In this note it is argued that the estimation error in Value-at-Risk predictors gives rise to underestimation of portfolio risk. We propose a simple correction and find in an empirical illustration that it is economically relevant.

In general, the properties of the conditional distribution of multiple period returns do not follow easily from the one-period data generating process. This renders computation of Value-at-Risk and Expected Shortfall for multiple period returns a non-trivial task. In this paper we consider some...

In the estimation of risk measures such as Value at Risk and Expected shortfall relatively short estimation windows are typically used rendering the estimation error a possibly non-negligible component. In this paper we build upon previous results for the Value at Risk and discuss how the...

The impact of news of the Moscow and New York stock market exchanges on the <p> returns and volatilities of the Baltic state stock market indices is studied using daily <p> return data for the period of 2000-2005. A nonlinear time series model that accounts <p> for asymmetries in the conditional mean and...</p></p></p>

This report provides analysis of qualitative research into the relationship between the internet-enabled exchanges mentioned and employability. In doing so, it focuses on three areas of crowdsourcing: using the internet to access funding (CSF); using the internet to access and undertake paid...

In the current economic context where a key policy emphasis is on employment, this project aims to inform policy of new forms of work and ways to enhance employability mediated by ICT. New applications of ICTs are continually changing the practices and possibilities of work: the way that tasks...

This thesis comprises four papers concerning risk prediction. Paper [I] suggests a nonlinear and multivariate time series model framework that enables the study of simultaneity in returns and in volatilities, as well as asymmetric effects arising from shocks. Using daily data 2000-2006 for the...

This thesis comprises four papers concerning modelling of financial count data. Paper [1], [2] <p> and [3] advance the integer-valued moving average model (INMA), a special case of integer-valued <p> autoregressive moving average (INARMA) model class, and apply the models to the number of <p> stock...</p></p></p>