<![CDATA[Investigating the volatility of financial assets is fundamental to risk management. This study used generalized Autoregressive Conditional Heteroscedastic Volatility models to evaluate the volatility of the long term interest rate of Nigeria's financial market. We also incorporated three innovations distributions viz: the Gaussian, the student-t, and the Generalized Error Distribution (GED) in the modeling process under the maximum likelihood estimation method. The results show that GARCH (GED) is the most performing model for describing the volatility of three and twenty-year interest rate returns while TARCH (GED) is the most suitable model for describing the volatility of five and ten-year interest rate returns in Nigeria. The preferred models will help in the development of tools for effective risk management by monitoring the behavior of long term interest rates.]]>
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