Filtering techniques are often applied to the estimation of dynamic latent variable models. However, these techniques … empirical performance of this algorithm is considered within the context of the stochastic volatility model. It is found that … the proposed algorithm outperforms a number of accepted procedures in terms of volatility forecasti …

significant in volatility as opposed to expected returns. This paper seeks an explanation for this empirical finding by … volatility model, in which the conditional daily volatility is measured in calendar time from open-to-close of the market, and … over weekends and especially holidays is a predictor of subsequent daily volatility. The SV parameters are estimated by …

The stochastic volatility (SV) models had not been popular as the ARCH (autoregressive conditional heteroskedasticity …) approximates the marginal likelihood of the observable process by simulating the latent volatility conditional on the available … information. Shephard and Pitt (1997) gave an idea of evaluating likelihood by exploiting sampled volatility. Durbin and Koopman …

is shown that the nonstationarity of volatility in the regression errors may induce spuriousness of the underlying … nonstationary volatility is present in the errors. Mild nonstationary volatilities do not render the underlying regression spurious … invalid. In the paper, we develop an unbiased and efficient method of estimation and a chi-square test applicable for the …

This paper investigates the effect of exchange rate volatility on US-UK bilateral trade flows. As part of econometric …

Previous analytical models focused on the effects of the real exchange rate (RER) and the RER volatility on Chinese … dollar because the negative impacts of the revaluation, and its accompanying effects on the RER volatility, if any, on the …