Abstract
The main aim of this investigation was to model the volatility of Somali shilling against US dollar by using monthly data covering from 1950 to 2010. Further to that, this finding has adopted both symmetric and asymmetric generalized autoregressive conditional heteroscedastic (GARCH) family models in order to capture volatility clustering and leverage effect as the most stylized facts of exchange rate returns. Result from ARCH indicates presence of conditional heteroscedasticity in the residual series of exchange rate. Symmetric GARCH(1,1) model shows presence of volatility clustering and persistent coefficients of greater than one indicating that volatility is an explosive process. Results from asymmetric TCHARCH(1,1) and EGARCH(1,1) indicates presence of leverage effect in the series of exchange rate where positive news have large effect on volatility than bad news of same magnitude. This study has an important implication to investors, business and risk managers. Nevertheless, this study suggests monetary authority to print new currency and de-dollarize the economy in order to be able influence exchange rate volatility. The outcome from this finding also suggests that GARCH family models sufficiently capture the volatility of Somali shilling against US dollar. Keywords: exchange rate, Somali shilling, US dollar, conditional heteroscedasticity, volatility clustering and leverage effect JEL Classifications: F31, O24 DOI: https://doi.org/10.32479/ijefi.9788
Highlights
Exchange rate is the rate at which one currency is converted or exchanged into another
Estimation Results of generalized autoregressive conditional heteroscedastic (GARCH), Threshold generalized autoregressive conditional heteroscedasticity (TGARCH) and exponential Generalized autoregressive conditional heteroscedasticity (EGARCH) Results from GARCH(1,1) in Table 5 shows that coefficients both Autoregressive conditionally heteroscedastic (ARCH) (b) and GARCH (α) are positive except Constant (ω) which is negative but all the three coefficients are statistically significant at 1% significance level
The significance of α reveals the presence of volatility clust3ering in GARCH(1,1)
Summary
Exchange rate is the rate at which one currency is converted or exchanged into another. Since floating exchange rate become prominent across the world countries after the end of Bretton wood system modelling exchange rate by measuring its fluctuation (risk) become vital. (Abdalla, 2012) conducted finding to model exchange rate of nineteen Arab countries while using GARCH models find out the existence (Epaphra, 2016) find that current exchange rate volatility depends on its previous fluctuation and presence of leverage effect positive shocks have more effect on volatility than negative shocks of same size as he elaborated by using Tanzania shilling against USD. The biggest and smallest is 1000 Somali shilling which can faked in other way supplied in the market illegally by individuals as confirmed by (Yusuf and Abdurrahman, 2019)
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