluctuation and the Nigeria Economic Growth. The Euro Economica. 2(35), 127-142.
[2] A. Hossai (2002). Exchange Rate Responses to Inflation in Bangladesh. Washington D. C. IMF Working Paper, No. WP/02/XX.
[3] K. Rogoffs & C. M. Reinhart (2004). The Modern History of Exchange Rate Arrangements: A Reinterpretation. Quarterly Journal of Economics, 119(1), pp. 1-47.
[4] M. Guclu (2009). How do Macroeconomic and Political Variables Affect the Flexibility of Exchange Rate Regime? Ege Academic Review, 9(2), p. 823-835.
[5] A. Markiewicz (2006). Choice of Exchange Rate Regimes in Transition Economies: An Empirical Analysis. Journal of Comparative Economics, 34(3), p. 484-498.
[6] K A. Rose (2011). Exchange Rate Regimes in the Modern Era: Fixed, Floating and Flaky. Journal of Economic Literature, 49(3), p. 652-672.
[7] Sandha, N. D. & Charanject, K. R., (2016). A Review on Machine Learning Techniques. In International Journal on Recent and Innovation Trends in Computing and Communication. 4(3), 451-458.
[8] A. J. Frankel (1999). No Single Currency Regime is Right for all Countries or at all Times” National Bureau of Economic Research, Working Paper No. 7338.
[9] T. Anish, T. & K. Yogesh(2013). Machine Learning: An Artificial Intelligience Methodology. In Internal Journal of Engineering and Computer Science. 23(6). 345-352.
[10] O. A. Taiwo (2010). Types of Machine Learning Algorithms, New Advances in Machine Learning, Yagang Zhang (Ed.), ISBN: 978-953-307-034-6, InTech.
[11] N. D. Sandha & K. R. Charanject (2016). A Review on Machine Learning Techniques. In International Journal on Recent and Innovation Trends in Computing and Communication. 4(3), 451-458.
[12] S. R. U. Aliyu(2011). Impact of Oil Price Shock and Exchange Rate Volatility on Economic Growth in Nigeria: An empirical investigation. Research Journal of International Studies.
[13] O. J. Asher (2012). The Impact of Exchange rate Fluctuation on the Nigeria Economic Growth (1980 – 2010). Unpublished B.sc Thesis of Caritas University Emene, Enugu State, Nigeria.
Cite This Article
  • APA Style

    Ledisi Giok Kabari, Osuo-Genseleke Macarthy. (2019). The Effect of Exchange Rates on Nigerians Currency and Projecting the Naira for the Year 2025. American Journal of Data Mining and Knowledge Discovery, 4(1), 15-18. https://doi.org/10.11648/j.ajdmkd.20190401.13

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    ACS Style

    Ledisi Giok Kabari; Osuo-Genseleke Macarthy. The Effect of Exchange Rates on Nigerians Currency and Projecting the Naira for the Year 2025. Am. J. Data Min. Knowl. Discov. 2019, 4(1), 15-18. doi: 10.11648/j.ajdmkd.20190401.13

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    AMA Style

    Ledisi Giok Kabari, Osuo-Genseleke Macarthy. The Effect of Exchange Rates on Nigerians Currency and Projecting the Naira for the Year 2025. Am J Data Min Knowl Discov. 2019;4(1):15-18. doi: 10.11648/j.ajdmkd.20190401.13

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  • @article{10.11648/j.ajdmkd.20190401.13,
      author = {Ledisi Giok Kabari and Osuo-Genseleke Macarthy},
      title = {The Effect of Exchange Rates on Nigerians Currency and Projecting the Naira for the Year 2025},
      journal = {American Journal of Data Mining and Knowledge Discovery},
      volume = {4},
      number = {1},
      pages = {15-18},
      doi = {10.11648/j.ajdmkd.20190401.13},
      url = {https://doi.org/10.11648/j.ajdmkd.20190401.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajdmkd.20190401.13},
      abstract = {Exchange rate instability is a good pointer for monitoring Nigerian currency and it has always been a key economic indicator to sustain Nigeria and her economic growth. Linear regression is a great statistical tool used to find, predict and also to assess whether there is an undeviating correlation and dependences between numerical variables. This study investigates the instabilities in exchange rate of five countries’ currencies which includes European Euro, United Kingdom Pounds, Saudi Arabian Riyal, Switzerland swissf and the Nigerian Naira with key interest on Naira. This was done to ascertain whether changes in other countries will affect the exchange rate of Naira. The stable and fluctuating exchange rate of these countries were examined and used to plot a digital signal structure. Data used for this study is the daily exchange rate of five countries’ currencies (Euro, Pounds, Riyal, Swissf and Naira) from 12th October, 2005 to 2nd October, 2018 obtained from https://www.cbn.gov.ng/rates/exchratebycurrency.asp. We applied linear regression tool on our source data and also applied the equation for prediction on our coefficients so we were able to predict the exchange for Naira come year 2025 which gave us N311.076. The rate of accuracy (R2) and the coefficient of our model were used in predicting Nigerians exchange rate for year 2025. The 99% rate of accuracy of our model reveals that our model is perfect and the impression from this study is that the exchange rate of other countries affects Naira.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - The Effect of Exchange Rates on Nigerians Currency and Projecting the Naira for the Year 2025
    AU  - Ledisi Giok Kabari
    AU  - Osuo-Genseleke Macarthy
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    JO  - American Journal of Data Mining and Knowledge Discovery
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    PB  - Science Publishing Group
    SN  - 2578-7837
    UR  - https://doi.org/10.11648/j.ajdmkd.20190401.13
    AB  - Exchange rate instability is a good pointer for monitoring Nigerian currency and it has always been a key economic indicator to sustain Nigeria and her economic growth. Linear regression is a great statistical tool used to find, predict and also to assess whether there is an undeviating correlation and dependences between numerical variables. This study investigates the instabilities in exchange rate of five countries’ currencies which includes European Euro, United Kingdom Pounds, Saudi Arabian Riyal, Switzerland swissf and the Nigerian Naira with key interest on Naira. This was done to ascertain whether changes in other countries will affect the exchange rate of Naira. The stable and fluctuating exchange rate of these countries were examined and used to plot a digital signal structure. Data used for this study is the daily exchange rate of five countries’ currencies (Euro, Pounds, Riyal, Swissf and Naira) from 12th October, 2005 to 2nd October, 2018 obtained from https://www.cbn.gov.ng/rates/exchratebycurrency.asp. We applied linear regression tool on our source data and also applied the equation for prediction on our coefficients so we were able to predict the exchange for Naira come year 2025 which gave us N311.076. The rate of accuracy (R2) and the coefficient of our model were used in predicting Nigerians exchange rate for year 2025. The 99% rate of accuracy of our model reveals that our model is perfect and the impression from this study is that the exchange rate of other countries affects Naira.
    VL  - 4
    IS  - 1
    ER  - 

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Author Information
  • Department of Computer Science, Faculty of Applied Sciences, Ken Saro-Wiwa Polytechnic, Bori, Nigeria

  • Department of Computer Science, Faculty of Natural and Applied Sciences, Ignatius Ajuru University, Port Harcourt, Nigeria

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