本研究將一般短期利率模型中誤差項之常態分配換成SGED及skewed t，期望找出最佳實證配適效果。首先利用單因子CEV模型採用線性漂浮項，只考慮水準效果下，利率波動的敏感度無法正確捕捉序列相關的條件變異。接著使用間斷時間GARCH模型搭配非線性漂浮項，合併水準效果及GARCH效果於變異項後，大大降低了水準效果的參數估計值，因此認為單純考慮水準效果之利率模型對於解釋短期利率動態調整過程之波動性仍嫌不足，假設誤差項服從GED分配，並採用非線性漂浮項之GARCH模型，對於波動性的解釋及估計金融商品之相關議題更有助益。 This paper estimates the generalized and nested models with SGED and skewed t distributions to determine the correct specification of the conditional distribution of short-term interest rates. First, the paper generalized the parametric models of short-term interest rate that nest one-factor CEV model with linear drift and level effect. Second, the paper nested the discrete-time GARCH models that incorporate the level and GARCH effects into the diffusion function. The empirical research points out that the significant parametric estimate reduces the level effect for the variance function. Moreover, the results can not fully capture modeling the dynamics of short-term interest rate volatility that only with level effect. Finally, the results also show that the significance of nonlinearity in the drift function relies crucially on the specification of the volatility function.
