The accuracy of parametric, non-parametric and semi-parametric methods in predicting the one-day-ahead Value-at-Risk (VaR) measure in three types of markets (stock exchanges, commodities and exchange rates) is investigated, both for long and short trading positions. The risk management...

In order to provide reliable Value-at-Risk (VaR) and Expected Shortfall (ES) forecasts, this paper attempts to investigate whether an inter-day or an intra-day model provides accurate predictions. We investigate the performance of inter-day and intra-day volatility models by estimating the...

The Basel Committee regulations require the estimation of Value-at-Risk at 99% confidence level for a 10-trading-day-ahead forecasting horizon. The paper provides a multivariate modelling framework for multi-period VaR estimates for leptokurtic and asymmetrically distributed real-estate...

In this paper an asymmetric autoregressive conditional heteroskedasticity (ARCH) model and a Levy-stable distribution are applied to some well-known financial indices (DAX30, FTSE20, FTSE100 and SP500), using a rolling sample of constant size, in order to investigate whether the values of the...

The paper constructs measures of intra-day realized volatility for 17 European and USA stock indices. We utilize a model-free de-noising method by assembling the realized volatility in sampling frequency selected according to the volatility signature plot which minimizes the micro-structure...