Generating one-month-ahead systematic (beta) risk forecasts is common place in financial management. This paper evaluates the accuracy of these beta forecasts in three return measurement settings; monthly, daily and 30 minutes. It is found that the popular Fama-MacBeth beta from 5 years of...

The last decade has seen substantial advances in the measurement, modeling and forecasting of volatility which has centered around the realized volatility literature. To date, most of the focus has been on the daily and monthly frequency, with little attention on longer horizons such as the...

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...

For the major foreign exchange rates, it is found that the optimal modelling frequency of volatility is weekly for forecast horizons ranging from 1 week up to 1 month. Autoregressive modelling is based on realized volatility measures computed from 30 min returns