Recent advances in financial econometrics have allowed for the construction of efficient ex post measures of daily volatility. This paper investigates the importance of instability in models of realised volatility and their corresponding forecasts. Testing for model instability is conducted with...

In this paper, we show the effects that outliers have on estimation and inference for autoregressive conditional heteroskedasticity (ARCH) models. We propose for a wide class of ARCH models commonly estimated, an empirically tractable solution to this problem by replacing outliers with their...

In this paper, we construct prediction intervals for autoregressive conditional heteroskedasticity (ARCH) models using the bootstrap. We use both a parametric and non-parametric bootstrap, which take account of parameter uncertainty. We compare our prediction intervals to traditional asymptotic...

Recent advances in the measurement of beta (systematic return risk) and volatility (total return risk), demonstrate substantial advantages in utilizing high frequency return data in a variety of settings. These advances in the measurement of beta and volatility have resulted in improvements in...