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Forecasting of Exchange Rate Volatility between Naira and US Dollar Using GARCH Models

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  • Musa Y.
  • Tasi’u M.
  • Abubakar Bello

Abstract

Exchange rates are important financial problem that is receiving attention globally. This study investigated the volatility modeling of daily Dollar/Naira exchange rate using GARCH, GJR- GARCH, TGRACH and TS-GARCH models by using daily data over the period June 2000 to July 2011. The aim of the study is to determine volatility modeling of daily exchange rate between US (Dollar) and Nigeria (Naira). The results show that the GJR-GARCH and TGARCH models show the existence of statistically significant asymmetry effect. The forecasting ability is subsequently assessed using the symmetric lost functions which are the Mean Absolute Error (MAE), Root Mean Absolute Error (RMAE), Mean Absolute Percentage Error (MAPE) and Theil inequality Coefficient. The results show that TGARCH model provide the most accurate forecasts. This model will captured all the necessary stylize facts (common features) of financial data, such as persistent, volatility clustering and asymmetric effects.

Suggested Citation

  • Musa Y. & Tasi’u M. & Abubakar Bello, 2014. "Forecasting of Exchange Rate Volatility between Naira and US Dollar Using GARCH Models," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 4(7), pages 369-381, July.
  • Handle: RePEc:hur:ijarbs:v:4:y:2014:i:7:p:369-381
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    References listed on IDEAS

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    1. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    2. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    3. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    4. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    5. Rohan Longmore & Wayne Robinson, 2005. "Modelling and Forecasting Exchange Rate Dynamics in Jamaica: an Application of Asymmetric Volatility Models," Money Affairs, CEMLA, vol. 0(1), pages 23-56, January-J.
    6. Taylor, Stephen J., 1987. "Forecasting the volatility of currency exchange rates," International Journal of Forecasting, Elsevier, vol. 3(1), pages 159-170.
    7. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    8. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. Hatice Erkekoglu & Aweng Peter Majok Garang & Adire Simon Deng, 2020. "Modeling and Forecasting USD/UGX Volatility through GARCH Family Models: Evidence from Gaussian, T and GED Distributions," International Journal of Economics and Financial Issues, Econjournals, vol. 10(2), pages 268-281.
    2. Nyoni, Thabani, 2018. "Modeling and Forecasting Naira / USD Exchange Rate In Nigeria: a Box - Jenkins ARIMA approach," MPRA Paper 88622, University Library of Munich, Germany, revised 19 Aug 2018.

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    More about this item

    Keywords

    Volatility; GARCH; Asymmetric models; Exchange Rates;
    All these keywords.

    JEL classification:

    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F43 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Economic Growth of Open Economies

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