Application of Non Linear Models in the Determination of the Behaviour of Interest Rates in Kenya
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Date
2012-11Author
Muriuki, Anthony K
Type
ThesisLanguage
enMetadata
Show full item recordAbstract
Empirical literature shows that stock returns could be non linear. However, studies on the
non linear behavior of interest rates in developing economies are limited. This study aims
at filling this knowledge gap by comparing linear and non linear models in predicting
interest rates.
The study compared the Random Walk Model, Moving averages Models, Autoregressive
Models, Autoregressive Moving Average Models, Autoregressive Conditional
Heteroskedasticity Models. The main variable for the study was the Treasury bills
interest rate series. In Kenya, this is the Central Bank of Kenya three month Treasury bill
rate. The study applied the monthly averages of the 91-day Treasury bill rate for the
period between August 1991 and December 2011 which were obtained from the Central
Bank of Kenya. The Akaike Information Criterion (AIC) and the Bayesian Information
Criterion (BIC) also called Schwarz-Bayesian information criterion (SBC) were used to
select the best fitting model from each type of models.
The results indicate that non linear GARCH (2, 1) performs better than any other models.
This is because it has the lowest AIC and BIC values among all the models tested.
Therefore this study concluded that non linear models are better than linear models in
predicting interest rates in Kenya. Thus interest rates are non linear
Publisher
University of Nairobi School Of Business, University Of Nairobi