American Journal of Applied Mathematics and Statistics
ISSN (Print): 2328-7306 ISSN (Online): 2328-7292 Website: Editor-in-chief: Mohamed Seddeek
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American Journal of Applied Mathematics and Statistics. 2014, 2(4), 179-184
DOI: 10.12691/ajams-2-4-1
Open AccessCase Study

Modeling Volatility under Normal and Student-t Distributional Assumptions (A Case Study of the Kenyan Exchange Rates)

Rotich Titus Kipkoech1,

1Department of Mathematics & Computer Science, University of Eldoret, Eldoret, Kenya

Pub. Date: June 12, 2014

Cite this paper:
Rotich Titus Kipkoech. Modeling Volatility under Normal and Student-t Distributional Assumptions (A Case Study of the Kenyan Exchange Rates). American Journal of Applied Mathematics and Statistics. 2014; 2(4):179-184. doi: 10.12691/ajams-2-4-1


The predictive performance of two EGARCH{i} models for modeling daily changes in logarithmic exchange rates (log Rt{ii}) are analyzed here. One is based on modeling the data on assumption of normal distribution and the other is based on the standardized student-t distribution. In particular, the (log Rt) of USDKES{iii}, EUROKES{iv} and GBPKES{v} are considered. For each assumption EGARCH is fitted, with varying numbers of parameters, and attempt to replicate the empirical (log Rt) sequence via simulation. Assessing the fit of each model, it is concluded that the families of EGARCH models with t-innovations adequately reflect the empirical nature of the (log Rt) sequence and therefore provides a better prediction model.

EGARCH simulation exchange rates innovations

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