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 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 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...

This paper studies the impact of news announcements on trade durations in stocks on the Stockholm Stock Exchange. The news are categorized into four groups and the impact on the time between transactions is studied. Times before, during and after the news release are considered. Econometrically,...

The paper 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 and an outside stock exchange. Using daily data 2000-2006 for the Baltic state stock exchanges and...

This paper empirically tests whether an open limit order book contains information about future short-run stock price movements. To account for the discrete nature of price changes, the integer-valued autoregressive model of order one is utilized. A model transformation has an advantage over...

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...

Conditional heteroskedasticity properties are derived for some common count data regression and time series models. New extensions are suggested and discussed.

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>