with volatility …

a GARCH process for conditional volatility. Under such heteroskedasticity, OLS estimators or parameters in single … can reverse under heteroskedasticity, especially when the conditional mean and variance are both persistent. In such cases …. Heteroskedasticity can increase dramatically the apparent asymptotic power advantages of long-horizon regressions to reject constant …

Most affine models of the term structure with stochastic volatility (SV) predict that the variance of the short rate is …(3) SV model generates a time series for the variance state variable that is strongly negatively correlated with a GARCH …;unspanned stochastic volatility (USV).quot; Of the models tested, only the A1(4) USV model is found to generate both realistic volatility …

It appears that volatility in equity markets is asymmetric: returns and conditional volatility are negatively … correlated. We provide a unified framework to simultaneously investigate asymmetric volatility at the firm and the market level … empirical evidence on asymmetry to Japanese stocks. Although volatility asymmetry is present and significant at the market and …

, accounting for almost half the skewness and excess kurtosis of standard monthly GARCH residuals. Estimated volatility discounts …It is sometimes argued that an increase in stock market volatility raises required stock returns, and thus lowers stock … prices. This paper modifies the generalized autoregressive conditionally heteroskedastic (GARCH) model of returns to allow …

Recently there has been a great deal of interest in modeling volatility fluctuations. ARCH models, for example, provide … parsimonious approximations to volatility dynamics. Here we provide a selective amount of certain aspects of conditional volatility …

heteroskedasticity in their movements. In particular, we estimate a structural-form GARCH' model that includes the short-term interest …