In this paper, a local 𝑀-estimation for the conditional variance function in heteroscedastic regression models under stationary α-mixing dependent samples is developed. The local 𝑀-estimator is ...

We propose a new combined semiparametric estimator, which incorporates the parametric and nonparametric estimators of the conditional variance in a multiplicative way. We derive the asymptotic bias, ...

The exponentially weighted moving average (EWMA) estimator is widely used to forecast the conditional volatility of short-horizon asset returns. The EWMA estimator is appropriate when returns are ...

There are several approaches to dealing with heteroscedasticity. If the error variance at different times is known, weighted regression is a good method. If, as is ...

This issue of the Journal of Risk contains four long papers dealing with market risk management. The first paper, “Risk estimation using the normal inverse Gaussian distribution”, by P. J. de Jongh ...