Modelling the Volatility of Exchange Rates in Rwandese Markets

Jean de Dieu Ntawihebasenga; Joseph Kyalor Mung’atu; Peter Nyamuhanga Mwita

doi:doi:10.11648/j.ajtas.20150406.12

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Modelling the Volatility of Exchange Rates in Rwandese Markets

Jean de Dieu Ntawihebasenga, Joseph Kyalor Mung’atu, Peter Nyamuhanga Mwita

Published in American Journal of Theoretical and Applied Statistics (Volume 4, Issue 6)

Received: 15 August 2014 Accepted: 19 March 2015 Published: 25 September 2015

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Abstract

This work applied Generalized Autoregressive Conditional Heteroskedasticity (GARCH) approachto modelling volatility in Rwanda Exchange rate returns. The Autoregressive (AR) model with GARCH errors was fitted to the daily exchange rate returns using Quasi-Maximum Likelihood Estimation (Q-MLE) method to get the current volatility, asymptotic consistency and asymptotic normality of estimated parameters.Akaike Information criterion was used for appropriate GARCH model selection while Jarque Bera test used for normality testing revealed that both returns and residuals have fat tails behaviour. It was shown that the estimated model fits Rwanda exchange rate returns data well.

Published in	American Journal of Theoretical and Applied Statistics (Volume 4, Issue 6)
DOI	10.11648/j.ajtas.20150406.12
Page(s)	426-431
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), 2015. Published by Science Publishing Group

Keywords

Model, Volatility, ExchangeRate, Quasi Maximum Likelihood, GARCH Model

References

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[16]	Sandmann, G., & Koopman, S. (1998). Estimation of Stochastics Volatility Models Via Monte Carlo Maximum Likelihood . Journal of Econometrics Vol.87 , 271-301.
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Jean de Dieu Ntawihebasenga, Joseph Kyalor Mung’atu, Peter Nyamuhanga Mwita. (2015). Modelling the Volatility of Exchange Rates in Rwandese Markets. American Journal of Theoretical and Applied Statistics, 4(6), 426-431. https://doi.org/10.11648/j.ajtas.20150406.12

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ACS Style

Jean de Dieu Ntawihebasenga; Joseph Kyalor Mung’atu; Peter Nyamuhanga Mwita. Modelling the Volatility of Exchange Rates in Rwandese Markets. Am. J. Theor. Appl. Stat. 2015, 4(6), 426-431. doi: 10.11648/j.ajtas.20150406.12

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AMA Style

Jean de Dieu Ntawihebasenga, Joseph Kyalor Mung’atu, Peter Nyamuhanga Mwita. Modelling the Volatility of Exchange Rates in Rwandese Markets. Am J Theor Appl Stat. 2015;4(6):426-431. doi: 10.11648/j.ajtas.20150406.12

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@article{10.11648/j.ajtas.20150406.12,
  author = {Jean de Dieu Ntawihebasenga and Joseph Kyalor Mung’atu and Peter Nyamuhanga Mwita},
  title = {Modelling the Volatility of Exchange Rates in Rwandese Markets},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {4},
  number = {6},
  pages = {426-431},
  doi = {10.11648/j.ajtas.20150406.12},
  url = {https://doi.org/10.11648/j.ajtas.20150406.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20150406.12},
  abstract = {This work applied Generalized Autoregressive Conditional Heteroskedasticity (GARCH) approachto modelling volatility in Rwanda Exchange rate returns. The Autoregressive (AR) model with GARCH errors was fitted to the daily exchange rate returns using Quasi-Maximum Likelihood Estimation (Q-MLE) method to get the current volatility, asymptotic consistency and asymptotic normality of estimated parameters.Akaike Information criterion was used for appropriate GARCH model selection while Jarque Bera test used for normality testing revealed that both returns and residuals have fat tails behaviour. It was shown that the estimated model fits Rwanda exchange rate returns data well.},
 year = {2015}
}

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TY  - JOUR
T1  - Modelling the Volatility of Exchange Rates in Rwandese Markets
AU  - Jean de Dieu Ntawihebasenga
AU  - Joseph Kyalor Mung’atu
AU  - Peter Nyamuhanga Mwita
Y1  - 2015/09/25
PY  - 2015
N1  - https://doi.org/10.11648/j.ajtas.20150406.12
DO  - 10.11648/j.ajtas.20150406.12
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 426
EP  - 431
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20150406.12
AB  - This work applied Generalized Autoregressive Conditional Heteroskedasticity (GARCH) approachto modelling volatility in Rwanda Exchange rate returns. The Autoregressive (AR) model with GARCH errors was fitted to the daily exchange rate returns using Quasi-Maximum Likelihood Estimation (Q-MLE) method to get the current volatility, asymptotic consistency and asymptotic normality of estimated parameters.Akaike Information criterion was used for appropriate GARCH model selection while Jarque Bera test used for normality testing revealed that both returns and residuals have fat tails behaviour. It was shown that the estimated model fits Rwanda exchange rate returns data well.
VL  - 4
IS  - 6
ER  -

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Author Information

Jean de Dieu Ntawihebasenga

Mahatma Gandhi University-Rwanda, Faculty of Science, Department of Mathematics, Kigali-Rwanda
Joseph Kyalor Mung’atu

Jomo Kenyatta University of Agriculture and Technology, Faculty of Applied Science, Department of Statistics and Actuarial Science, Kisumu-Kenya
Peter Nyamuhanga Mwita

Jomo Kenyatta University of Agriculture and Technology, Faculty of Applied Science, Department of Statistics and Actuarial Science, Nairobi-Kenya

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APA Style

Jean de Dieu Ntawihebasenga, Joseph Kyalor Mung’atu, Peter Nyamuhanga Mwita. (2015). Modelling the Volatility of Exchange Rates in Rwandese Markets. American Journal of Theoretical and Applied Statistics, 4(6), 426-431. https://doi.org/10.11648/j.ajtas.20150406.12

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ACS Style

Jean de Dieu Ntawihebasenga; Joseph Kyalor Mung’atu; Peter Nyamuhanga Mwita. Modelling the Volatility of Exchange Rates in Rwandese Markets. Am. J. Theor. Appl. Stat. 2015, 4(6), 426-431. doi: 10.11648/j.ajtas.20150406.12

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AMA Style

Jean de Dieu Ntawihebasenga, Joseph Kyalor Mung’atu, Peter Nyamuhanga Mwita. Modelling the Volatility of Exchange Rates in Rwandese Markets. Am J Theor Appl Stat. 2015;4(6):426-431. doi: 10.11648/j.ajtas.20150406.12

Copy | Download

@article{10.11648/j.ajtas.20150406.12,
  author = {Jean de Dieu Ntawihebasenga and Joseph Kyalor Mung’atu and Peter Nyamuhanga Mwita},
  title = {Modelling the Volatility of Exchange Rates in Rwandese Markets},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {4},
  number = {6},
  pages = {426-431},
  doi = {10.11648/j.ajtas.20150406.12},
  url = {https://doi.org/10.11648/j.ajtas.20150406.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20150406.12},
  abstract = {This work applied Generalized Autoregressive Conditional Heteroskedasticity (GARCH) approachto modelling volatility in Rwanda Exchange rate returns. The Autoregressive (AR) model with GARCH errors was fitted to the daily exchange rate returns using Quasi-Maximum Likelihood Estimation (Q-MLE) method to get the current volatility, asymptotic consistency and asymptotic normality of estimated parameters.Akaike Information criterion was used for appropriate GARCH model selection while Jarque Bera test used for normality testing revealed that both returns and residuals have fat tails behaviour. It was shown that the estimated model fits Rwanda exchange rate returns data well.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - Modelling the Volatility of Exchange Rates in Rwandese Markets
AU  - Jean de Dieu Ntawihebasenga
AU  - Joseph Kyalor Mung’atu
AU  - Peter Nyamuhanga Mwita
Y1  - 2015/09/25
PY  - 2015
N1  - https://doi.org/10.11648/j.ajtas.20150406.12
DO  - 10.11648/j.ajtas.20150406.12
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 426
EP  - 431
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20150406.12
AB  - This work applied Generalized Autoregressive Conditional Heteroskedasticity (GARCH) approachto modelling volatility in Rwanda Exchange rate returns. The Autoregressive (AR) model with GARCH errors was fitted to the daily exchange rate returns using Quasi-Maximum Likelihood Estimation (Q-MLE) method to get the current volatility, asymptotic consistency and asymptotic normality of estimated parameters.Akaike Information criterion was used for appropriate GARCH model selection while Jarque Bera test used for normality testing revealed that both returns and residuals have fat tails behaviour. It was shown that the estimated model fits Rwanda exchange rate returns data well.
VL  - 4
IS  - 6
ER  -

Copy | Download