We show that, when allowing for general distributions of dividend growth in a Lucas economy with multiple "trees," idiosyncratic volatility will affect expected returns in ways that are not captured by the log linear approximation. We derive an exact expression for the risk premia for general...

This paper decomposes the popular risk measure Value-at-Risk (VaR) into one jump- and one continuous component. The continuous component corresponds to general market risk and the jump component is proportional to the event risk as defined in the Basel II accord. We find that event risk, which...

A new model for financial returns with time varying variance, skewness and kurtosis based on the Normal Inverse Gaussian (NIG) distribution is proposed. The new model and two previously suggested NIG models are evaluated by their Value at Risk (VaR) forecasts on a long series of daily Standard...

This paper investigates the forecasting performance of the Garch (1, 1) model when estimated with NINE different error distributions on Standard and Poor's 500 Index Future returns. By utilizing the theory of realized variance to construct an appropriate ex post measure of volatility from...

We derive exact expressions for the risk premia for general distributions in a Lucas economy and show that the errors when using log-linear approximations can be economically significant when the shocks are nonnormal. Assuming growth rates are Normal Inverse Gaussian (NIG) and fitting the...