I introduce two-factor discrete time stochastic
volatility models of the short-term interest rate to
compare the relative performance of existing and
alternative empiricial specificattions. I develop a
nonlinear asymmmetric framework that allows for
comparisons of non-nested models featuring
conditional heteoskedasticity and sensitivity of the
volatility process to interest rate levels. A new
class of stochastic volatility models with
asymmetric GARCH models. The existing models are
rejected in favor of the newly proposed models
because of the asymmetric drift of the short rate,
and the presence of nonlinearity, asymmetry, GARCH,
and level effects in its volatility. I test the
predictive power of nested and non-nested models in
capturing the stochastic behavior of the risk-free
rate. Empirical evidence on three-, six-, and
12-month U.S. Treasury bills indicates but that
two-factor stochastic volatility models are better
than diffusion and GARCH models in forecasting the
future level and volatility of interest rate
changes.