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标题：Modeling and Forecasting USD/UGX Volatility through GARCH Family Models: Evidence from Gaussian, T and GED Distributions
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作者：Hatice Erkekoglu ; Aweng Peter Majok Garang ; Adire Simon Deng 等
期刊名称：International Journal of Economics and Financial Issues
电子版ISSN：2146-4138
出版年度：2020
卷号：10
期号：2
页码：268-281
DOI：10.32479/ijefi.9016
出版社：EconJournals
摘要：Symmetric and asymmetric GARCH models-GARCH (1,1); PARCH(1;1); EGARCH(1,1,); TARCH(1,1) and IGARCH(1,1)- were used to examine stylized facts of daily USD/UGX return series from September 1st, 2005 to August 30th, 2018. Modeling and forecasting were performed based on Gaussian, Student’s t and GED distribution densities with a view to identifying the best distribution for examining stylized facts about the volatility of returns. Initial tests of heteroscedasticity (ARCH-LM), autocorrelation and stationarity were carried out to establish specific data requirements before modeling. Results for conditional variance indicated the presence of significant asymmetries, volatility clustering, leptokurtic distribution, and leverage effects. Effectively, PARCH (1,1) under GED distribution provided highly significant results free from serial correlation and ARCH effects, thus revealing the asymmetric responsiveness and persistence to shocks. Forecasting was performed across distributions & assessed based on symmetric lost functions (RMSE, MAE, MAPE & Thiel’s U) and information criteria (AIC, SBC & Loglikelihood). The information criteria offered a preference for EGARCH (1,1) under GED distribution while symmetric lost functions provided very competitive choices with very slight precedence for GARCH (1,1) and EGARCH (1,1) under GED distribution. Following these results, it’s recommended that PARCH (1,1) and EGARCH (1,1) be respectively preferred for modeling and forecasting volatility with GED as the choice distribution. Given the asymmetric responsiveness and persistence of conditional variance, macroeconomic & fiscal adjustments in addition to stabilization of the internal political environment are advised for Uganda.
关键词：Forecasting volatility; GARCH family Models; Probability Distribution Density; Forecast accuracy