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Conditional Heteroscedasticity: GARCH model with application to interest rate in Ghana (2003:01 – 2013:12).

Buckman Akuffo, Enock Mintah Ampaw, Samuel Lartey

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Abstract

The development of time series model for analysis has seen a major patronage in recent times. This can mainly be attributed to the precision that is associated with these models and hence its dependence in the field of finance, statistics and economics. The theory of Generalized Autoregressive Conditional Heteroscedasticity (GARCH) was explored and monthly interest rate of Ghana from 2003:01 to 2013:12 was applied. The results shows that the best GARCH model to adequately capture the volatility in interest rest is the GARCH (1, 2). The estimated model was used to forecast interest rate for a year in Ghana and the result shows that interest rate is predicted not to hit above 30% by the end of 2014. Keywords: Autocorrelation , Conditional, GARCH, heteroscedasticity, and volatility.

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The development of time series model for analysis has seen a major patronage in recent times. This can mainly be attributed to the precision that is associated with these models and hence its dependence in the field of finance, statistics and economics. The theory of Generalized Autoregressive Conditional Heteroscedasticity (GARCH) was explored and monthly interest rate of Ghana from 2003:01 to 2013:12 was applied. The results shows that the best GARCH model to adequately capture the volatility in interest rest is the GARCH (1, 2). The estimated model was used to forecast interest rate for a year in Ghana and the result shows that interest rate is predicted not to hit above 30% by the end of 2014. Keywords: Autocorrelation , Conditional, GARCH, heteroscedasticity, and volatility.

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Available abstract

The development of time series model for analysis has seen a major patronage in recent times. This can mainly be attributed to the precision that is associated with these models and hence its dependence in the field of finance, statistics and economics. The theory of Generalized Autoregressive Conditional Heteroscedasticity (GARCH) was explored and monthly interest rate of Ghana from 2003:01 to 2013:12 was applied. The results shows that the best GARCH model to adequately capture the volatility in interest rest is the GARCH (1, 2). The estimated model was used to forecast interest rate for a year in Ghana and the result shows that interest rate is predicted not to hit above 30% by the end of 2014. Keywords: Autocorrelation , Conditional, GARCH, heteroscedasticity, and volatility.

Key concepts: Heteroscedasticity, Autoregressive conditional heteroskedasticity, Econometrics, Volatility (finance), Autoregressive model, Autocorrelation, Interest rate, Conditional variance

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Conditional Heteroscedasticity: GARCH model with application to interest rate in Ghana (2003:01 – 2013:12). — Research Paper | ScholarLens